In-Depth Review of the I-have-ADHD Skill
This skill makes coding agents lead with the answer, summarize what they did, and include only the necessary details. It is therefore well suited to debugging, code reviews, or test-result summaries where readers need the key points quickly.
It works especially well when the response format is defined in advance—for example, stating the cause, relevant files, fix, and verification results. For complex tasks, the agent should also be allowed to ask follow-up questions or state limitations; otherwise, the response may become so short that it skips important conditions.
The limitation is that the skill does not make the agent reason more accurately, and it may remove necessary details. The hidden cost is that users must write rules suited to each task and verify that conciseness has not come at the expense of completeness.
In-Depth Review of the I-have-ADHD Skill
This skill makes coding agents lead with the answer, summarize what they did, and include only the necessary details. It is therefore well suited to debugging, code reviews, or test-result summaries where readers need the key points quickly.
It works especially well when the response format is defined in advance—for example, stating the cause, relevant files, fix, and verification results. For complex tasks, the agent should also be allowed to ask follow-up questions or state limitations; otherwise, the response may become so short that it skips important conditions.
The limitation is that the skill does not make the agent reason more accurately, and it may remove necessary details. The hidden cost is that users must write rules suited to each task and verify that conciseness has not come at the expense of completeness.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we open a task, we do not see the result immediately. Instead, we have to work through the activity log, modified code, options the agent tried, and lengthy explanations before we know what it actually accomplished.
Time that should be spent reviewing code is consumed searching for the answer in the text. It is easy to lose focus, and if we need to look back at where the agent went wrong, we may have to reread everything several times. The more urgent the task, the more likely we are to overlook important results or conditions that have not yet been checked.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we open a task, we do not see the result immediately. Instead, we have to work through the activity log, modified code, options the agent tried, and lengthy explanations before we know what it actually accomplished.
Time that should be spent reviewing code is consumed searching for the answer in the text. It is easy to lose focus, and if we need to look back at where the agent went wrong, we may have to reread everything several times. The more urgent the task, the more likely we are to overlook important results or conditions that have not yet been checked.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD operates at the communication layer of a coding agent. It organizes the response so the agent states the important points first—for example, what was completed, what problems occurred, and what the user should do next. It is not a new model and does not modify code directly.
It works alongside the agent already in use by filtering the activity log, attempted options, and intermediate details into an answer that is easy to read and verify. The agent still analyzes and modifies the code, while this skill ensures that the result is not buried in a long block of text.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD operates at the communication layer of a coding agent. It organizes the response so the agent states the important points first—for example, what was completed, what problems occurred, and what the user should do next. It is not a new model and does not modify code directly.
It works alongside the agent already in use by filtering the activity log, attempted options, and intermediate details into an answer that is easy to read and verify. The agent still analyzes and modifies the code, while this skill ensures that the result is not buried in a long block of text.
What the Skill Contains and How It Changes the Shape of the Answer
This skill requires the agent to place the “main answer” at the top, followed by the task status and necessary technical details. The trial-and-error log is moved to the end of the answer or shortened.
Before using the skill, readers must work through a long message to determine how far the task has progressed. After using it, the key points are immediately visible, with a clear distinction between what has been completed, what remains pending, and what should happen next.
What the Skill Contains and How It Changes the Shape of the Answer
This skill requires the agent to place the “main answer” at the top, followed by the task status and necessary technical details. The trial-and-error log is moved to the end of the answer or shortened.
Before using the skill, readers must work through a long message to determine how far the task has progressed. After using it, the key points are immediately visible, with a clear distinction between what has been completed, what remains pending, and what should happen next.
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a lengthy report into something more like a teammate who knows what to communicate first. Important details are still retained, but they are placed where they can be easily viewed when needed.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | At the end of a long introduction | Immediately near the beginning |
| Introduction | Detailed process narrative | Summary of only what is necessary |
| Task status | Must be read and interpreted manually | Completed and pending work clearly separated |
| Next step | Unclear what to do next | Next steps provided to follow |
| Verification details | Plentiful but mixed with explanations | Retained as supporting evidence |
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a lengthy report into something more like a teammate who knows what to communicate first. Important details are still retained, but they are placed where they can be easily viewed when needed.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | At the end of a long introduction | Immediately near the beginning |
| Introduction | Detailed process narrative | Summary of only what is necessary |
| Task status | Must be read and interpreted manually | Completed and pending work clearly separated |
| Next step | Unclear what to do next | Next steps provided to follow |
| Verification details | Plentiful but mixed with explanations | Retained as supporting evidence |
What It Is Like to Use in Situations That Require Speed
When fixing a bug, the answer should begin with the result: what was fixed and whether the symptom is gone, followed by the cause and commands that can be used immediately for verification.
If a command takes a long time to run, the agent should provide a status update first—for example, what it is doing, how long it may take, and what the user can do next. While waiting, it should not dump lengthy logs that obscure the main point.
For tasks involving multiple files, the response should use a list that clearly separates the modified files, reasons, and impact, while also identifying pending work. This format makes review faster because there is no need to excavate the answer from a large pile of text.
After modifying code, the response should end with a brief summary separating “what changed,” “how it was checked,” and “next steps,” while retaining the full details as supporting evidence.
What It Is Like to Use in Situations That Require Speed
When fixing a bug, the answer should begin with the result: what was fixed and whether the symptom is gone, followed by the cause and commands that can be used immediately for verification.
If a command takes a long time to run, the agent should provide a status update first—for example, what it is doing, how long it may take, and what the user can do next. While waiting, it should not dump lengthy logs that obscure the main point.
For tasks involving multiple files, the response should use a list that clearly separates the modified files, reasons, and impact, while also identifying pending work. This format makes review faster because there is no need to excavate the answer from a large pile of text.
After modifying code, the response should end with a brief summary separating “what changed,” “how it was checked,” and “next steps,” while retaining the full details as supporting evidence.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a consistent summary format without having to repeat instructions for every command. A system prompt is more flexible, but users must maintain the rules themselves, and it may affect tasks that require multiple response formats.
| Factor | I-have-ADHD | Write your own system prompt | Specify the format for every command |
|---|---|---|---|
| Installation | Easy and reusable | Must write and adjust it yourself | No installation required |
| Consistency | High | Depends on the prompt | Depends on repeating the instruction each time |
| Flexibility | Adjustable to the task | High | High |
| Maintenance burden | Low | High | High |
If you work with coding agents regularly, I-have-ADHD clearly reduces repetitive overhead. However, a system prompt remains more suitable when a team needs detailed control over its own rules.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a consistent summary format without having to repeat instructions for every command. A system prompt is more flexible, but users must maintain the rules themselves, and it may affect tasks that require multiple response formats.
| Factor | I-have-ADHD | Write your own system prompt | Specify the format for every command |
|---|---|---|---|
| Installation | Easy and reusable | Must write and adjust it yourself | No installation required |
| Consistency | High | Depends on the prompt | Depends on repeating the instruction each time |
| Flexibility | Adjustable to the task | High | High |
| Maintenance burden | Low | High | High |
If you work with coding agents regularly, I-have-ADHD clearly reduces repetitive overhead. However, a system prompt remains more suitable when a team needs detailed control over its own rules.
Strengths That Make This Skill Worth Using—and Points to Watch Out For
I-have-ADHD brings important answers to the forefront, reduces the time spent searching through long messages, and makes it easier to check task status. It is well suited to days when you need to switch between multiple tasks or do not want to read lengthy reports.
The risk is that a summary may omit necessary details or misunderstand the context. Users should therefore verify whether the task is actually complete, because a short answer does not mean the agent’s work is finished.
Pros
- +Reduces the time spent searching for answers
- +Makes task status easier to check
- +Reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly
- −Risk of assuming the task is complete while work remains
Strengths That Make This Skill Worth Using—and Points to Watch Out For
I-have-ADHD brings important answers to the forefront, reduces the time spent searching through long messages, and makes it easier to check task status. It is well suited to days when you need to switch between multiple tasks or do not want to read lengthy reports.
The risk is that a summary may omit necessary details or misunderstand the context. Users should therefore verify whether the task is actually complete, because a short answer does not mean the agent’s work is finished.
Pros
- +Reduces the time spent searching for answers
- +Makes task status easier to check
- +Reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly
- −Risk of assuming the task is complete while work remains
The Real Costs That Do Not Appear in the Installation Command
The hidden cost is not limited to the time required to install the skill. It also includes the time spent adjusting the prompt to fit the task and checking whether logs, errors, or important steps have been omitted from the answer. If the agent misunderstands the context, you must spend additional time correcting it and repeating instructions.
Results also vary by agent and workflow. Some agents summarize well when the task has clearly defined steps, while others may remove too much detail—especially during debugging, when a small error can affect the solution.
Therefore, this skill genuinely reduces the reading burden, but it should be used alongside checking the original answer and defining what must not be omitted, so brevity does not become a source of risk.
The Real Costs That Do Not Appear in the Installation Command
The hidden cost is not limited to the time required to install the skill. It also includes the time spent adjusting the prompt to fit the task and checking whether logs, errors, or important steps have been omitted from the answer. If the agent misunderstands the context, you must spend additional time correcting it and repeating instructions.
Results also vary by agent and workflow. Some agents summarize well when the task has clearly defined steps, while others may remove too much detail—especially during debugging, when a small error can affect the solution.
Therefore, this skill genuinely reduces the reading burden, but it should be used alongside checking the original answer and defining what must not be omitted, so brevity does not become a source of risk.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of I-have-ADHD is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, status, and decisions requiring attention appear before the details. Readers can immediately see how far the task has progressed and which supporting evidence they need to open next.
A clear way to test it is to choose one type of task, such as debugging, and use the skill several times. Measure the time spent actually reviewing the answers, compare it with the previous workflow, and check whether important details have disappeared. If review time decreases while you can still follow the reasoning and solve the problem completely, that is a sign the skill is genuinely helping.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of I-have-ADHD is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, status, and decisions requiring attention appear before the details. Readers can immediately see how far the task has progressed and which supporting evidence they need to open next.
A clear way to test it is to choose one type of task, such as debugging, and use the skill several times. Measure the time spent actually reviewing the answers, compare it with the previous workflow, and check whether important details have disappeared. If review time decreases while you can still follow the reasoning and solve the problem completely, that is a sign the skill is genuinely helping.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we ask a coding agent to help debug, we may have to work through the activity log, modified code, attempted options, and lengthy explanations before discovering whether the issue was actually fixed.
Work that should be reviewed quickly instead consumes time and attention with unnecessary details. The more times we need to check it, the greater the risk of missing an important result or failing to see which parts of the code the agent changed.
The problem this skill addresses is therefore not merely making answers shorter. It is organizing the answer so the result, reasoning, and next steps are immediately visible, making continued review smoother.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we ask a coding agent to help debug, we may have to work through the activity log, modified code, attempted options, and lengthy explanations before discovering whether the issue was actually fixed.
Work that should be reviewed quickly instead consumes time and attention with unnecessary details. The more times we need to check it, the greater the risk of missing an important result or failing to see which parts of the code the agent changed.
The problem this skill addresses is therefore not merely making answers shorter. It is organizing the answer so the result, reasoning, and next steps are immediately visible, making continued review smoother.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD is a skill for communication and response prioritization. It is not a new model and does not modify code directly.
It works alongside the coding agent already in use by organizing the response to begin with the key result, followed by the reasoning, changes made, and next steps. Users can understand the situation more quickly without changing the agent or primary tools they already use.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD is a skill for communication and response prioritization. It is not a new model and does not modify code directly.
It works alongside the coding agent already in use by organizing the response to begin with the key result, followed by the reasoning, changes made, and next steps. Users can understand the situation more quickly without changing the agent or primary tools they already use.
What the Skill Contains and How It Changes the Shape of the Answer
Before using the skill, answers often begin with lengthy technical details, forcing readers to work through the message before finding the result and task status. After using the skill, the main answer appears at the top, followed by the task status, reasoning, and technical details. Logs and secondary points are moved to the end of the answer.
What the Skill Contains and How It Changes the Shape of the Answer
Before using the skill, answers often begin with lengthy technical details, forcing readers to work through the message before finding the result and task status. After using the skill, the main answer appears at the top, followed by the task status, reasoning, and technical details. Logs and secondary points are moved to the end of the answer.
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a step-by-step narration into a response that presents the result first and then reveals only the necessary details. Readers immediately know how far the task has progressed and what needs to happen next.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | Hidden at the end of the message | At the top |
| Introduction | Long and indirect | Short and to the point |
| Task status | Must read the message to understand it | Clearly presented |
| next step | Unclear what to do next | Next steps specified |
| Verification details | All information is dumped together | Only necessary parts are retained |
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a step-by-step narration into a response that presents the result first and then reveals only the necessary details. Readers immediately know how far the task has progressed and what needs to happen next.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | Hidden at the end of the message | At the top |
| Introduction | Long and indirect | Short and to the point |
| Task status | Must read the message to understand it | Clearly presented |
| next step | Unclear what to do next | Next steps specified |
| Verification details | All information is dumped together | Only necessary parts are retained |
What It Is Like to Use in Situations That Require Speed
When fixing a bug where the result is needed immediately, have the agent begin with the cause, test status, and whether the check passed, then attach the necessary details. This avoids having to work through lengthy logs.
If a command takes a long time to run, state what is being done, the latest status, and the next step first. Tasks involving multiple files should be summarized by file, including the impact and areas that need checking.
After modifying code, end with a brief summary of what changed, what was tested, and what remains pending. This format makes the answer visible quickly, even when the background work is not yet complete.
What It Is Like to Use in Situations That Require Speed
When fixing a bug where the result is needed immediately, have the agent begin with the cause, test status, and whether the check passed, then attach the necessary details. This avoids having to work through lengthy logs.
If a command takes a long time to run, state what is being done, the latest status, and the next step first. Tasks involving multiple files should be summarized by file, including the impact and areas that need checking.
After modifying code, end with a brief summary of what changed, what was tested, and what remains pending. This format makes the answer visible quickly, even when the background work is not yet complete.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a clear response format for every task without having to repeat reminders. A system prompt offers greater control, but users must maintain the rules themselves whenever the task format changes.
| Factor | I-have-ADHD | Write your own system prompt | General result-summary skill | Specify the format for every command |
|---|---|---|---|---|
| Installation | Easy | Must write and adjust it yourself | Easy | No installation required |
| Consistency | High | Depends on the rules written | Focuses on summaries more than process | Depends on the instruction given each time |
| Flexibility | Adaptable to different tasks | High | Limited by its objective | High |
| Self-maintenance burden | Low | High | Low | High |
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a clear response format for every task without having to repeat reminders. A system prompt offers greater control, but users must maintain the rules themselves whenever the task format changes.
| Factor | I-have-ADHD | Write your own system prompt | General result-summary skill | Specify the format for every command |
|---|---|---|---|---|
| Installation | Easy | Must write and adjust it yourself | Easy | No installation required |
| Consistency | High | Depends on the rules written | Focuses on summaries more than process | Depends on the instruction given each time |
| Flexibility | Adaptable to different tasks | High | Limited by its objective | High |
| Self-maintenance burden | Low | High | Low | High |
Strengths That Make This Skill Worth Using—and Points to Watch Out For
Pros
- +Reduces the time spent searching for answers in long conversations
- +Makes task status easier to check and reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly if the rules are unclear
- −May make users think the task is complete when work remains
Strengths That Make This Skill Worth Using—and Points to Watch Out For
Pros
- +Reduces the time spent searching for answers in long conversations
- +Makes task status easier to check and reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly if the rules are unclear
- −May make users think the task is complete when work remains
The Real Costs That Do Not Appear in the Installation Command
The hidden cost of this skill is the time spent adjusting the prompt to suit the behavior of each agent. If the rules are unclear, the agent may summarize too aggressively and omit important logs or errors, forcing users to reread the conversation and correct misunderstandings themselves.
Results also depend on the workflow. Tasks with fixed steps may produce consistent summaries, but agents that work through multiple iterations or frequently changing contexts may report progress even when work remains. Therefore, check the summary against the actual status every time, especially before delivering the work.
The Real Costs That Do Not Appear in the Installation Command
The hidden cost of this skill is the time spent adjusting the prompt to suit the behavior of each agent. If the rules are unclear, the agent may summarize too aggressively and omit important logs or errors, forcing users to reread the conversation and correct misunderstandings themselves.
Results also depend on the workflow. Tasks with fixed steps may produce consistent summaries, but agents that work through multiple iterations or frequently changing contexts may report progress even when work remains. Therefore, check the summary against the actual status every time, especially before delivering the work.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of the I-have-ADHD skill is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, task status, and decisions requiring attention appear before the details, allowing readers to continue reviewing the work immediately.
Try using the skill with one type of task first, such as bug fixing, and measure the time spent actually reviewing the work compared with the previous workflow. Also check whether the answer still contains enough information to confirm the result and identify any pending work.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of the I-have-ADHD skill is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, task status, and decisions requiring attention appear before the details, allowing readers to continue reviewing the work immediately.
Try using the skill with one type of task first, such as bug fixing, and measure the time spent actually reviewing the work compared with the previous workflow. Also check whether the answer still contains enough information to confirm the result and identify any pending work.
In-Depth Review of the I-have-ADHD Skill
This skill makes coding agents lead with the answer, summarize what they did, and include only the necessary details. It is therefore well suited to debugging, code reviews, or test-result summaries where readers need the key points quickly.
It works especially well when the response format is defined in advance—for example, stating the cause, relevant files, fix, and verification results. For complex tasks, the agent should also be allowed to ask follow-up questions or state limitations; otherwise, the response may become so short that it skips important conditions.
The limitation is that the skill does not make the agent reason more accurately, and it may remove necessary details. The hidden cost is that users must write rules suited to each task and verify that conciseness has not come at the expense of completeness.
In-Depth Review of the I-have-ADHD Skill
This skill makes coding agents lead with the answer, summarize what they did, and include only the necessary details. It is therefore well suited to debugging, code reviews, or test-result summaries where readers need the key points quickly.
It works especially well when the response format is defined in advance—for example, stating the cause, relevant files, fix, and verification results. For complex tasks, the agent should also be allowed to ask follow-up questions or state limitations; otherwise, the response may become so short that it skips important conditions.
The limitation is that the skill does not make the agent reason more accurately, and it may remove necessary details. The hidden cost is that users must write rules suited to each task and verify that conciseness has not come at the expense of completeness.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we open a task, we do not see the result immediately. Instead, we have to work through the activity log, modified code, options the agent tried, and lengthy explanations before we know what it actually accomplished.
Time that should be spent reviewing code is consumed searching for the answer in the text. It is easy to lose focus, and if we need to look back at where the agent went wrong, we may have to reread everything several times. The more urgent the task, the more likely we are to overlook important results or conditions that have not yet been checked.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we open a task, we do not see the result immediately. Instead, we have to work through the activity log, modified code, options the agent tried, and lengthy explanations before we know what it actually accomplished.
Time that should be spent reviewing code is consumed searching for the answer in the text. It is easy to lose focus, and if we need to look back at where the agent went wrong, we may have to reread everything several times. The more urgent the task, the more likely we are to overlook important results or conditions that have not yet been checked.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD operates at the communication layer of a coding agent. It organizes the response so the agent states the important points first—for example, what was completed, what problems occurred, and what the user should do next. It is not a new model and does not modify code directly.
It works alongside the agent already in use by filtering the activity log, attempted options, and intermediate details into an answer that is easy to read and verify. The agent still analyzes and modifies the code, while this skill ensures that the result is not buried in a long block of text.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD operates at the communication layer of a coding agent. It organizes the response so the agent states the important points first—for example, what was completed, what problems occurred, and what the user should do next. It is not a new model and does not modify code directly.
It works alongside the agent already in use by filtering the activity log, attempted options, and intermediate details into an answer that is easy to read and verify. The agent still analyzes and modifies the code, while this skill ensures that the result is not buried in a long block of text.
What the Skill Contains and How It Changes the Shape of the Answer
This skill requires the agent to place the “main answer” at the top, followed by the task status and necessary technical details. The trial-and-error log is moved to the end of the answer or shortened.
Before using the skill, readers must work through a long message to determine how far the task has progressed. After using it, the key points are immediately visible, with a clear distinction between what has been completed, what remains pending, and what should happen next.
What the Skill Contains and How It Changes the Shape of the Answer
This skill requires the agent to place the “main answer” at the top, followed by the task status and necessary technical details. The trial-and-error log is moved to the end of the answer or shortened.
Before using the skill, readers must work through a long message to determine how far the task has progressed. After using it, the key points are immediately visible, with a clear distinction between what has been completed, what remains pending, and what should happen next.
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a lengthy report into something more like a teammate who knows what to communicate first. Important details are still retained, but they are placed where they can be easily viewed when needed.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | At the end of a long introduction | Immediately near the beginning |
| Introduction | Detailed process narrative | Summary of only what is necessary |
| Task status | Must be read and interpreted manually | Completed and pending work clearly separated |
| Next step | Unclear what to do next | Next steps provided to follow |
| Verification details | Plentiful but mixed with explanations | Retained as supporting evidence |
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a lengthy report into something more like a teammate who knows what to communicate first. Important details are still retained, but they are placed where they can be easily viewed when needed.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | At the end of a long introduction | Immediately near the beginning |
| Introduction | Detailed process narrative | Summary of only what is necessary |
| Task status | Must be read and interpreted manually | Completed and pending work clearly separated |
| Next step | Unclear what to do next | Next steps provided to follow |
| Verification details | Plentiful but mixed with explanations | Retained as supporting evidence |
What It Is Like to Use in Situations That Require Speed
When fixing a bug, the answer should begin with the result: what was fixed and whether the symptom is gone, followed by the cause and commands that can be used immediately for verification.
If a command takes a long time to run, the agent should provide a status update first—for example, what it is doing, how long it may take, and what the user can do next. While waiting, it should not dump lengthy logs that obscure the main point.
For tasks involving multiple files, the response should use a list that clearly separates the modified files, reasons, and impact, while also identifying pending work. This format makes review faster because there is no need to excavate the answer from a large pile of text.
After modifying code, the response should end with a brief summary separating “what changed,” “how it was checked,” and “next steps,” while retaining the full details as supporting evidence.
What It Is Like to Use in Situations That Require Speed
When fixing a bug, the answer should begin with the result: what was fixed and whether the symptom is gone, followed by the cause and commands that can be used immediately for verification.
If a command takes a long time to run, the agent should provide a status update first—for example, what it is doing, how long it may take, and what the user can do next. While waiting, it should not dump lengthy logs that obscure the main point.
For tasks involving multiple files, the response should use a list that clearly separates the modified files, reasons, and impact, while also identifying pending work. This format makes review faster because there is no need to excavate the answer from a large pile of text.
After modifying code, the response should end with a brief summary separating “what changed,” “how it was checked,” and “next steps,” while retaining the full details as supporting evidence.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a consistent summary format without having to repeat instructions for every command. A system prompt is more flexible, but users must maintain the rules themselves, and it may affect tasks that require multiple response formats.
| Factor | I-have-ADHD | Write your own system prompt | Specify the format for every command |
|---|---|---|---|
| Installation | Easy and reusable | Must write and adjust it yourself | No installation required |
| Consistency | High | Depends on the prompt | Depends on repeating the instruction each time |
| Flexibility | Adjustable to the task | High | High |
| Maintenance burden | Low | High | High |
If you work with coding agents regularly, I-have-ADHD clearly reduces repetitive overhead. However, a system prompt remains more suitable when a team needs detailed control over its own rules.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a consistent summary format without having to repeat instructions for every command. A system prompt is more flexible, but users must maintain the rules themselves, and it may affect tasks that require multiple response formats.
| Factor | I-have-ADHD | Write your own system prompt | Specify the format for every command |
|---|---|---|---|
| Installation | Easy and reusable | Must write and adjust it yourself | No installation required |
| Consistency | High | Depends on the prompt | Depends on repeating the instruction each time |
| Flexibility | Adjustable to the task | High | High |
| Maintenance burden | Low | High | High |
If you work with coding agents regularly, I-have-ADHD clearly reduces repetitive overhead. However, a system prompt remains more suitable when a team needs detailed control over its own rules.
Strengths That Make This Skill Worth Using—and Points to Watch Out For
I-have-ADHD brings important answers to the forefront, reduces the time spent searching through long messages, and makes it easier to check task status. It is well suited to days when you need to switch between multiple tasks or do not want to read lengthy reports.
The risk is that a summary may omit necessary details or misunderstand the context. Users should therefore verify whether the task is actually complete, because a short answer does not mean the agent’s work is finished.
Pros
- +Reduces the time spent searching for answers
- +Makes task status easier to check
- +Reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly
- −Risk of assuming the task is complete while work remains
Strengths That Make This Skill Worth Using—and Points to Watch Out For
I-have-ADHD brings important answers to the forefront, reduces the time spent searching through long messages, and makes it easier to check task status. It is well suited to days when you need to switch between multiple tasks or do not want to read lengthy reports.
The risk is that a summary may omit necessary details or misunderstand the context. Users should therefore verify whether the task is actually complete, because a short answer does not mean the agent’s work is finished.
Pros
- +Reduces the time spent searching for answers
- +Makes task status easier to check
- +Reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly
- −Risk of assuming the task is complete while work remains
The Real Costs That Do Not Appear in the Installation Command
The hidden cost is not limited to the time required to install the skill. It also includes the time spent adjusting the prompt to fit the task and checking whether logs, errors, or important steps have been omitted from the answer. If the agent misunderstands the context, you must spend additional time correcting it and repeating instructions.
Results also vary by agent and workflow. Some agents summarize well when the task has clearly defined steps, while others may remove too much detail—especially during debugging, when a small error can affect the solution.
Therefore, this skill genuinely reduces the reading burden, but it should be used alongside checking the original answer and defining what must not be omitted, so brevity does not become a source of risk.
The Real Costs That Do Not Appear in the Installation Command
The hidden cost is not limited to the time required to install the skill. It also includes the time spent adjusting the prompt to fit the task and checking whether logs, errors, or important steps have been omitted from the answer. If the agent misunderstands the context, you must spend additional time correcting it and repeating instructions.
Results also vary by agent and workflow. Some agents summarize well when the task has clearly defined steps, while others may remove too much detail—especially during debugging, when a small error can affect the solution.
Therefore, this skill genuinely reduces the reading burden, but it should be used alongside checking the original answer and defining what must not be omitted, so brevity does not become a source of risk.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of I-have-ADHD is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, status, and decisions requiring attention appear before the details. Readers can immediately see how far the task has progressed and which supporting evidence they need to open next.
A clear way to test it is to choose one type of task, such as debugging, and use the skill several times. Measure the time spent actually reviewing the answers, compare it with the previous workflow, and check whether important details have disappeared. If review time decreases while you can still follow the reasoning and solve the problem completely, that is a sign the skill is genuinely helping.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of I-have-ADHD is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, status, and decisions requiring attention appear before the details. Readers can immediately see how far the task has progressed and which supporting evidence they need to open next.
A clear way to test it is to choose one type of task, such as debugging, and use the skill several times. Measure the time spent actually reviewing the answers, compare it with the previous workflow, and check whether important details have disappeared. If review time decreases while you can still follow the reasoning and solve the problem completely, that is a sign the skill is genuinely helping.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we ask a coding agent to help debug, we may have to work through the activity log, modified code, attempted options, and lengthy explanations before discovering whether the issue was actually fixed.
Work that should be reviewed quickly instead consumes time and attention with unnecessary details. The more times we need to check it, the greater the risk of missing an important result or failing to see which parts of the code the agent changed.
The problem this skill addresses is therefore not merely making answers shorter. It is organizing the answer so the result, reasoning, and next steps are immediately visible, making continued review smoother.
When the Agent’s Answer Is Buried Beneath a Wall of Text
When we ask a coding agent to help debug, we may have to work through the activity log, modified code, attempted options, and lengthy explanations before discovering whether the issue was actually fixed.
Work that should be reviewed quickly instead consumes time and attention with unnecessary details. The more times we need to check it, the greater the risk of missing an important result or failing to see which parts of the code the agent changed.
The problem this skill addresses is therefore not merely making answers shorter. It is organizing the answer so the result, reasoning, and next steps are immediately visible, making continued review smoother.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD is a skill for communication and response prioritization. It is not a new model and does not modify code directly.
It works alongside the coding agent already in use by organizing the response to begin with the key result, followed by the reasoning, changes made, and next steps. Users can understand the situation more quickly without changing the agent or primary tools they already use.
Where This Skill Appears in a Coding Agent’s Toolkit
I-have-ADHD is a skill for communication and response prioritization. It is not a new model and does not modify code directly.
It works alongside the coding agent already in use by organizing the response to begin with the key result, followed by the reasoning, changes made, and next steps. Users can understand the situation more quickly without changing the agent or primary tools they already use.
What the Skill Contains and How It Changes the Shape of the Answer
Before using the skill, answers often begin with lengthy technical details, forcing readers to work through the message before finding the result and task status. After using the skill, the main answer appears at the top, followed by the task status, reasoning, and technical details. Logs and secondary points are moved to the end of the answer.
What the Skill Contains and How It Changes the Shape of the Answer
Before using the skill, answers often begin with lengthy technical details, forcing readers to work through the message before finding the result and task status. After using the skill, the main answer appears at the top, followed by the task status, reasoning, and technical details. Logs and secondary points are moved to the end of the answer.
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a step-by-step narration into a response that presents the result first and then reveals only the necessary details. Readers immediately know how far the task has progressed and what needs to happen next.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | Hidden at the end of the message | At the top |
| Introduction | Long and indirect | Short and to the point |
| Task status | Must read the message to understand it | Clearly presented |
| next step | Unclear what to do next | Next steps specified |
| Verification details | All information is dumped together | Only necessary parts are retained |
From an Agent That Tells You Everything to One That Leads with What Matters
This skill changes the answer from a step-by-step narration into a response that presents the result first and then reveals only the necessary details. Readers immediately know how far the task has progressed and what needs to happen next.
| Factor | Before using the skill | After using the skill |
|---|---|---|
| Answer position | Hidden at the end of the message | At the top |
| Introduction | Long and indirect | Short and to the point |
| Task status | Must read the message to understand it | Clearly presented |
| next step | Unclear what to do next | Next steps specified |
| Verification details | All information is dumped together | Only necessary parts are retained |
What It Is Like to Use in Situations That Require Speed
When fixing a bug where the result is needed immediately, have the agent begin with the cause, test status, and whether the check passed, then attach the necessary details. This avoids having to work through lengthy logs.
If a command takes a long time to run, state what is being done, the latest status, and the next step first. Tasks involving multiple files should be summarized by file, including the impact and areas that need checking.
After modifying code, end with a brief summary of what changed, what was tested, and what remains pending. This format makes the answer visible quickly, even when the background work is not yet complete.
What It Is Like to Use in Situations That Require Speed
When fixing a bug where the result is needed immediately, have the agent begin with the cause, test status, and whether the check passed, then attach the necessary details. This avoids having to work through lengthy logs.
If a command takes a long time to run, state what is being done, the latest status, and the next step first. Tasks involving multiple files should be summarized by file, including the impact and areas that need checking.
After modifying code, end with a brief summary of what changed, what was tested, and what remains pending. This format makes the answer visible quickly, even when the background work is not yet complete.
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a clear response format for every task without having to repeat reminders. A system prompt offers greater control, but users must maintain the rules themselves whenever the task format changes.
| Factor | I-have-ADHD | Write your own system prompt | General result-summary skill | Specify the format for every command |
|---|---|---|---|---|
| Installation | Easy | Must write and adjust it yourself | Easy | No installation required |
| Consistency | High | Depends on the rules written | Focuses on summaries more than process | Depends on the instruction given each time |
| Flexibility | Adaptable to different tasks | High | Limited by its objective | High |
| Self-maintenance burden | Low | High | Low | High |
Compared with Other Methods for Making Agents Respond More Concisely
I-have-ADHD suits people who want a clear response format for every task without having to repeat reminders. A system prompt offers greater control, but users must maintain the rules themselves whenever the task format changes.
| Factor | I-have-ADHD | Write your own system prompt | General result-summary skill | Specify the format for every command |
|---|---|---|---|---|
| Installation | Easy | Must write and adjust it yourself | Easy | No installation required |
| Consistency | High | Depends on the rules written | Focuses on summaries more than process | Depends on the instruction given each time |
| Flexibility | Adaptable to different tasks | High | Limited by its objective | High |
| Self-maintenance burden | Low | High | Low | High |
Strengths That Make This Skill Worth Using—and Points to Watch Out For
Pros
- +Reduces the time spent searching for answers in long conversations
- +Makes task status easier to check and reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly if the rules are unclear
- −May make users think the task is complete when work remains
Strengths That Make This Skill Worth Using—and Points to Watch Out For
Pros
- +Reduces the time spent searching for answers in long conversations
- +Makes task status easier to check and reduces reading burden
Cons
- −May omit necessary details
- −May summarize the context incorrectly if the rules are unclear
- −May make users think the task is complete when work remains
The Real Costs That Do Not Appear in the Installation Command
The hidden cost of this skill is the time spent adjusting the prompt to suit the behavior of each agent. If the rules are unclear, the agent may summarize too aggressively and omit important logs or errors, forcing users to reread the conversation and correct misunderstandings themselves.
Results also depend on the workflow. Tasks with fixed steps may produce consistent summaries, but agents that work through multiple iterations or frequently changing contexts may report progress even when work remains. Therefore, check the summary against the actual status every time, especially before delivering the work.
The Real Costs That Do Not Appear in the Installation Command
The hidden cost of this skill is the time spent adjusting the prompt to suit the behavior of each agent. If the rules are unclear, the agent may summarize too aggressively and omit important logs or errors, forcing users to reread the conversation and correct misunderstandings themselves.
Results also depend on the workflow. Tasks with fixed steps may produce consistent summaries, but agents that work through multiple iterations or frequently changing contexts may report progress even when work remains. Therefore, check the summary against the actual status every time, especially before delivering the work.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of the I-have-ADHD skill is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, task status, and decisions requiring attention appear before the details, allowing readers to continue reviewing the work immediately.
Try using the skill with one type of task first, such as bug fixing, and measure the time spent actually reviewing the work compared with the previous workflow. Also check whether the answer still contains enough information to confirm the result and identify any pending work.
Conclusion: A Good Answer Does Not Have to Be Long, but It Must Remain Verifiable
The goal of the I-have-ADHD skill is not to force coding agents to speak as briefly as possible. It is to organize the answer so that the result, task status, and decisions requiring attention appear before the details, allowing readers to continue reviewing the work immediately.
Try using the skill with one type of task first, such as bug fixing, and measure the time spent actually reviewing the work compared with the previous workflow. Also check whether the answer still contains enough information to confirm the result and identify any pending work.