trace
Skill1 starsChanged 2 months agoMITView on GitHub
Reconstruct how a behavior actually flows through a codebase or technical system across calls, events, data transformations, state transitions, async boundaries, and resource lifecycles. Use when a bug, feature, review, or architecture question depends on the exact path rather than broad project structure.
27 other projects use a version of this.
Adopted by
Most recently taken up by
- thoughtbot/rails-consultanttheir own version, first seen Nov 8, 2026
- Yeachan-Heo/oh-my-claudecodetheir own version, first seen Nov 8, 2026
- myths-labs/musetheir own version, first seen Nov 6, 2026
- pahlevikun/levistacktheir own version, first seen Nov 1, 2026
- lza6/claw-code-tingfengtheir own version, first seen Nov 1, 2026
- RoleModel/skillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use ai-slop-cleaner, ralplan and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
Jurel89Skillai-slop-cleaner
Clean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only mode
Also in 4 projects that use this
ibahgatSkillralplan
Create a strict, quality-first execution plan with explicit gates and rollback-ready sequencing.
Also in 4 projects that use this
woosikkimSkilldeepinit
Generate hierarchical AGENTS.md codebase maps for agent context
Also in 3 projects that use this
klauswgSkilldeep-interview
在明确批准执行之前,通过数学化歧义门控进行苏格拉底式深度访谈
Also in 4 projects that use this
AWSSkillmap
Map verified service capabilities against customer-provided control framework and threat model. Produces mapping-results.json, controls-catalog.md, and framework-mapping.md. Supports pluggable frameworks: CCMv4, NIST 800-53, CIS Benchmarks, ISO 27001, etc. Split into 4 focused sub-skills for better accuracy; this skill orchestrates them.
Also in 4 projects that use this
buddyhSkilldeep-dive
Deep dive on any topic. Decomposes into subtopics, researches each in parallel with thorough source gathering, then synthesizes into a comprehensive report (4,000-10,000+ words, 40-100+ sources). Scales depth dynamically based on topic complexity. Use when asked for a deep dive, deep research, comprehensive analysis, or thorough investigation of a topic.
Also in 3 projects that use this
Other versions27 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 27
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- zereight/gitlab-mcp★ 2.1ksame name
- ai-analyst-lab/ai-analyst★ 304same name
- Soul-Brews-Studio/arra-oracle-skills-cli★ 121same name
- unlearndev/skills★ 101same name
- petrowsky/agentic-fm★ 96same name
- simota/agent-skills★ 96same name
- mbwsims/claude-universe★ 71same name
- myths-labs/muse★ 38same name
17 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- develop-featureSkill
- diagnoseSkill
- fix-bugSkill
- grillSkill
- plan-changeSkill
- praxflow-embeddedSkill
- review-changeSkill
- surveySkill
- understand-projectSkill
The file
We split this skill into the rules it gives an agent
11 rules. 0 are common, 10 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 23 edited versions we read keep these.
10
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 25
If the question is still “where should I look?”, use survey first when available.
- Distinctive: line 56
Do not infer a hop merely because two modules have suggestive names.
- Distinctive: line 87
Follow branches that can change the target behavior.
- Distinctive: line 89
When multiple possible paths exist, state the condition that selects each path.
- Distinctive: line 93
Before presenting a trace as established:
- Distinctive: line 95
search for alternate entry points.
- Distinctive: line 96
check guards/early returns.
- Distinctive: line 97
verify async callbacks or subscriptions are actually registered.
- Distinctive: line 103
Prefer an explicit path plus supporting notes:
- Distinctive: line 123
Stop when the trace explains the behavior needed by the current task with no unresolved branch likely to change the next decision.
- Distinctive: line 125
Do not turn a focused trace into a full architecture survey.
“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Trace
Trace one behavior end to end. Optimize for a trustworthy path, not maximum coverage.
Choose the trace question
Name the specific thing being traced, for example:
- a request from entry to response;
- a UI action to backend effect;
- data from input/IRQ/message to consumer;
- a state transition and who causes it;
- creation → ownership → use → release of a resource;
- an error from origin to user-visible handling.
If the question is still “where should I look?”, use survey first when available.
Method
1. Find an observable entry and outcome
Anchor the trace at concrete points whenever possible.
Examples:
HTTP request -> response
button click -> device command
IRQ -> application event
login completion -> first authenticated request
allocation -> final release2. Follow evidence, not naming conventions
At each hop, record the relevant evidence:
- caller/callee;
- event publisher/subscriber;
- queue or IPC boundary;
- state mutation;
- data transformation;
- ownership transfer;
- scheduling/thread/interrupt boundary;
- error translation.
Do not infer a hop merely because two modules have suggestive names.
3. Preserve important context changes
Highlight boundaries where reasoning assumptions can break:
- process/thread/ISR changes;
- sync → async transitions;
- serialization/deserialization;
- mutable shared state;
- retries/timeouts;
- caching;
- ownership or lifetime changes;
- external service/device calls.
4. Track state and data separately when necessary
A call chain alone can miss the cause of behavior.
For a complex path, maintain parallel questions:
Control: who invokes whom?
Data: what value is passed/transformed?
State: what persistent state changes?
Context: on which thread/process/device does it run?
Ownership: who may use/release the resource?5. Expand only when the path branches materially
Follow branches that can change the target behavior. Do not recursively explore unrelated callers or consumers.
When multiple possible paths exist, state the condition that selects each path.
6. Validate the reconstructed path
Before presenting a trace as established:
- search for alternate entry points;
- check guards/early returns;
- verify async callbacks or subscriptions are actually registered;
- inspect state conditions that can bypass a hop;
- note unresolved dynamic behavior that static inspection cannot establish.
Output
Prefer an explicit path plus supporting notes:
Entry
-> Component A: reason/evidence
-> async boundary
-> Component B: state change
-> Component C: resultThen add only the useful details:
- critical state transitions;
- data transformations;
- execution-context changes;
- ownership/lifecycle observations;
- unresolved branches or unknowns.
Stop condition
Stop when the trace explains the behavior needed by the current task with no unresolved branch likely to change the next decision.
Do not turn a focused trace into a full architecture survey.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

