debugging
Skill1 starsChanged 46 days agoMITView on GitHub
Use when investigating a bug, test failure, incident, performance regression, or unexpected behavior; require reproduction, evidence, a testable hypothesis, isolation, a minimal correction, and regression validation. Do not use for speculative feature work or unrelated cleanup.
119 other projects use a version of this.
Adopted by
Most recently taken up by
- lengrufeng2008/dsh-skill-librarytheir own version, first seen Nov 15, 2026
- jameswyse/skillstheir own version, first seen Nov 15, 2026
- sayurionishi/playwright-scaffoldtheir own version, first seen Nov 15, 2026
- Tariux/AI-Skills-Not-Awesometheir own version, first seen Nov 15, 2026
- iliaal/ai-skillstheir own version, first seen Nov 14, 2026
- JetBrains/intellij-communitytheir own version, first seen Nov 13, 2026
Used with
Projects with it also use Problem-Solving Techniques, media-processing 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.
truongtv22SkillProblem-Solving Techniques
Apply systematic problem-solving techniques for complexity spirals (simplification cascades), innovation blocks (collision-zone thinking), recurring patterns (meta-pattern recognition), assumption constraints (inversion exercise), scale uncertainty (scale game), and dispatch when stuck. Techniques derived from Microsoft Amplifier project patterns adapted for immediate application.
Also in 4 projects that use this
mrgoonieSkillmedia-processing
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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JetBrainsSkillssr
Guide for using Structural Search and Replace in IntelliJ. Use when creating or modifying SSR inspections or search patterns.
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mrgoonieSkillweb-frameworks
Build modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.
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DevNewbie1826Skillremove-ai-slops
Remove AI-generated code slop from branch changes or an explicit file list while preserving behavior, including junk tests (prose pins, source greps, copied inventories, mock echoes), each proven by its class rule before a cut. Use when asked to remove slop, clean AI code, deslop, clean up generated code, strip slop, prune junk tests, or review generated-code cleanup. Start by locking behavior with regression tests, then use the category and workflow references.
Also in 3 projects that use this
DevNewbie1826Skillprogramming
MUST USE for work on Python, Rust, TypeScript, JavaScript, or Go source files and project manifests, and whenever a test or spec file is written, reshaped, reviewed, or deleted. Triggers: write or edit code; add, change, or delete a test; test authoring gate; junk tests; new project; Go HTTP service (gin lane); Bubble Tea TUI; CJK IME; Connect-Go RPC; sqlc or pgx; branded IDs; exhaustive matching; unsafe Rust; Miri; oversized file; refactoring; logging, log levels, structured logging, or observability; arena, allocator, bumpalo, const fn, const generics, compile-time programming, zero-allocation APIs, bitfields, repr, scope guards, errdefer-style cleanup, Zig-like patterns, zero-copy parsing, packed data, or FFI; Rust public API design or macros.
Also in 3 projects that use this
- +6 more from mrgoonie
Other versions119 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 119
- tursodatabase/turso★ 25ksame name
- JetBrains/intellij-community★ 21ksame name
- DetachHead/rebased★ 6.5ksame name
- mrgoonie/claudekit-skills★ 2.2ksame name
- JetBrains/MPS★ 1.7ksame name
- danieleteti/delphimvcframework★ 1.4ksame name
- glommer/pgmicro★ 1.2ksame name
- karrioapi/karrio★ 799same name
- rapidaai/voice-ai★ 755same name
- i-am-manware/Manware-s-AI-Learning-Toolkit★ 717same name
109 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 repository8 other files it gives its agents.
- adaptive-agent-routingSkill
- brand-aware-designSkill
- engineering-verificationSkill
- frontend-designSkill
- human-copywritingSkill
- orchestrated-deliverySkill
- security-reviewSkill
- skill-authoringSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
13 rules. 0 are common, 12 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 107 edited versions we read keep these.
12
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
- Distinctive: line 34
Use for bugs, regressions, failed tests, build/integration failures, performance or concurrency failures, incidents with a safe evidence …
- Distinctive: line 36
Do not use to invent a feature from an ambiguous request, replace a missing acceptance criterion, or justify changing unrelated code.
- Distinctive: line 50
If the request is diagnosis-only, stop there.
- Distinctive: line 54
Only after diagnosis justifies a correction:
- Distinctive: line 58
avoid unrelated cleanup, upgrades, or production changes.
- Distinctive: line 73
If the issue cannot be reproduced, remain in diagnosis.
- Distinctive: line 79
Never print or persist secrets, tokens, cookies, private keys, credentials, or unnecessary personal data.
- Distinctive: line 83
Use a falsifiable form:
- Distinctive: line 87
Prefer one variable per experiment.
- Distinctive: line 93
Do not disable authorization, validation, tenant checks, TLS, rate limits, or error handling to make reproduction easier.
- Distinctive: line 99
If the hypothesis was not confirmed, do not keep a patch merely because it appears to help.
- Distinctive: line 103
Add or update a focused regression check.
- Very specific: line 105
If required validation cannot run because of an unavailable environment, credential, service, or dependency, report NOT_RUN or …
“Common” is measured: kept by at least 6 in 10 of the 107 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
Debugging
Turn an observable failure into an evidence-backed root-cause finding and, only after that, a narrowly scoped correction.
Operational contract
Objective
Convert an observed failure into a defensible root-cause conclusion before changing behavior. When implementation is authorized and justified, apply the smallest correction tied to that cause and prove the original symptom is covered by regression evidence.
Expected inputs
The workflow expects the symptom, expected behavior, actual behavior, affected scope, environment or version context, a safe reproduction path when available, relevant sanitized evidence, repository/worktree state, and whether the request is diagnosis-only or includes implementation.
Required outputs
Return reproduction status, labeled FACT/INFERENCE/HYPOTHESIS/UNKNOWN evidence, the falsifiable hypothesis and experiment, the isolated failing boundary, root cause with limits, any changed files when implementation is in scope, and regression/static validation results with honest external blockers.
Definition of done
Diagnosis is done when the root-cause conclusion is supported by evidence or the remaining uncertainty is explicitly bounded. A fix is done only when it is tied to the confirmed cause, the original reproduction is re-run, focused regression evidence covers the symptom, and required unavailable checks remain NOT_RUN or BLOCKED_EXTERNAL rather than being inferred as PASS.
Non-negotiable invariant
Do not implement a correction before investigating the root cause, and do not present diagnosis as implementation.
When to use
Use for bugs, regressions, failed tests, build/integration failures, performance or concurrency failures, incidents with a safe evidence source, and requests to explain a failure before deciding whether code should change.
Do not use to invent a feature from an ambiguous request, replace a missing acceptance criterion, or justify changing unrelated code.
Required separation
Diagnosis
Establish:
- expected behavior and actual behavior;
- a reproduction, or why reproduction is unavailable;
- sanitized evidence from the relevant execution path;
- a falsifiable hypothesis and controlled test;
- the smallest confirmed root cause, with confidence and limits.
If the request is diagnosis-only, stop there.
Implementation
Only after diagnosis justifies a correction:
- change the smallest coherent surface tied to the cause;
- preserve behavior outside the affected path;
- avoid unrelated cleanup, upgrades, or production changes;
- include focused regression evidence for the original symptom.
Workflow
1. Establish the boundary
Record issue, expected result, actual result, affected scope, environment class, and the decision the investigation must support. Inspect the current worktree/diff before editing.
Label important statements as FACT, INFERENCE, HYPOTHESIS, or UNKNOWN.
2. Reproduce before correcting
Attempt the smallest safe reproduction before changing implementation. Preserve relevant input, preconditions, command/request shape, version, and timing. Compare a known-good case when possible and capture the original failure.
If the issue cannot be reproduced, remain in diagnosis. A non-reproduced issue does not justify a speculative fix.
3. Gather sanitized evidence
Collect only evidence needed to distinguish hypotheses: error text, trace shape, status, timing, state transition, focused logs/metrics, test output, diff, and boundary evidence.
Never print or persist secrets, tokens, cookies, private keys, credentials, or unnecessary personal data.
4. Test one hypothesis
Use a falsifiable form:
If cause X is responsible under condition Y, observation Z should occur; if X is not responsible, Z should not occur.
Prefer one variable per experiment. Record what the experiment proved and what it did not prove.
5. Isolate the failing boundary
Separate application logic from inputs, persistence, network calls, authentication, queues, caches, clocks, and external dependencies.
Do not disable authorization, validation, tenant checks, TLS, rate limits, or error handling to make reproduction easier. A mock can establish a local contract; it cannot prove the real dependency is healthy.
6. Apply the minimal correction
State the confirmed root cause, identify the smallest correction, make one coherent change at a time, then re-run the original reproduction.
If the hypothesis was not confirmed, do not keep a patch merely because it appears to help.
7. Prove regression behavior
Add or update a focused regression check. When practical, show that it fails against the pre-correction behavior and passes after the correction. Run the narrowest neighboring/static check needed to catch accidental breakage.
If required validation cannot run because of an unavailable environment, credential, service, or dependency, report NOT_RUN or BLOCKED_EXTERNAL rather than calling the correction proven.
External failure boundaries
Timeouts, outages, quotas, remote 5xx, unavailable authenticated sessions, and network restrictions are evidence about a boundary, not automatic proof of an application defect.
A local stub can validate local contract handling; it cannot prove remote provider health. A 401/403 can prove access was not granted; it cannot justify bypassing authentication.
Handoff
Report:
- symptom and reproduction status;
- evidence with FACT/INFERENCE/HYPOTHESIS/UNKNOWN labels;
- hypothesis, experiment, result, and confirmed root cause;
- files/boundaries changed if implementation was in scope;
- regression and static validation results;
- external limits, unexecuted checks, residual risk, and next action.
Checklist
- Expected and actual behavior are explicit.
- Existing worktree changes were inspected and preserved.
- Original symptom was reproduced or inability to reproduce is documented.
- Evidence is sanitized and separated from inference.
- A falsifiable hypothesis and controlled experiment were recorded.
- The failing boundary was isolated without weakening controls.
- The correction is minimal and tied to a confirmed cause.
- A focused regression check covers the original symptom.
- External failures and unrun checks are labeled honestly.
- Diagnosis and implementation are reported separately.
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