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aayushostwalaayushostwal/nexus/skills/debugging/SKILL.md

debugging

Skill19 starsChanged 3 months agoMITView on GitHub

Use when something is failing, regressing, or behaving unexpectedly and the goal is root-cause analysis, narrowest fix, and verification. Covers CI/CD, tests, runtime, deployment, and tooling failures. Output should be RCA + fix + prevention, not design options.

116 other projects use a version of this.

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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.
  • truongtv22Skill

    Problem-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

  • mrgoonieSkill

    media-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.

    Also in 6 projects that use this

  • JetBrainsSkill

    ssr

    Guide for using Structural Search and Replace in IntelliJ. Use when creating or modifying SSR inspections or search patterns.

    Also in 3 projects that use this

  • mrgoonieSkill

    web-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.

    Also in 6 projects that use this

  • DevNewbie1826Skill

    remove-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

  • DevNewbie1826Skill

    programming

    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

The file

Show its rules and text

We split this skill into the rules it gives an agent

16 rules. 0 are common, 12 are distinctive, and 4 are very specific to this project.

  • 0

    Common

    Most of the 104 edited versions we read keep these.

  • 12

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If unsure: ask "Is the failure in pipeline logs, app code, or a framework?"

    line 32
  2. Distinctive:

    Before reading the sub-guide, collect:

    line 35
  3. Very specific:

    Read the appropriate sub-guide.

    line 42
  4. Very specific:

    Read common.md for shared output format and checklists.

    line 43
  5. Distinctive:

    If the error is framework-specific or tool-specific:

    line 46
  6. Very specific:

    Search: "<exact error message>" <tool-name> <version> — use exact error text

    line 47
  7. Distinctive:

    Check the official tool changelog for breaking changes in the version in use

    line 48
  8. Distinctive:

    Check GitHub Issues for the tool repo filtered by the error keyword

    line 49
  9. Distinctive:

    Run the exact verification command that confirms the fix (re-run the failing test or job)

    line 53
  10. Distinctive:

    Never guess the root cause without reading the full error message and stack trace first.

    line 72
  11. Distinctive:

    Never apply a fix without stating and running a verification step.

    line 73
  12. Distinctive:

    Never mix tracks — pick one sub-guide and follow it completely before considering another.

    line 74
  13. Distinctive:

    Never paraphrase an error message when searching — copy it verbatim.

    line 75
  14. Distinctive:

    Never mark the issue resolved before running the verification command.

    line 76
  15. Distinctive:

    Never clean up unrelated code as part of a bug fix — scope the change to the root cause only.

    line 77
  16. Very specific:

    Step 4: Search "ModuleNotFoundError: No module named 'pydantic'" github actions → find pydantic missing from requirements.txt

    line 91

“Common” is measured: kept by at least 6 in 10 of the 104 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Nexus Debugging

Route to the correct sub-guide and follow it end-to-end.


Compatibility

  • Sub-guides: skills/debugging/ci-cd.md, skills/debugging/codebase.md, skills/debugging/frameworks.md
  • Shared rules and output formats: skills/debugging/common.md

Workflow

Step 1 — Classify the Failure

Pick exactly one track:

TrackFailure originSub-guide
CI/CDGitHub Actions, Jenkins, CircleCI, or deployment pipeline logci-cd.md
CodebaseFailing test, runtime exception, or regression in application codecodebase.md
FrameworkDjango, FastAPI, Bazel, or other tooling misbehaviorframeworks.md

If unsure: ask "Is the failure in pipeline logs, app code, or a framework?"

Step 2 — Gather Error Context

Before reading the sub-guide, collect:

  1. Full error message or stack trace — copy exact text, do not paraphrase
  2. What changed recently: last commit, dependency update, config change, environment change
  3. Environment details: local vs CI, OS, Python/Node/runtime version
  4. Steps to reproduce (minimum reproducible case if possible)

Step 3 — Read Sub-Guide & Execute

Read the appropriate sub-guide. Follow its steps in order. Do not skip steps. Read common.md for shared output format and checklists.

Step 4 — Search for Tool-Specific Errors

If the error is framework-specific or tool-specific:

  1. Search: "<exact error message>" <tool-name> <version> — use exact error text
  2. Check the official tool changelog for breaking changes in the version in use
  3. Check GitHub Issues for the tool repo filtered by the error keyword

Step 5 — Apply Fix & Verify

  1. Apply the narrowest fix that addresses the root cause — do not clean up unrelated code
  2. Run the exact verification command that confirms the fix (re-run the failing test or job)
  3. State what would prevent this from recurring

Output Format

## Debug Report
**Track:** [CI/CD | Codebase | Framework]
**Root Cause:** [one sentence — specific, not "something went wrong"]
**Fix:** [exact command or minimal code diff]
**Verification:** [command to run to confirm fix]
**Prevention:** [what change stops this from recurring]

Anti-Patterns

  • Never guess the root cause without reading the full error message and stack trace first.
  • Never apply a fix without stating and running a verification step.
  • Never mix tracks — pick one sub-guide and follow it completely before considering another.
  • Never paraphrase an error message when searching — copy it verbatim.
  • Never mark the issue resolved before running the verification command.
  • Never clean up unrelated code as part of a bug fix — scope the change to the root cause only.

Examples

Input: User pastes GitHub Actions log:

ModuleNotFoundError: No module named 'pydantic'
Error: Process completed with exit code 1.

Step 1: Track = CI/CD (failure in pipeline) Step 2: Error = ModuleNotFoundError: No module named 'pydantic'; changed = recent dependency PR; env = GitHub Actions Ubuntu 22.04 Step 4: Search "ModuleNotFoundError: No module named 'pydantic'" github actions → find pydantic missing from requirements.txt

Output:

## Debug Report
Track: CI/CD
Root Cause: pydantic installed locally but not in requirements.txt — CI builds from scratch so it's absent
Fix: pip freeze | grep pydantic >> requirements.txt && git add requirements.txt && git commit -m "fix: add pydantic to requirements"
Verification: Re-run the failing GitHub Actions job — confirm it passes
Prevention: Add a CI step that runs `pip check` after install to catch missing transitive deps

Debugging Specialization

  • For CI/CD failures: always check if the failure is environment-specific — works locally but fails in CI = env delta (missing secret, different OS, version mismatch).
  • For codebase bugs: always check if a recent commit introduced the regression; use git bisect if the commit is not obvious.
  • For framework issues: always check the framework changelog for the exact version in use before assuming it's your code.
  • For flaky tests: run the test 5 times in isolation before investigating — confirm it's truly flaky vs. consistently failing.

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