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LuisHiluyLuisHiluy/claude-code-pipeline-skills/debug-pipeline/SKILL.md

debug-pipeline

Skill0 starsChanged 7 months agoMITView on GitHub

Structured diagnostic runbook for broken AI media pipelines. Walks through symptom → root cause → fix for generator auth failures, stale worker locks, review-app crashes, MCP auth errors, rate limits, and corrupted state files. Use whenever generation jobs fail, workers stop picking up tasks, generated output looks wrong, review tools break, MCP servers error, or any multi-component failure happens in an AI media pipeline. Trigger on "debug the pipeline", "generation is broken", "worker not running", "review app down", "why is this failing", "what's wrong with the pipeline", or anytime the user reports a symptom without yet knowing the root cause.

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    1. harness/harness-skills★ 127same name
    2. bbvch-ai/aihub-core★ 16same name
    3. tstephx/book-mcp-server★ 1same name
    4. glassflow/agent-skills★ 0same name

    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 repository5 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

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    Common

    Most of the 4 edited versions we read keep these.

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    Distinctive

    This author's own choices. Worth a look.

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    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run the full check first:

    line 12

“Common” is measured: kept by at least 6 in 10 of the 4 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

Debug Pipeline — AI Media Runbook

Structured diagnostic for when the generation pipeline breaks.

Quick Diagnostic

Run the full check first:

bash "${CLAUDE_SKILL_DIR}/scripts/check-pipeline.sh" all

Or target a specific component:

bash "${CLAUDE_SKILL_DIR}/scripts/check-pipeline.sh" generator
bash "${CLAUDE_SKILL_DIR}/scripts/check-pipeline.sh" worker
bash "${CLAUDE_SKILL_DIR}/scripts/check-pipeline.sh" review-app
bash "${CLAUDE_SKILL_DIR}/scripts/check-pipeline.sh" mcp

Customize the script for your pipeline's components.

Diagnostic Flow

Symptom reported
  ↓
Run check-pipeline.sh all → identify which component is failing
  ↓
Look up symptom in reference/symptom-map.md → follow specific steps
  ↓
Output structured finding:
  - Component: [generator | worker | review-app | mcp | database]
  - Symptom: [what was observed]
  - Root cause: [what the check found]
  - Fix: [specific command or action]
  - Verified: [did the fix work — re-run check-pipeline.sh]

Common Fixes (80% of issues)

SymptomFix
Generation stuckRe-auth the generator
Worker not runningRemove stale lock: rm runs/worker.lock, restart
Review app downRestart servers from launch config
Wrong characterCheck prompt uses descriptors not names, add reference images
API rate limitBack off, reduce parallel batch size

Detailed Symptom Map

For full symptom → diagnostic → fix chains, see reference/symptom-map.md. Extend this file as you discover new failure modes.

Gotchas

  • Web-auth tokens expire. If anything generation-related fails, check auth first.
  • Worker lock files persist if the worker crashes. Always check if the PID is actually alive before assuming the worker is running.
  • Port proxies — if your backend is on port X and your proxy is on port Y, check both. A silent failure on X looks like a failure on Y.
  • Review data files are often the source of truth for metadata. If they get corrupted, restore from git.

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