systematic-debugging

A four-phase method for finding the root cause of unclear test failures, build errors, and runtime problems. It gathers evidence, ranks possible causes, tests those explanations, and then applies a verified fix.

In plain words
What is it for?
Use it when an error is not immediately obvious, keeps returning, or follows a dependency, schema, backend, frontend, ingestion, or test change. It includes ways to reproduce Java, Python, TypeScript, and browser-test failures.
Why use it?
It prevents random fix attempts and helps distinguish the original problem from symptoms introduced by later changes.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/open-metadata/openmetadata/systematic-debugging
Any agent
npx skills add open-metadata/OpenMetadata --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/open-metadata/OpenMetadata

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,025 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.01025
Opus 5 $0.00018 $0.00513
Sonnet 5 $0.00007 $0.00205
Haiku 4.5 $0.00004 $0.00103

Measured 2d ago against content hash a8759f5a3d97, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

systematic-debugging scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/systematic-debugging/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging for OpenMetadata

Structured 4-phase debugging process. Stops you from guessing and forces root cause identification.

When to Use

  • Test failures with unclear cause
  • Build errors after dependency or schema changes
  • Runtime exceptions in backend, frontend, or ingestion
  • Issues that persist after 2+ fix attempts

Phase 1: Gather Evidence

Do not change any code yet. Only observe and collect data.

  1. Read the full error — not just the last line. Stack traces, build logs, test output.
  2. Reproduce reliably:
    # Java
    mvn test -pl <module> -Dtest=FailingTest#failingMethod
    
    # Python
    source env/bin/activate && cd ingestion
    python -m pytest tests/unit/path/to/test.py::test_name -v
    
    # TypeScript
    cd openmetadata-ui/src/main/resources/ui
    yarn test path/to/test.spec.ts
    
    # E2E
    yarn playwright:run --grep "test name"
    
  3. Check what changed recently:
    git log --oneline -20
    git diff HEAD~5 -- <relevant-directory>
    
  4. Document findings: Write down the exact error, when it started, and what you've observed.

Phase 2: Form Hypotheses

Based on the evidence, list 2-3 possible causes ranked by likelihood:

1. [Most likely] Schema change in X broke generated model Y
   Evidence: error mentions field Z, git log shows schema modified 3 commits ago
2. [Possible] Dependency version mismatch after recent upgrade
   Evidence: ClassNotFoundException for new API
3. [Unlikely] Test environment state pollution
   Evidence: test passes in isolation but fails in suite

Do not jump to fixing yet. Verify the top hypothesis first.

Phase 3: Verify Root Cause

Test your top hypothesis with the smallest possible experiment:

  • Read the suspected code — don't guess what it does
  • Add targeted logging or use a debugger if needed
  • Check one hypothesis at a time — don't make multiple changes simultaneously

Common OpenMetadata Root Causes

Symptom Likely Cause Verification
ImportError in Python Models not regenerated after schema change make generate then retry
TypeScript compile error on generated types Schema changed, types not rebuilt yarn parse-schema then retry
Java NullPointerException in entity Missing field in Flyway migration Check bootstrap/sql/migrations/
Test passes alone, fails in suite Shared state mutation between tests Run with --forked (Java) or -x (pytest)
404 Not Found on API endpoint Missing @Path annotation or route config Check resource class registration
UI component renders blank Missing i18n key Check locale/languages/en-us.json
Connection refused in integration test Docker service not running docker compose -f docker/development/docker-compose.yml ps

Read the full file on GitHub · 103 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 103 lines · 37 tokens per session scan A a8759f5a3d97

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository open-metadata/OpenMetadata (15,032 stars, last pushed 2d ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,025 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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