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.
npx skills add Vimalk0703/shipworthy --skill systematic-debugginggit clone --depth 1 https://github.com/Vimalk0703/shipworthyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vimalk0703/shipworthy/systematic-debugging)<a href="https://agentmods.dev/skills/vimalk0703/shipworthy/systematic-debugging"><img src="https://agentmods.dev/badge/skills/vimalk0703/shipworthy/systematic-debugging/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vimalk0703/shipworthy/systematic-debugging"><img src="https://agentmods.dev/badge/skills/vimalk0703/shipworthy/systematic-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.00673 |
| Opus 5.5 | $0.00016 | $0.00269 |
| Sonnet 5.5 | $0.00008 | $0.00135 |
| Haiku 4.5 | $0.00004 | $0.00067 |
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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
The Anti-Pattern This Prevents
Trial-and-error debugging: change something, see if it works, repeat. This approach takes 2-3 hours and has a 50% first-time fix rate. Systematic debugging takes 15-30 minutes with a 95% first-time fix rate.
The 4 Phases
Phase 1: Observe
Gather evidence before forming theories.
- What exactly is the symptom? (error message, wrong output, crash)
- When does it happen? (always, sometimes, only in production)
- What changed recently? (git log, recent deploys, config changes)
- Can you reproduce it reliably?
- Read the FULL error message and stack trace
Phase 2: Hypothesize
Form testable theories based on evidence.
- What could cause this symptom?
- List 2-3 hypotheses, ranked by likelihood
- Each hypothesis must be testable — "something is wrong" is not a hypothesis
- Consider: is this a code bug, a data bug, a config bug, or an environment bug?
Phase 3: Test
Test each hypothesis methodically.
- Start with the most likely hypothesis
- Design a test that would CONFIRM or ELIMINATE the hypothesis
- Run the test. Read the results carefully.
- If confirmed: proceed to Phase 4
- If eliminated: move to the next hypothesis
Phase 4: Implement
Fix the root cause, not the symptom.
- Write a test that reproduces the bug FIRST (TDD applies to bugs too)
- Implement the fix
- Run the reproducing test — it should pass now
- Run the full test suite — nothing else should break
- Verify the fix in the original context where the bug was observed
The 3-Fix Rule
If 3 attempted fixes don't resolve the issue, STOP.
You're likely:
- Fixing a symptom, not the root cause
- Working with wrong assumptions
- Dealing with an architectural issue that requires a different approach
When you hit the 3-fix limit:
- Step back and re-examine your assumptions
- Re-read the error messages and logs from scratch
- Consider whether the bug is in a different layer than you're looking at
- Discuss with the user before proceeding
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.
- 1mo ago First seen · 68 lines · 39 tokens per session scan A ce0c7ca32fcf
systematic-debugging is a skill published in the GitHub repository Vimalk0703/shipworthy (6 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 673 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
dare-bugfix-design
Analisa um projeto existente e gera um Implementation Plan focado apenas na correcao de um bug complexo. Use quando precisar diagnosticar e corrigir um erro no sistema atual. Cria um documento DESIGN-Bugfix-[Nome].md.
dare-reverse
Camada semântica da engenharia reversa (Fase 0 / brownfield). Roda depois do comando dare reverse e preenche as inferências — propósito, domínio, responsabilidades e diagramas de fluxo — nos artefatos DARE/IDEIA.md e DARE/REVERSE/module-.md.
bug-triage
Re-evaluate open bugs — priority vs severity, assign to sprints, surface systemic trends. Run when the count grows.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524): sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
sandbox-unblock
Diagnostic protocol to run before reporting a sandbox blocker or asking for a configuration change. Eleven checks that eliminate false positives, then a report template the person holding the settings can act on. On one measured day, six of eight reported blockers turned out to be false, all from the same handful of…
monitoring-observability
OpenTelemetry, structured logging, distributed tracing, alerting, and dashboards. Use when instrumenting services, designing logs/traces/metrics, defining SLOs and alerts, or debugging production behavior from telemetry.