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 aegntic/compound-engineering --skill systematic-debugginggit clone --depth 1 https://github.com/aegntic/compound-engineeringWrote 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/aegntic/compound-engineering/systematic-debugging)<a href="https://agentmods.dev/skills/aegntic/compound-engineering/systematic-debugging"><img src="https://agentmods.dev/badge/skills/aegntic/compound-engineering/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/aegntic/compound-engineering/systematic-debugging"><img src="https://agentmods.dev/badge/skills/aegntic/compound-engineering/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 | $0.00025 | $0.01340 |
| Opus 5.5 | $0.00010 | $0.00536 |
| Sonnet 5.5 | $0.00005 | $0.00268 |
| Haiku 4.5 | $0.00003 | $0.00134 |
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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
A structured methodology for debugging unexpected errors encountered during implementation. Prevents trial-and-error guessing by enforcing a disciplined observe-hypothesize-test-fix cycle.
Announce at start: "I'm using the systematic-debugging skill to diagnose this issue."
When to Use
- A test fails unexpectedly during implementation
- An error occurs that you did not anticipate
- A subagent has retried 2+ times without success
- Something "should work" but does not
- You are tempted to make random changes hoping something fixes it
When NOT to Use
- The error message is clear and the fix is obvious (just fix it)
- You are validating a reported bug (use the
bug-reproduction-validatoragent instead) - The failure is a known issue documented in
docs/solutions/
The 4-Phase Process
Phase 1: Observe
Gather evidence before forming any theories. Do not skip this phase.
- Reproduce the error -- Run the exact command that failed. Confirm you see the same error.
- Read the full error -- Read the COMPLETE error message, stack trace, and any surrounding output. Do not skim.
- Check the context -- What changed recently? What was the last thing that worked? What is different now?
- Gather state -- Check relevant logs, database state, environment variables, configuration files, or any other state that could be relevant.
- Note the symptoms -- Write down exactly what you observe:
- What happens (the error)
- What should happen (expected behavior)
- When it happens (always, sometimes, under specific conditions)
Output of Phase 1: A clear, factual description of the symptoms with no theories attached.
Phase 2: Hypothesize
Form structured theories about the root cause. Do not jump to fixing yet.
- List 3 possible root causes ranked by likelihood:
- Most likely: [hypothesis based on error message and context]
- Possible: [alternative explanation]
- Less likely but worth checking: [edge case or environmental cause]
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 · 141 lines · 25 tokens per session scan A ca3110e4660a
systematic-debugging is a skill published in the GitHub repository aegntic/compound-engineering (2 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 1,340 once invoked, about $0.0001 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
review-all
Multi-agent code review for diffs (project-agnostic). Covers standards, bugs, security, DRY, smells, perf, tests, API contracts, a11y/i18n. Verifies each finding to eliminate false positives. Use for /review-all, pre-PR/pre-commit review, or auditing uncommitted/staged changes.
logic-review
Find logic bugs in a single file or function via semi-formal execution tracing (Premises → Trace → Divergence → Trigger → Remedy). Trigger when a user shares code and suspects something is wrong without naming a concrete failure — phrases like "review this", "does this look right", "check this function", "audit this…
logic-fix-all
Autonomous repository-wide audit-and-fix pipeline: health → review → locate/explain → fix → diff-verify → iterate until clean. Starts with a mandatory consent prompt (token-intensive); after consent runs hands-free. Trigger when the user wants ALL logic issues found and fixed — "fix everything", "fix all logic…
logic-health
Sweep a directory, module, or full codebase for logic correctness and produce a scored health dashboard with systemic patterns. Trigger when the user requests a health view — "audit the whole codebase", "health check", "health overview", "logic health overview", "audit src/", "audit auth and payments modules", "where…
Refactor-Claim Audit リファクタ完了主張の検証
A review check for claims that a migration or refactor is complete, including claims about large reductions or unchanged behavior.
Async Correctness 非同期処理の正しさ検証
A code review check for asynchronous code, meaning work that finishes later through async/await, promises, or chained callbacks. It looks for missing waits, ignored errors, and operations that can run in the wrong order or interfere with each other.