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 agentmods add skills/vrennat/developersdevelopers/systematic-debuggingnpx skills add vrennat/developersDevelopers --skill systematic-debugginggit clone --depth 1 https://github.com/vrennat/developersDevelopersWhat 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 | $0.00039 | $0.00332 |
| Opus 5 | $0.00019 | $0.00166 |
| Sonnet 5 | $0.00008 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
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 yesterday.
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.
What it actually says
Systematic Debugging
Fires when execution produces a real failure: a test error, a stack trace, a non-zero exit code, or output that contradicts the expected behavior. Does NOT fire when the user mentions a bug abstractly without evidence on screen.
Procedure
- State observed vs expected in one sentence each.
- Form 1-3 hypotheses ranked by likelihood.
- Design the smallest experiment that proves or disproves the top hypothesis (a print, a one-line edit, a focused test).
- Run the experiment. Capture the output.
- Update or replace hypotheses based on the result. Repeat from step 3 until root cause is identified.
- State the root cause and the proposed fix. Hand off to
/implor direct implementation.
Example
Observed: `bun run check` reports `TS2339: Property 'roomId' does not exist on type 'GameState'.`
Expected: typecheck passes after the new prop was added.
Hypothesis 1 (likely): roomId was added to ServerState but not propagated to GameState.
Experiment: grep for `interface GameState` to see the actual definition.
Result: GameState extends ClientState, not ServerState. roomId lives on ServerState.
Root cause: prop placement on the wrong type in the layered state hierarchy.
Fix: move roomId to a shared base interface.
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.
- yesterday First seen · 33 lines · 39 tokens per session scan A c23187cc5d3b
systematic-debugging is a skill published in the GitHub repository vrennat/developersDevelopers (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 332 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 2026-08-31.
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