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/jnmetacode/skillet/systematic-debuggingnpx skills add jnMetaCode/skillet --skill systematic-debugginggit clone --depth 1 https://github.com/jnMetaCode/skilletWhat 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 | $0.00043 | $0.00532 |
| Opus 5 | $0.00022 | $0.00266 |
| Sonnet 5 | $0.00009 | $0.00106 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
systematic-debugging scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
line, an assertion, a debugger breakpoint, one curl. What it actually says
systematic-debugging
Never fix what you can't reproduce; never explain what you haven't observed. The loop is: reproduce → observe → hypothesize → test the hypothesis → narrow. One variable at a time.
Procedure
- Reproduce first. Find the smallest, fastest command that shows the
failure deterministically. If it's flaky, make the loop tight
(
while ./repro; do :; done) and treat flakiness itself as a clue (timing, ordering, shared state). - Read the actual error. The full message, the first stack frame in your own code, and the line right before things went wrong. Resist pattern-matching to a familiar failure — verify this one.
- State a falsifiable hypothesis ("the cache returns stale entries after a restart") and pick the cheapest observation that could kill it: a log line, an assertion, a debugger breakpoint, one curl.
- Bisect the space, whichever axis is cheapest:
- history:
git bisect run ./repro - data: half the failing input, recurse
- stack: confirm the bad value at the boundary between two layers, then descend into the guilty one only
- history:
- The fix must explain the symptom. Before writing it, say why this cause produces exactly this behavior. If the explanation is fuzzy, you've found a bug, maybe not the bug.
- Prove it: the repro from step 1 now passes, AND a new regression test
fails without the fix. Then look for siblings — the same mistake usually
exists elsewhere (
grepfor the pattern you just fixed).
Anti-patterns
- Changing two things between observations — you learn nothing from the result.
- "It works now" without knowing why it failed — it will be back.
- Adding sleeps to fix timing issues — that's hiding the race, not fixing it.
- Debugging through the framework before confirming your own code's inputs and outputs at the boundary.
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 · 46 lines · 43 tokens per session scan A 8d9f567283a4
systematic-debugging is a skill published in the GitHub repository jnMetaCode/skillet (1 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 532 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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