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/tmj-90/gaffer/fix-flaky-testnpx skills add tmj-90/gaffer --skill fix-flaky-testgit clone --depth 1 https://github.com/tmj-90/gafferWrote 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/tmj-90/gaffer/fix-flaky-test)<a href="https://agentmods.dev/skills/tmj-90/gaffer/fix-flaky-test"><img src="https://agentmods.dev/badge/skills/tmj-90/gaffer/fix-flaky-test.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.00498 |
| Opus 5 | $0.00034 | $0.00249 |
| Sonnet 5 | $0.00014 | $0.00100 |
| Haiku 4.5 | $0.00007 | $0.00050 |
Grade A, and why
fix-flaky-test 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 4d 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.
What it actually says
Fix a flaky test
A flaky test fails non-deterministically. The job is to find the source of non-determinism and remove it — not to retry until it passes.
Steps
- Reproduce the flakiness. Run the named test repeatedly (a loop, or the runner's repeat flag) and, where relevant, in randomised order. Capture a failing run; you can't fix what you can't observe.
- Locate the non-determinism. It's almost always one of: timing (sleeps, races, unawaited async), test order / shared mutable state (leaked globals, DB rows, singletons), unseeded randomness, real clock/timezone, or network/external calls. Read the failure to narrow which.
- Fix the root cause. Await async properly and wait on conditions not timeouts; isolate state with proper setup/teardown; seed randomness and fake the clock; stub the external boundary. Do not add a retry, increase a sleep, or mark the test skipped — those hide the bug.
- Prove stability. Re-run the test many times (and in random order) and confirm it
passes every time. Then run the full suite (
run-tests) to confirm no regression. - Evidence: the repeated-run command and a clean streak, plus the fix summary. Then
use the
record-evidenceskill to recordtest_outputagainst the AC and submit for review.
Rules
- Fix the cause (timing/order/shared state/randomness), never add a retry or longer sleep.
- Never skip or delete the test to make the suite green.
- Demonstrate stability with many repeated passes, not a single run.
- If the flake reveals a real product bug, note it; fix only what the ticket scopes.
- Run on a branch (the
create-branchskill), never a protected branch.
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.
- 4d ago First seen · 38 lines · 69 tokens per session scan A 232d854c28a4
fix-flaky-test is a skill published in the GitHub repository tmj-90/gaffer (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 69 tokens to every session and 498 once invoked, about $0.0003 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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