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 Neeeophytee/finding-unknowns-skills --skill regression-proofgit clone --depth 1 https://github.com/Neeeophytee/finding-unknowns-skillsWrote 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/neeeophytee/finding-unknowns-skills/regression-proof)<a href="https://agentmods.dev/skills/neeeophytee/finding-unknowns-skills/regression-proof"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/regression-proof/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/neeeophytee/finding-unknowns-skills/regression-proof"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/regression-proof.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 | $0.00054 | $0.00573 |
| Opus 5.5 | $0.00022 | $0.00229 |
| Sonnet 5.5 | $0.00011 | $0.00115 |
| Haiku 4.5 | $0.00005 | $0.00057 |
Grade A, and why
regression-proof 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 — 26 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regression proof
A passing test is evidence for a fix only if it can distinguish the broken behavior from the intended behavior.
Steps
- Establish the reported failure, expected behavior, and authorized scope from the request, relevant code, and existing tests. Record the starting state, including uncommitted changes. Run the relevant baseline and reproduce the bug before editing when possible; distinguish a product failure from a broken test environment.
- Add the smallest regression test that exercises the real failing path and asserts the required outcome. Run it against the original behavior and verify that it fails for the reported reason, not an import error, missing dependency, or unrelated failure. Reuse an existing test if it already demonstrates this.
- Trace the cause and make a scoped fix when implementation is authorized. For review-only requests, assess the proposed fix without silently changing production code. Preserve the evidence from the original failure.
- Run the same regression test against the fixed behavior. If the fix existed before the test, compare with the original implementation in an isolated copy or worktree that preserves the relevant starting state. Do not reset the user's working tree. If an equivalent comparison cannot be made, report that limitation rather than claiming a verified before/after result.
- Check the neighboring behavior most likely to be affected. Where an incomplete fix could pass the reproducer, add a discriminating case. Use reference comparisons, bounded randomized checks, or performance measurements only when the failure mechanism warrants them; record seeds and conditions needed to reproduce results.
- Finish with the cause, fix or review finding, commands and observed before/after outcomes, adjacent checks, and remaining uncertainty. If the bug cannot be reproduced or expected behavior is unresolved, say what evidence is missing and avoid a speculative fix. Stop once the scoped claim is supported and relevant checks pass.
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 · 26 lines · 54 tokens per session scan A 8dd348c03d65
regression-proof is a skill published in the GitHub repository Neeeophytee/finding-unknowns-skills (356 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 573 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 2026-09-28.
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