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 reidemeister94/development-skills --skill eval-regressiongit clone --depth 1 https://github.com/reidemeister94/development-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/reidemeister94/development-skills/eval-regression)<a href="https://agentmods.dev/skills/reidemeister94/development-skills/eval-regression"><img src="https://agentmods.dev/badge/skills/reidemeister94/development-skills/eval-regression.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 5.1 | $0.00031 | $0.00538 |
| Opus 5 | $0.00015 | $0.00269 |
| Sonnet 5 | $0.00006 | $0.00108 |
| Haiku 4.5 | $0.00003 | $0.00054 |
Grade A, and why
eval-regression 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 7d 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 — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Eval regression
Use deterministic repository tests first. Stop when the target has no behavioral diff.
Resolve the plugin from the argument or cwd. Its catalog is evals/evals.json; the shared runner is ../ai-agent-bench/scripts/run_evals.py. Require the user to choose agent, model, and effort. Never select a costly model or high effort silently.
Normal check
- Select cases by changed paths with
--changed-from <base>, or name them with--case. Do not select the full catalog implicitly. - Run the command without
--run. The runner prints the cases, modes, repeat count, session count, per-session timeout, and maximum duration without starting an agent. - Present that plan and stop for explicit cost approval.
- After approval, repeat the same command with
--run. The default is candidate-only, one run per case, 180 seconds per session, and at most four sessions. - Report every failed assertion, timeout, non-zero exit, duration, and token count. Missing evidence is inconclusive.
Escalation
- Compare base and candidate only when the user asks, or when a failed candidate check needs to distinguish a regression from an existing failure. Extract the base with
git archive; run the same selected cases, agent, model, effort, repeat, and timeout on both; compare reports with--compare. - Repeat only a failed or observably unstable case. Three repeats are a stability benchmark, not a default.
--all,--repeat > 1, a larger--max-sessions, or a longer timeout needs a new run plan and explicit approval.- Routing cases stop at the first Skill selection. A tool assertion is appropriate there because routing is the contract; they must not execute the selected skill.
Remove temporary base copies after the comparison. Do not edit or commit the target.
Deterministic assertions are tool, tool_not, clean_worktree, changed_files_exact, file_contains, file_not_contains, transcript_contains, and tool_sequence. Use a semantic judge only when no filesystem, command, tool, ordering, or assistant-output observation can express the contract.
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.
- 7d ago First seen · 32 lines · 31 tokens per session scan A 7ba5eb7c74c5
eval-regression is a skill published in the GitHub repository reidemeister94/development-skills (11 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 538 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 2026-08-30.
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