Borrowing it
Nothing to install: this file belongs to ForgeyClap/claude-forge. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ForgeyClap/claude-forge/main/.claude/skills/forge-skill-testing/SKILL.mdgit clone --depth 1 https://github.com/ForgeyClap/claude-forgeWrote 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/forgeyclap/claude-forge/forge-skill-testing)<a href="https://agentmods.dev/skills/forgeyclap/claude-forge/forge-skill-testing"><img src="https://agentmods.dev/badge/skills/forgeyclap/claude-forge/forge-skill-testing.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 | $0.00047 | $0.01397 |
| Opus 5 | $0.00023 | $0.00698 |
| Sonnet 5 | $0.00009 | $0.00279 |
| Haiku 4.5 | $0.00005 | $0.00140 |
Grade A, and why
forge-skill-testing 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
forge-skill-testing — activation + A/B test protocol
Self-improvement substrate (wp-skill-evals, 2026-07-31): before applying this skill, read
learnings.md in this skill's own folder and honor its corrections. After a run that produced a
genuine correction, append it to learnings.md with a date and real evidence — never invent a lesson
that didn't happen.
Origin (wp-disclosure-ab, backlog item 8, YT-SWEEP-2026-07-31, 4 source videos: 7s9Fnorg3eI, O_z9vDLgvoY, UtGszoiwrsQ, wQ0duoTeAAU): complementary to the description-length budget work (wp3b) — a short, well-formed description is step 1 (discovery), but nobody was measuring whether a skill actually activates on real phrasing, or whether it genuinely helps once it does. Community data cited in the sweep: activation drops to ~20% with vague descriptions, and this is essentially never measured in practice.
This is the CHECKLIST/PROTOCOL, not an automated runner. No script executes these steps — they are
a human/agent-in-the-loop procedure, the same way forge-code-review's severity scale is a method, not
a linter. Step 2 after forge-skill-evals.cjs's binary evals (see that tool's own header comment for the
"step 1 -> step 2" pointer).
When to use
- A skill's
SKILL.mdfrontmatterdescriptionwas just written or rewritten. - A skill's body changed enough that its trigger conditions may have shifted.
- Skill Boss or Head Chef wants real evidence a skill is actually discoverable/useful, not just present.
- NOT required for every trivial doc tweak (a typo fix, a one-line clarification) — use judgment; this protocol costs real runs (see part 2) and is opt-in per skill change, never a merge/ship gate.
Part 1 — Activation test (cheap, do this for every meaningfully-changed skill)
- Write 6+ trigger phrases — realistic things an owner/agent would actually type that SHOULD cause this skill to be selected/loaded. Use the skill's own "When to use" bullets and description as the source, but phrase them the way a real request sounds, not a copy of the description.
- Write 4+ near-miss phrases — realistic requests that sound adjacent but should NOT activate this specific skill (they belong to a sibling skill, or a different domain entirely). A near-miss that accidentally activates the skill is a real precision problem, not a pass.
- Run each phrase in a fresh session (or ask "would this skill fire on X?" against the current frontmatter honestly) and record activation Y/N per phrase.
- Target: >= 95% correct (trigger phrases activate AND near-miss phrases don't, combined). Below that, the description likely needs sharper "when to use" language — rewrite and re-test, don't just accept a low score.
- Log the result in
.claude/FORGE_SKILL_REGISTRY.md— that table has no dedicated activation-test column (see its own legend), so append a compact, dated note to the skill's existing Safety notes cell in the exact shapeactivation <correct>/<total> (<YYYY-MM-DD>)(see the template below for a worked example). Never touch any other skill's row while doing this.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 85 lines · 0 tokens per session scan A 624076b1ebe2
forge-skill-testing is a skill published in the GitHub repository ForgeyClap/claude-forge (2 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 1,397 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 2026-09-03.
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