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 edonadei/caliper --skill evaluate-skillgit clone --depth 1 https://github.com/edonadei/caliperWrote 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/edonadei/caliper/evaluate-skill)<a href="https://agentmods.dev/skills/edonadei/caliper/evaluate-skill"><img src="https://agentmods.dev/badge/skills/edonadei/caliper/evaluate-skill/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/edonadei/caliper/evaluate-skill"><img src="https://agentmods.dev/badge/skills/edonadei/caliper/evaluate-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00070 | $0.01882 |
| Opus 5.5 | $0.00028 | $0.00753 |
| Sonnet 5.5 | $0.00014 | $0.00376 |
| Haiku 4.5 | $0.00007 | $0.00188 |
Grade A, and why
evaluate-skill 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 9d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluate Skill
Operate Caliper: run a skill's eval, read what the results say, and trace each failure to the place that fixes it.
Prerequisites
The caliper CLI must be on PATH. This skill can be copied into an agent without the Caliper repo, so install it if missing:
pipx install caliper-eval
caliper <command> --help is the authority on flags. REFERENCE.md covers the full spec format, engines, and what the results mean.
The four questions
A skill eval answers four separate questions. Each has its own measurement and its own fix location, so keep them apart: a blended number hides which half broke.
| Question | Measured by | A failure is fixed in |
|---|---|---|
| Fires: does the agent reach for the skill when it should, and only then? | activates: on tasks, and trigger probes |
the skill's description frontmatter |
| Works: once it fires, does it get the job done? | expect: / assert:, scored as the success rate |
the skill's body |
| Earns: does it beat the agent without it? | the control (--ablate <skill-name>: the declared neighbourhood minus this skill) and caliper compare. For a truly bare agent, ablate every declared skill and every declared mcp: server, and isolate the run |
the tasks: if the control passes too, the task is too easy |
| Holds: does it stay good across edits and over time? | caliper compare of each full run against the previous one, skill drift |
the edit that moved it |
Spec shape
skills:
- ./SKILL.md # relative to the spec; installed, never preloaded
tasks:
- name: What success looks like
prompt: <what a real user would type; never names the skill>
expect: <natural-language pass/fail criterion>
assert: | # optional deterministic Python check
assert ...
activates: [my-skill] # frontmatter name: of the skill that should fire
- name: Unrelated work stays unrelated
prompt: <work no declared skill should answer>
activates: [] # a trigger probe: no judge, cheap
What ships with it
2 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.
- 9d ago Changed · +2 lines 21df2e6831a5
- 20d ago Changed 66699279c281
- 23d ago Changed · +32 lines · +10 tokens per session 1f2634b5a6c0
- 24d ago Changed · +6 lines bbced1b703e2
- 1mo ago First seen · 59 lines · 60 tokens per session scan A 14911ba6094f
evaluate-skill is a skill published in the GitHub repository edonadei/caliper (214 stars, last pushed 3d ago), licensed MIT. It adds 70 tokens to every session and 1,882 once invoked, about $0.0003 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 2026-08-30.
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