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 Snowflake-Labs/cocoplus --skill meter-benchmarkgit clone --depth 1 https://github.com/Snowflake-Labs/cocoplusWrote 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/snowflake-labs/cocoplus/meter-benchmark)<a href="https://agentmods.dev/skills/snowflake-labs/cocoplus/meter-benchmark"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/meter-benchmark/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/snowflake-labs/cocoplus/meter-benchmark"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/meter-benchmark.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 | $0.00027 | $0.00288 |
| Opus 5.5 | $0.00011 | $0.00115 |
| Sonnet 5.5 | $0.00005 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
meter-benchmark 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.
What it actually says
Your objective is to establish a measured p-hat baseline before optimizing a flow template, wisdom rule, or skill.
Command
$meter benchmark --flow <template>
Run or read the requested template's benchmark history, then report:
- number of runs,
- per-stage success probability,
- confidence interval,
- average token cost,
- average elapsed time,
- failure classes observed.
Write results to .cocoplus/meter/template-benchmarks.jsonl.
Exit Criteria
- No optimization is recommended without a measured baseline.
- Stage-level p-hat is reported separately from whole-flow success.
- Benchmark results include cost and confidence, not only pass/fail count.
Anti-Rationalization
| Shortcut / Temptation | Why It Fails |
|---|---|
| Treat the skill as complete because the file exists | Skill contracts must describe observable behavior and verification, not just command names. |
| Skip artifact and safety checks for a small command | Small commands still mutate state or guide execution; preserve the same gates. |
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 · 41 lines · 27 tokens per session scan A ccf21fe5bfcb
meter-benchmark is a skill published in the GitHub repository Snowflake-Labs/cocoplus (727 stars, last pushed 25d ago), licensed MIT. It adds 27 tokens to every session and 288 once invoked, about $0.0001 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 2026-09-03.
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