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 daddia/claude-for-strategy --skill instrument-metricsgit clone --depth 1 https://github.com/daddia/claude-for-strategyWrote 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/daddia/claude-for-strategy/instrument-metrics)<a href="https://agentmods.dev/skills/daddia/claude-for-strategy/instrument-metrics"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/instrument-metrics/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/daddia/claude-for-strategy/instrument-metrics"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/instrument-metrics.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 | $0.00052 | $0.01049 |
| Opus 5 | $0.00026 | $0.00524 |
| Sonnet 5 | $0.00010 | $0.00210 |
| Haiku 4.5 | $0.00005 | $0.00105 |
Grade A, and why
instrument-metrics 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 11d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument Metrics
When to use
Map each KR to a measurement spec precise enough two people calculate the same number — with cross-plugin handoff to performance when installed.
What this skill does not do
- Does not duplicate
performance:metrics-glossarywhen performance plugin installed — mapping only. - Does not set targets — route to
/okr:set-targetsafter baselines known. - Does not invent data sources — flag unknowns for user input.
Preconditions
| Input | If missing |
|---|---|
| KRs to instrument | Ask user to provide |
| Practice profile (performance plugin status, check-in frequency) | Detect performance plugin; flag [PROVISIONAL] on cadence match |
Provisional mode
Ambiguous formulas: flag AMBIGUITY FLAGS — do not pick calculation method silently.
Trust spine
- Confidence bands (
structured-aggregation):- High: Every KR mapped; formula/source/owner/cadence complete or deferred to performance with explicit handoff.
- Medium: Some ambiguities flagged; cadence mismatches noted.
- Low: KRs without measurable spec — halt target-setting.
- Failure modes:
- Strategic advice vs. support: Spec is draft for data owner validation.
- Client confidentiality: Metric definitions may expose internal systems — CONFIDENTIAL header.
- Accountability gap: Owner named per metric; ambiguities flagged not hidden.
- Analytical Rigor: Completeness check — every KR has mapping or explicit gap.
- Incentive Gaming: N/A — definition focus.
- Escalation triggers: Check-in frequency faster than metric refresh — flag mismatch blocking reliable pulse.
Workflow
- Read practice profile for
performanceplugin status. - If performance installed: KR-to-metric mapping only; defer definition to
performance:metrics-glossary. - If performance not installed or metric new: full spec — formula, source, owner, refresh, caveats.
- Cadence match check — check-in frequency vs. metric refresh.
- Flag ambiguous formulas — do not pick silently.
- Completeness/source-tag check before output.
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.
- 11d ago First seen · 116 lines · 52 tokens per session scan A 5b3e0943512d
instrument-metrics is a skill published in the GitHub repository daddia/claude-for-strategy (2 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 1,049 once invoked, about $0.0003 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 2026-08-31.
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