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 Uxcel-Lab/product-skills --skill okr-metric-validitygit clone --depth 1 https://github.com/Uxcel-Lab/product-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/uxcel-lab/product-skills/okr-metric-validity)<a href="https://agentmods.dev/skills/uxcel-lab/product-skills/okr-metric-validity"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/okr-metric-validity/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/uxcel-lab/product-skills/okr-metric-validity"><img src="https://agentmods.dev/badge/skills/uxcel-lab/product-skills/okr-metric-validity.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 | $0.00108 | $0.02369 |
| Opus 5 | $0.00054 | $0.01184 |
| Sonnet 5 | $0.00022 | $0.00474 |
| Haiku 4.5 | $0.00011 | $0.00237 |
Grade A, and why
pm-okr-metric-validity-audit 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OKR & Metric Validity Audit Skill
What this skill changes vs. default behavior
By default, Claude reviews OKRs by polishing wording and nodding at structure — it rarely challenges whether a key result is falsifiable, whether a metric is vanity, whether an "objective" is just a feature launch in disguise, or whether hitting the target could actually harm the product. This audit forces four things: every finding names the violated principle, every metric is tested for decision-usefulness ("what would we do differently if this number changed?"), every optimization target is checked for gaming exposure and guardrails, and findings come severity-rated with concrete rewrites — not general encouragement.
This is an evaluative skill: it auto-runs whenever OKRs, KPIs, or success metrics are present in work being reviewed or generated.
Scope discipline. When invoked directly (the user named this audit), review only this concern — don't pull in sibling audits. It runs alongside other lenses only when the pm-product-review orchestrator or a generative skill calls it under docs/orchestration-policy.md, where it sits in an artifact-specific lens — offered (when metrics/OKRs are defined). Explicit scope always wins.
The framework — what to check and what a violation looks like
1. Outcome, not output
Outputs are things teams ship (features, releases, launches). Outcomes are changes in user behavior or business results. Key results and metrics must measure outcomes; counting shipped things is the feature-factory signature.
Flag when: a KR or metric counts deliverables, launches, tickets closed, or activities performed; an objective prescribes a solution ("Launch mobile app by Q3").
- ❌ KR: "Ship 12 features this quarter" · Objective: "Launch the referral program"
- ✅ KR: "Increase week-4 retention from 22% to 30%" · Objective: "Make our signup the simplest in the industry"
2. Falsifiability (the SMART test)
Each key result is obviously achieved or not — a number, a unit, a baseline, a target, a timeframe. If reasonable people could disagree about whether it was hit, it's a wish, not a key result.
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 · 161 lines · 108 tokens per session scan A 38801bff9ebc
pm-okr-metric-validity-audit is a skill published in the GitHub repository Uxcel-Lab/product-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 108 tokens to every session and 2,369 once invoked, about $0.0005 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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