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 agentmods add skills/ghaida/intent/measurenpx skills add ghaida/intent --skill measuregit clone --depth 1 https://github.com/ghaida/intentWhat 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 | $0.00127 | $0.04173 |
| Opus 5 | $0.00063 | $0.02086 |
| Sonnet 5 | $0.00025 | $0.00835 |
| Haiku 4.5 | $0.00013 | $0.00417 |
Grade A, and why
measure 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 2d 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 — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Measure — Define and Track Success
Overview
If you can't define success, you can't design for it. And if you measure the wrong thing, you'll optimize for the wrong outcome.
UX measurement connects design decisions to observable evidence — did the thing we built actually help? This skill defines what to measure, how to measure it, and how to make decisions from what you learn. It bridges the gap between "we shipped it" and "it worked."
But measurement is not neutral. Every metric you choose shapes what gets optimized. Measure time-on-site and you'll get infinite scroll. Measure clicks and you'll get clickbait. Measure conversion and you'll get dark patterns — unless you also measure what those metrics cost the user. This skill guards against measurement becoming manipulation, ensuring that metrics incentivize genuine value, not engineered engagement.
When to activate this skill: Defining success criteria for a new feature, designing experiments, building measurement frameworks, analyzing funnel performance, reviewing whether existing metrics are measuring the right things, or anytime "the numbers look good" but the experience feels wrong.
Skill family
Measure works alongside the full Intent skill system:
/strategize: Their hypotheses need measurable success criteria. Every strategic bet should connect to a metric that tells you whether the bet paid off./strategizedefines "we believe X";/measuredefines "we'll know X is true when Y." When metrics contradict a strategic assumption, measure loops back to reopen strategy — with guardrails (see "When measurement points back to strategy" below)./investigate: Qualitative research complements quantitative measurement. When the numbers say users drop off at step 3, investigate tells you why. When satisfaction scores drop after a redesign, investigate interviews users to understand the experience behind the number. Never make major design decisions from metrics alone./evaluate: UX assessment produces scores and findings that inform what to measure. Evaluation identifies usability issues; measurement tracks whether fixes actually resolved them./specify: Test plans and success metrics go into handoff specs. Every feature spec should include what success looks like and how to measure it, so engineering can instrument accordingly./philosopher: A cross-cutting cognitive mode for questioning your metrics before they become targets. Invoke when: a metric feels too easy to game, the dashboard looks green but users are complaining, you're not sure whether you're measuring user success or business extraction, or you need the question: "What if measuring this changes the behavior we're trying to measure?"
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.
- 2d ago First seen · 292 lines · 127 tokens per session scan A b7560a443127
measure is a skill published in the GitHub repository ghaida/intent (142 stars, last pushed 1mo ago), licensed CC0-1.0. It adds 127 tokens to every session and 4,173 once invoked, about $0.0006 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 2026-08-30.
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