measurement
Skill1 starsChanged 3 months agoMITView on GitHub
Check whether the shipped change actually moved its success metric, and feed the answer back as evidence. Use after a release has real usage, when deciding whether to iterate or move on, when someone declares a feature a success without numbers, or when the roadmap ignores what the last three ships taught.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- PostPlusAI/postplus-skillstheir own version, first seen Nov 5, 2026
Other versions1 project uses a version of this.
Word for word · 0
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Edited · 0
None found.
Wrote their own version · 1
- PostPlusAI/postplus-skills★ 27same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository14 other files it gives its agents.
- accessibilitySkill
- colorSkill
- content-designSkill
- design-reviewSkill
- design-systemSkill
- implementation-reviewSkill
- interaction-designSkill
- layoutSkill
- motionSkill
- product-evidenceSkill
- product-framingSkill
- typographySkill
- validationSkill
- visual-directionSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
No baseline, no verdict: If the baseline wasn't captured before ship, the first job is instrumenting one now and the honest report is …
- Distinctive: line 22
Moved the wrong way: check the guardrail metrics you should have paired with the success metric (support tickets, task time, error rate, …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Measurement
Shipping is not the outcome; the behavior change is. This skill closes the loop: it takes the success metric written in the frame, compares against the baseline, and turns the answer into evidence for the next cycle. Without it the team is a factory that never learns whether its products work.
The contract was written in the frame
The frame declared a target behavior, a success metric, and a baseline. Measurement holds the work to that contract:
- No baseline, no verdict. If the baseline wasn't captured before ship, the first job is instrumenting one now and the honest report is "unmeasurable this cycle".
- Measure the frame's metric, not a flattering neighbor. "Engagement is up" doesn't answer "did trial users reach their first deploy faster?"
- Wait for the novelty decay. Week-one numbers measure curiosity. Compare stable windows: same weekdays, enough volume, seasonality acknowledged.
Reading the result
- Moved as predicted: the frame's assumption graduates to fact in the evidence ledger, with the numbers as source.
- Didn't move: the feature works and the hypothesis was wrong. That's information, not failure; the assumption it kills goes back in the ledger marked falsified. The expensive error is quietly keeping the belief.
- Moved the wrong way: check the guardrail metrics you should have paired with the success metric (support tickets, task time, error rate, churn on the adjacent flow). Every success metric needs at least one guardrail, or you'll optimize it at the product's expense.
- Can't tell: volume too low or instrumentation missing. Say so. A shrug with numbers attached beats a story without them.
Segment before concluding: an average that's flat is often one audience up and another down, and the frame named which audience mattered.
Qualitative closes the why
Numbers say what changed; they never say why. Pair the metric read with the cheap qualitative sources: support tickets mentioning the feature, session recordings of the changed flow, the in-product search terms. Route what you learn to the owning skill: wrong words to content-design, wrong flow to interaction-design, wrong bet to the next frame.
The loop
The report is one page: metric, baseline, result, verdict, what enters the evidence ledger, and the single next decision (iterate, expand, revert, or leave it alone). File the ledger entries; the next product-evidence pass starts from them. That's the difference between a design team and a design factory: the factory ships; the team finds out.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
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