quick-stats
Skill36 starsChanged 14 days agoMITView on GitHub
Lightning-fast answers to simple numeric questions — "how many users yesterday", "what's the conversion rate", "how many sessions today". Use when the question is a single number, no analysis needed. Skips the full general-analysis workflow.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- marketcalls/vectorbt-backtesting-skillstheir own version, first seen Jul 12, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- marketcalls/vectorbt-backtesting-skills★ 200same 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 repository45 other files it gives its agents.
- a11y-analyzerSkill
- annotation-opsSkill
- anomaly-detectorSkill
- api-monitorSkill
- benchmark-analyzerSkill
- campaign-trackerSkill
- changelog-detectiveSkill
- cohort-compassSkill
- comparisonsSkill
- customer-360Skill
- dashboard-builderSkill
- deploy-radarSkill
- error-forensicsSkill
- experiment-analyzerSkill
- feature-adoptionSkill
- form-analyzerSkill
- frustration-hunterSkill
- funnel-doctorSkill
- general-analysisSkill
- heatmap-generatorSkill
- incident-responderSkill
- jira-bug-reporterSkill
- journey-builderSkill
- lifecycle-analyzerSkill
- metric-auditorSkill
- mobile-analyzerSkill
- nps-proxySkill
- onboarding-tutorSkill
- page-performanceSkill
- persona-builderSkill
- predictive-alertsSkill
- privacy-auditorSkill
- query-translatorSkill
- report-deckSkill
- retention-analyzerSkill
- revenue-impactSkill
- scroll-depth-analyzerSkill
- segment-wizardSkill
- session-playlistSkill
- session-reviewSkill
- session-searchSkill
- slack-reporterSkill
- user-journeySkill
- webhook-healthSkill
- weekly-digestSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 31
Add minimal context: "That's +3% vs the daily average last week" — but only if you already have the comparison data.
- Distinctive: line 35
Don't use this skill if the question is:
- Distinctive: line 48
If the metric already exists from a previous call in the conversation, reuse it.
- Very specific: line 49
If the question needs validation (result is zero, looks wrong), don't use Quick Stats — upgrade to general-analysis which handles …
≈ “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
Quick Stats
One-number answers. No analysis, no session investigation, no validation dance. Just the number, with context.
When to Use
- "How many users yesterday?"
- "What's the conversion rate this week?"
- "How many sessions today?"
- "How many rage clicks last month?"
- "What's our error count for this week?"
Short questions that expect a single numeric answer.
Workflow
Everything is one step: build, compute, present.
fullstory:build_metric(query="page views yesterday", output_type="single_number")
fullstory:compute_metric(metric_id)Present: "12,340 page views yesterday (Aug 3)."
Add minimal context: "That's +3% vs the daily average last week" — but only if you already have the comparison data. Don't make extra calls to get it.
When NOT to Use
Don't use this skill if the question is:
- A comparison ("mobile vs desktop") →
comparisons - A trend ("is it getting worse?") →
general-analysis(trend metric) - A breakdown ("by page" or "by device") →
general-analysis(top_n metric) - A "why" question → any of the deep-dive skills
Quick Stats is for "what's the number" — nothing more.
Guidelines
- One metric, one compute call, one answer. No extra API calls.
- Include the time period in the answer: "12,340 page views yesterday" not "12,340 page views."
- Surface the
metric_urlso the user can verify. - If the metric already exists from a previous call in the conversation, reuse it. Don't rebuild.
- If the question needs validation (result is zero, looks wrong), don't use Quick Stats — upgrade to
general-analysiswhich handles validation.
Does it work?
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

