discover-analytics-patterns
Skill14 starsChanged 37 days agoLicence not identifiedView on GitHub
Discovers how analytics tracking calls are actually written in this codebase — the concrete SDK calls, function signatures, and import patterns used to send events. Use this skill whenever you need to understand the existing analytics instrumentation patterns before adding new tracking, when someone asks "how do we track events here?", "show me the analytics setup", "what's the analytics pattern in this codebase?", or any time the instrument-events or discover-event-surfaces skills are about to run and you need to know the correct coding style to follow. Outputs a deduplicated list of patterns with generalized examples and the file paths where each pattern appears, plus the dominant event and property naming conventions inferred from those call sites. Always use this skill before writing any analytics instrumentation code.
In this repository74 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- add-analytics-instrumentationSkill
- agents-schemaSkill
- airbyteSkill
- airflowSkill
- analyze-account-healthSkill
- analyze-ai-topicsSkill
- analyze-chartSkill
- analyze-dashboardSkill
- analyze-experimentsSkill
- analyze-feedbackSkill
- bigquery-basicsSkill
- cloud-run-basicsSkill
- compare-user-journeysSkill
- coupler-ioSkill
- create-chartSkill
- create-dashboardSkill
- cubeSkill
- dagsterSkill
- daily-briefSkill
- data-appsSkill
- dbt-analytics-qaSkill
- dbtchartsSkill
- dbt-dagSkill
- dbt-developmentSkill
- dbt-fusionSkill
- dbt-mcp-serverSkill
- dbt-migrationSkill
- dbt-semantic-layerSkill
- dbt-to-smmlSkill
- dbt-troubleshootingSkill
- dbt-unit-testingSkill
- debug-replaySkill
- diagnose-errorsSkill
- diff-intakeSkill
- dignified-pythonSkill
- discover-event-surfacesSkill
- discover-opportunitiesSkill
- droughtySkill
- Engagement ContextSkill
- engagement-status-reportSkill
- Fathom SyncSkill
- fivetranSkill
- gcloudSkill
- google-cloud-recipe-authSkill
- google-cloud-waf-cost-optimizationSkill
- google-cloud-waf-securitySkill
- hightouchSkill
- instrument-eventsSkill
- investigate-ai-sessionSkill
- looker-dashboard-mockupSkill
- lookml-content-authoringSkill
- lookml-content-authoringSkill
- metabaseSkill
- monitor-ai-qualitySkill
- monitor-experimentsSkill
- monitor-reliabilitySkill
- omniSkill
- project-reviewSkill
- Release DirectorSkill
- The first 60 shown.
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. About 0 are common, 9 are distinctive, and 6 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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
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.

