Name: add-analytics-instrumentation
Author: amplitude

End-to-end analytics instrumentation workflow for a PR, branch, file, directory, or feature. Reads the code, discovers what events should be tracked, and produces a concrete instrumentation plan — all in one shot. Use this skill whenever a user wants to add analytics to a PR, asks "instrument this P

add analytics instrumentation You are the orchestrator for the analytics instrumentation pipeline. Your job is to figure out what the user wants to instrument, gather the relevant code, and run the pipeline to produce a tracking plan. Pipeline Step 0: Capture intent Before running anything, determine what the user wants to instrument. There are four input types — infer the type from what the user has already provided in the conversation. Only ask if it's genuinely ambiguous. Input type How to recognize it Example PR A PR URL, PR number, or phrases like "this PR", "my PR" instrument PR 42 , https://github.com/org/repo/pull/42 Branch A branch name or "this branch", "my branch", "current branch" instrument feature/checkout , add tracking to this branch File / Directory A file path, directory path, or glob pattern instrument src/components/Checkout.tsx , add analytics to src/payments/ Feature A natural language description of functionality, not a specific code reference instrument the onboarding flow , add tracking to the checkout experience Inference rules: If the user provided a URL or number → PR If the user provided something that looks like a branch name (contains / , no file extension, matches a git branch) → Branch If the user provided a path that exists on disk (file or directory) → File / Directory If none of the above match and the input is descriptive → Feature If the conversation already contains a PR link, branch name, or file path from earlier messages, use that instead of asking again If ambiguous , ask the user: What would you like to instrument? 1. A specific file or directory 2. A PR 3. A branch 4. A feature (describe it and I'll find the relevant code) Once you know the input type, proceed to the appropriate step: PR or Branch → go to Step 1 (diff intake) File / Directory → go to Step 1a (direct file read) Feature → go to Step 1b (feature search) Step 1: diff intake skill (PR or Branch) Invoke the diff intake skill with the user's PR or branch reference. It produces a change brief YAML block. Capture the full YAML output — step 2 consumes it verbatim. Skip to Step 2. Step 1a: Direct file read (File / Directory) Skip diff intake entirely — there's no diff to analyze. Instead, build the change brief YAML yourself by reading the files directly. 1. Resolve the input. If a directory, find all source files in it (skip tests, config, lock files, generated code). If a single file, just use that. 2. Read each file and summarize what it does — focus on user facing behavior, not implementation details. 3. Scan for existing instrumentation using the same patterns as diff intake: track( , trackEvent( , logEvent( , amplitude.track( , ampli. , and analytics related imports. 4. Build the change brief YAML with analytics scope: high (the user explicitly asked to instrument these files, so assume they want tracking). Set primary: feat and classification.types: [feat] . Populate file summary map with each file's summary, layer, and existing instrumentation. Proceed to Step 2 with the YAML you built. Step 1b: Feature search (Feature) The user described a feature in natural language. Your job is to find the relevant code, then build a change brief . 1. Search git commit history to find related commits. Use git log all grep="<patterns " . This will find relevant commits. Then read the git commit body to understand the feature and relevant files. If the results are good, then proceed to generating the change brief YAML 2. Search the codebase for files related to the described feature. Use a combination of: Grep for keywords from the feature description (component names, route paths, function names, domain terms) Glob for likely file paths (e.g., /checkout/ , /onboarding/ ) Read route definitions, navigation configs, or index files to find entry points 3. Build the change brief YAML. Proceed to Step 2 with the YAML you built. Step 2: discover event surfaces Invoke the discover event surfaces skill, passing the change brief YAML from step 1. It produces an event candidates YAML block. If there are zero candidates, stop and tell the user the change has user facing impact but no events worth instrumenting were identified. If event candidates is empty, stop here and tell the user there's nothing to instrument. Capture the full YAML output — step 3 consumes it. Step 3: instrument events Invoke the instrument events skill, passing the event candidates YAML from step 2. It produces a trackingPlan JSON with exact file locations, tracking code, and property definitions for every critical (priority 3) event. Presenting the result After step 3 completes, present the tracking plan to the user. Walk through each event briefly: What it tracks and why it matters Which Amplitude project(s) it routes to ( appId / appIds ) — call this out when the repo has an .amplitude/instrumentation agent.yaml and events span more than one project Where the tracking call goes (file + function) What properties it sends Then ask if they want to adjust anything or proceed to implementation. Error handling If any step fails (e.g., the PR doesn't exist, git commands error, no files to analyze), surface the error clearly and stop. Don't try to continue with incomplete data.