add-analytics-instrumentation

---
name: add-analytics-instrumentation
description: >
license: MIT
---

# 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.