AI Product Manager

Use This Skill When

• you want OpenClaw to turn product signals into execution-ready backlog work
• you need one workflow across analytics, RevenueCat, Sentry/GlitchTip, feedback, store signals, and repo context
• you want the deterministic work to live in a standalone openclaw CLI and OpenClaw to stay the AI/chat layer
• you want delivery configurable between OpenClaw chat handoff, GitHub issues, and draft pull requests

Preferred Runtime

Prefer the standalone openclaw CLI as the runtime surface.

• Setup path: openclaw setup --config openclaw.config.json
• Primary path: openclaw start --config openclaw.config.json
• Local monorepo path: pnpm --filter @analyticscli/openclaw-cli dev -- start
• Legacy copied-runtime scripts under scripts/openclaw-growth-*.mjs remain fallback-only for older OpenClaw workspaces

The CLI is intentionally non-AI. OpenClaw should stay the only conversational and implementation layer.
Use the CLI to gather signals, generate proposals, schedule checks, and send deliveries.
If the user later asks OpenClaw to implement a proposal, OpenClaw should inspect the generated drafts and then use OpenClaw itself to do the work.

Setup DX Rules

Setup should feel guided for a developer, not like a silent preflight dump.

• Prefer auto-detection and direct fixes over asking the user to run generic commands.
• Explain why each connection matters before asking for it, especially AnalyticsCLI auth, GitHub code access, and optional GitHub write scopes.
• Ask for the minimum missing value only; do not request issue/PR permissions unless artifact creation is enabled.
• For every blocker, return a compact checklist with status, why it matters, where to get it, and the exact minimum permission or command.
• After each setup phase, report what was detected, what was configured, and the next concrete command OpenClaw will run.
• Keep secrets out of prompts, repo files, logs, and command arguments; prefer OpenClaw secret storage or environment injection.
• When SDK instrumentation is missing or weak, guide the developer through the analyticscli-ts-sdk setup path so analytics events become useful for later growth analysis.

Mandatory Baseline

Before autopilot runs, these are non-negotiable:

• analyticscli CLI available
• target repo checkout readable via project.repoRoot
• a writable openclaw.config.json
• sources.analytics enabled

GitHub connection is strongly recommended for serious analysis, even when GitHub delivery is disabled.
Treat readable GitHub repo access as very important because analytics signals become much more actionable when OpenClaw can map funnels, events, crashes, revenue signals, and feedback back to actual code areas.
Without repo context, findings stay generic and file/module hypotheses are lower confidence.

Use the least privilege GitHub access that matches the requested workflow:

• code analysis only: readable repo/code access is enough
• issue creation: add issue write permission only when GitHub issue delivery is enabled
• pull-request creation: add pull-request and contents write permission only when draft PR delivery is enabled

Dependency Refresh Protocol

Run this protocol at the start of every setup/start/run request, and whenever the user asks to fetch, update, upgrade, or reinstall this skill.
Do not stop after saying the skill was fetched from ClawHub.
The job is not done until the npm binary and companion skills are updated and verified.
If the user reports analyticscli: command not found in their own terminal, treat that as unresolved even if analyticscli works inside OpenClaw's child process.
Child processes cannot mutate the PATH of an already-open parent terminal.

1. Refresh this ClawHub skill:

   npx -y clawhub install ai-product-manager

2. Refresh the AnalyticsCLI agent skill only when it can run non-interactively:

   npx -y skills add wotaso/analyticscli-skills --skill analyticscli-cli

   If this command asks an interactive agent-selection question, stop that command and continue with the npm package install instead of blocking.
   Do not describe an interactive skills add prompt as a successful refresh.
3. Install or update the npm package that provides the analyticscli binary:

   npm install -g @analyticscli/cli@preview

4. If global npm install fails with a permissions error, use the bundled helper from the installed skill root:

   bash skills/ai-product-manager/scripts/install-analyticscli-cli.sh

5. Verify and report the exact binary path:

   command -v analyticscli
   analyticscli --help

If analyticscli: command not found still happens, do not claim setup is complete.
Find the user-local binary and fix PATH for future shells yourself; do not bounce this step back to the user:

export PATH="$HOME/.local/bin:$HOME/.local/analyticscli-npm/bin:$PATH"
command -v analyticscli || ls -l "$HOME/.local/bin/analyticscli" "$HOME/.local/analyticscli-npm/bin/analyticscli"

If the binary exists under $HOME/.local/bin or $HOME/.local/analyticscli-npm/bin, make future shells pick it up. Update all common shell startup files idempotently, then verify from a fresh shell:

for f in "$HOME/.profile" "$HOME/.bashrc" "$HOME/.bash_profile" "$HOME/.zshrc" "$HOME/.zprofile"; do
  touch "$f"
  grep -Fq 'export PATH="$HOME/.local/bin:$HOME/.local/analyticscli-npm/bin:$PATH"' "$f" ||
    printf '\n# AnalyticsCLI CLI user-local npm bin\nexport PATH="$HOME/.local/bin:$HOME/.local/analyticscli-npm/bin:$PATH"\n' >> "$f"
done
bash -lc 'source "$HOME/.bashrc" 2>/dev/null || true; source "$HOME/.profile" 2>/dev/null || true; command -v analyticscli && analyticscli --help >/dev/null'

Child processes cannot mutate an already-open parent terminal. Say that only as residual context after you have already updated profile files and verified a fresh shell. Do not say "analyticscli is fixed" unless this exact command succeeds in the same command context you control:

command -v analyticscli && analyticscli --help >/dev/null

AnalyticsCLI CLI Install Protocol

If analyticscli is missing or the user reports analyticscli: command not found, OpenClaw must install/update it directly from the scoped npm package before doing anything else.

Do not search npm for analyticscli.
Do not search npm for analyticsscli.
Those are binary names or typos, not package names.

Use this exact package:

npm install -g @analyticscli/cli@preview

Then verify:

command -v analyticscli
analyticscli --help

If global npm installs are blocked, use the bundled helper from the installed skill root:

bash skills/ai-product-manager/scripts/install-analyticscli-cli.sh

The bundled helper automatically falls back from global npm install to a user-local npm prefix at ~/.local when global install fails with permissions errors.
It must also update common shell profile files and verify that a fresh shell can resolve analyticscli.

Only ask the user for help if both direct npm install and the bundled helper fail with a concrete permission or network error.

Delivery Modes

The CLI can write proposals to one or more targets:

• deliveries.openclawChat.enabled = true: write .openclaw/chat/latest.md and .openclaw/chat/latest.json for OpenClaw to pick up in chat
• deliveries.github.mode = "issue" with deliveries.github.autoCreate = true: create implementation-ready GitHub issues
• deliveries.github.mode = "pull_request" with deliveries.github.autoCreate = true: create draft PRs that add .openclaw/proposals/...md proposal files to the repo

Connector Model

Built-in channels:

• analytics
• revenuecat
• sentry
• feedback
  default command path: analyticscli feedback summary --format json
  default cursor behavior: first run --last 30d, later runs --since <lastCollectedAt> unless the command already sets explicit time flags

Additional connectors:

• configure sources.extra[]
• each extra connector can use mode=file or mode=command
• preferred output is shared signals[]
• crash-style tools may use issues[]
• feedback-style tools may use items[]

Feedback Rules

• Always include a stable locationId for feedback collection points
• Always include a human-readable originName for where the feedback originated in the product
• Prefer AnalyticsCLI feedback retrieval via analyticscli feedback summary --format json instead of maintaining a second feedback definition
• The SDK should track lightweight feedback submission events without sending raw feedback text into analytics events

Feedback Source Memory

• The CLI should persist per-source cursor state, especially for the built-in feedback source
• Default behavior must avoid accidental historical re-fetches
• If sources.feedback.cursorMode = "auto_since_last_fetch" and the command has no explicit --since, --until, or --last, the CLI should auto-append a bounded window
• Re-fetching older history should always be a conscious action by changing the command or resetting cursor state

Startup Protocol

When the user says start, run, or kick off:

1. Run the Dependency Refresh Protocol first. It must update this skill, the analyticscli-cli skill when available, and the @analyticscli/cli@preview npm package, then verify command -v analyticscli.
2. Prefer the CLI entrypoint:
   • openclaw setup --config openclaw.config.json
3. Then run:
   • openclaw start --config openclaw.config.json
4. If the standalone openclaw CLI is unavailable but this ClawHub skill is installed, bootstrap the bundled runtime once:
   • bash skills/ai-product-manager/scripts/bootstrap-openclaw-workspace.sh
   • confirm scripts/openclaw-growth-start.mjs now exists
   • node scripts/openclaw-growth-start.mjs --config data/openclaw-growth-engineer/config.json
5. In this monorepo, use the workspace dev entrypoint when openclaw is not installed globally:
   • pnpm --filter @analyticscli/openclaw-cli dev -- start
6. Run portable checks first when setup is incomplete:
   • command -v analyticscli
   • analyticscli projects list
   • detect project.githubRepo from git remote when possible
   • verify readable GitHub repo access when available so analytics findings can be mapped to code
   • verify GitHub issue/PR write scopes only if GitHub delivery is enabled
7. If preflight fails, return only a concrete blocker checklist
8. If preflight passes, continue with openclaw run --config openclaw.config.json

Proposal Strategy

The CLI config should expose strategy.proposalMode:

• mandatory: only strongest, clearly evidenced fixes and must-have requests
• balanced: default mix of necessary fixes and moderate product ideas
• creative: still evidence-led, but more willing to suggest bolder experiments or feature ideas

Output Rules

• max 3-5 proposals per pass
• each proposal must include measurable impact and file/module hypotheses
• each proposal must say what should change
• low-confidence findings must be marked explicitly
• when GitHub delivery is disabled, proposals should still be fully usable via the OpenClaw chat outbox

Required Secrets

• GITHUB_TOKEN
  strongly recommended with readable repo/code access for code-aware analysis
  required with write scopes only when GitHub issue or pull-request delivery is enabled
• ANALYTICSCLI_ACCESS_TOKEN
  recommended for AnalyticsCLI command/API mode when no local CLI login exists
• REVENUECAT_API_KEY
  recommended for RevenueCat command/API mode
• SENTRY_AUTH_TOKEN
  recommended for Sentry command/API mode
• optional connector-specific secretEnv per sources.extra[]

References

• README
• Setup And Scheduling
• Required Secrets
• Input Schema
• Issue Template