Case 01630

Skill knownasnaffy/prompthound/dataset/case_01630

A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.

Install

npx -y skills add knownasnaffy/prompthound --skill case_01630

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What its author says it does

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Query Google Analytics 4 (GA4) data through the Google Analytics Data API for trends, countries, sources, pages, and conversion analysis. Use when a user wants GA/GA4 metrics inside OpenClaw, wants to set up GA4 access, or needs GA4 reports such as activeUsers, sessions, country/source breakdowns, page trends, or key event analysis. For enterprise/internal GA data, first verify which Google account actually has permission before proposing service accounts or extra cloud setup.

SKILL.md

3.6 KB, 771 tokens by cl100k_base, as published. Nobody here has run it

GA4 Data API

Use this skill to set up and query GA4 through OAuth user authorization.

Default approach

Prefer OAuth user authorization first.

Use scripts/install_ga4_openclaw.sh + scripts/ga4_query.py for the normal path.

Only suggest service accounts later, when there is a clear need for headless/server-side access.

Hard rules

Check account + permission before setup
- Ask which Google account can actually log into GA and has property/account access.
- Do not start with service-account setup by default for enterprise/internal data.
Be honest about blockers
- If the user cannot add users, say it is a permission blocker.
- If the OAuth app is still in Testing, say the account must be added to test users.
- If the user can see the property but lacks admin controls, say it is an access-level issue instead of pretending the button is hidden.

Setup flow

Step 1 — Verify access model

Ask/confirm:

Which Google account has GA access?
Can the user log into that account?
What is the GA4 Property ID?
Is Google Analytics Data API already enabled?
Is there already a Desktop OAuth client JSON?

Step 2 — Install and wire credentials

Run:

bash ~/.openclaw/workspace/skills/ga4-data-api/scripts/install_ga4_openclaw.sh <GA4_PROPERTY_ID> <PATH_TO_CLIENT_SECRET_JSON>

This installs Python deps, copies the OAuth client JSON into ~/.config/openclaw/ga4-client.json, and writes GA4_PROPERTY_ID into shell config.

Step 3 — First authorization

Run:

python3 ~/.openclaw/workspace/skills/ga4-data-api/scripts/ga4_query.py \
  --metrics activeUsers,sessions \
  --dimensions date \
  --start 7daysAgo \
  --end today \
  --pretty

The browser will open. The user must choose the same Google account that actually has GA access.

Successful authorization creates:

~/.config/openclaw/ga4-token.json

Step 4 — Query examples

Recent trend:

python3 ~/.openclaw/workspace/skills/ga4-data-api/scripts/ga4_query.py \
  --metrics activeUsers,sessions \
  --dimensions date \
  --start 7daysAgo \
  --end yesterday \
  --pretty

Country split:

python3 ~/.openclaw/workspace/skills/ga4-data-api/scripts/ga4_query.py \
  --metrics activeUsers \
  --dimensions country \
  --start 7daysAgo \
  --end yesterday \
  --limit 50 \
  --pretty

Source split:

python3 ~/.openclaw/workspace/skills/ga4-data-api/scripts/ga4_query.py \
  --metrics sessions \
  --dimensions sessionSourceMedium \
  --start 7daysAgo \
  --end yesterday \
  --limit 50 \
  --pretty

Analysis guidance

For trend questions:

Prefer full days (end=yesterday) unless the user explicitly wants intraday.
Call out whether a same-day drop is just partial-day data.

For conversion questions:

Separate traffic events from true conversion events.
If key events look too broad, recommend narrowing the event set before drawing product conclusions.

References

Read references/setup.md when the user needs the shareable setup process.
Use scripts/ga4_query.py instead of hand-writing fresh GA SDK samples each time.