Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/mixpanel/ai-plugins/enrich-datagit clone --depth 1 https://github.com/mixpanel/ai-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00531 |
| Opus 5 | $0.00000 | $0.00266 |
| Sonnet 5 | $0.00000 | $0.00106 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
enrich-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command: enrich-data
Set up the Lexicon metadata the agent needs to understand the data itself: event descriptions, property descriptions, and tags. This command delegates to the manage-lexicon skill run inline — it does not reimplement enrichment. Its job is to hand off cleanly and capture the result for the unified readiness status.
Session reads: org_id, project_id, project_name, caller_role Session writes: lexicon_score
Step 1 — Preconditions
- A project must be in scope (
project_id). If only org-level context was being worked on, ask which project to enrich — Lexicon is per-project. - The caller needs write permission for Lexicon (see SKILL.md's "Permissions gate writes" constraint for the role matrix). Check
caller_role; if missing, name the required role and offer to have an admin run this step. - Confirm
manage-lexiconis available. If it is not, follow SKILL.md's "manage-lexiconcan be unavailable" constraint — additionally, point the user to themanage-lexiconskill in the Mixpanel skills repository, then return.
Step 2 — Hand off to manage-lexicon
Hand this project_id to manage-lexicon and let it do two things, in this order: first measure current metadata health (description coverage on events and properties, tag coverage) and capture that score; then fill empty event and property descriptions and add tags — using whatever entry points that skill exposes. Respect its own guardrails (verify current behavior against that skill) — expect at least fill-only-empty (never overwrite existing metadata), add tags rather than replace, and a preview + CONFIRM gate before writes. Those guardrails are the reason we delegate rather than rebuild — don't bypass them.
Let manage-lexicon own its previews and confirmations. This command does not duplicate or wrap those prompts; the user interacts with manage-lexicon's flow directly.
Step 3 — Capture result
After enrichment, record the post-run coverage into lexicon_score (events described %, properties described %, events tagged %), so status can show both layers in one readout. If manage-lexicon ran a final score, reuse it; otherwise ask it to score coverage once more to capture the after state.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 28 lines · 0 tokens per session scan A 596b31a51577
enrich-data is a command published in the GitHub repository mixpanel/ai-plugins (15 stars, last pushed 9d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 531 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.