Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mixpanel/ai-pluginsnpx agentmods add skills/mixpanel/ai-plugins/prepare-ai-readinessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mixpanel/ai-plugins/prepare-ai-readiness)<a href="https://agentmods.dev/skills/mixpanel/ai-plugins/prepare-ai-readiness"><img src="https://agentmods.dev/badge/skills/mixpanel/ai-plugins/prepare-ai-readiness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mixpanel/ai-plugins/prepare-ai-readiness"><img src="https://agentmods.dev/badge/skills/mixpanel/ai-plugins/prepare-ai-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 154 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What 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 5.1 | $0.00083 | $0.02856 |
| Opus 5 | $0.00042 | $0.01428 |
| Sonnet 5 | $0.00017 | $0.00571 |
| Haiku 4.5 | $0.00008 | $0.00286 |
Grade A, and why
prepare-ai-readiness 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 9d 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mixpanel AI Readiness
Engine required — resolve an engine per
ENGINE.md: one named in the conversation or loaded instructions is mandatory (not set up → offer/mixpanel:installfor it); otherwise use the Mixpanel MCP server, or offer/mixpanel:installif it's unavailable.
This skill gets a customer's Mixpanel setup ready for AI assistants (the in-product agent and MCP clients). "Ready" means two layers are in place:
- Business context — markdown designed to be the agent's first read, at org level (who the company is) and project level (how a project is set up), so it can ground the north star, what a "qualified user" means, which project to default to, and the team's conventions. This skill owns this layer.
- Lexicon metadata — descriptions on events, descriptions on properties, and tags. Without these the agent has less signal for what each event and property means. This skill delegates this layer to the
manage-lexiconskill, run inline, rather than reimplementing it.
How the agent consumes each layer evolves with the product — verify current agent behavior against Mixpanel docs.
The skill is import-first: if the customer already has their business knowledge written down somewhere (Notion, a Google Doc, a tracking-plan sheet, a PRD, a pasted block), it pulls that in and maps it onto the template, then interviews only to fill what's missing. It runs as a single interactive session and writes only after explicit preview and confirmation.
Components
Canonical commands
Loaded on demand from commands/.
| Command | File | Match if message contains any of |
|---|---|---|
status |
commands/status.md |
how ready, ai-ready, score, audit, what's missing, check our setup |
import-context |
commands/import-context.md |
import, we already have, pull from, from notion/doc/drive, paste |
setup-context |
commands/setup-context.md |
set up context, configure context, interview, create context |
enrich-data |
commands/enrich-data.md |
event descriptions, property descriptions, tags, clean up events, lexicon |
target |
commands/target.md |
switch level, org vs project, change target, where should this live |
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 165 lines · 83 tokens per session scan A 0091048d172a
prepare-ai-readiness is a skill published in the GitHub repository mixpanel/ai-plugins (15 stars, last pushed 5d ago), licensed Apache-2.0. It adds 83 tokens to every session and 2,856 once invoked, about $0.0004 per session on Opus 5. 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.
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