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 skills add big-emotion/agent-atelier --skill audience-auditgit clone --depth 1 https://github.com/big-emotion/agent-atelierWrote 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/big-emotion/agent-atelier/audience-audit)<a href="https://agentmods.dev/skills/big-emotion/agent-atelier/audience-audit"><img src="https://agentmods.dev/badge/skills/big-emotion/agent-atelier/audience-audit/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/big-emotion/agent-atelier/audience-audit"><img src="https://agentmods.dev/badge/skills/big-emotion/agent-atelier/audience-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00122 | $0.02081 |
| Opus 5.5 | $0.00049 | $0.00832 |
| Sonnet 5.5 | $0.00024 | $0.00416 |
| Haiku 4.5 | $0.00012 | $0.00208 |
Grade A, and why
audience-audit scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "$BASE/top-stats?period=30d" How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audience Audit
Headings are fixed. Section headings are fixed identifiers: copy them exactly as written in the deliverable templates (English, with the same hash marks), whatever the language of the profile. Only the text under a heading is written in the profile's language.
Measures the audience, classifies the pages, writes one dated report. It is the producer of the comms pipeline:
/audience-audit → <reports>/audit-YYYY-MM-DD.md → /content-strategist
The handoff is a file, not a conversation. The consumer runs in a session that never saw this one, so anything it needs must survive in the report.
This skill never modifies source, never publishes, never posts, never schedules. It reads analytics, reads the repository, writes one Markdown file.
The project profile
Four things are project-specific. Ask for any that is not already recorded in the project's own documentation, and write them into the report's header so the next run is comparable.
| Input | Example shape |
|---|---|
| Analytics endpoint and site id | a self-hosted Plausible instance and the domain it tracks |
| Content inventory command | the shell command that counts what the project publishes |
| Route source | the sitemap route's source, or the router directory |
| Report destination | the directory holding the dated series |
Read the sitemap route's source rather than running a full build. The build is slow and this audit does not need its output.
Step 1 — Read the analytics over its API, not its dashboard
A self-hosted Plausible instance answers its internal stats API without authentication and without a browser. Use it: scriptable, exact, and immune to the dashboard's rendering quirks.
BASE=https://<instance>/api/stats/<site-id>
curl -s "$BASE/top-stats?period=30d"
curl -s "$BASE/pages?period=30d&detailed=true&limit=200"
curl -s "$BASE/entry-pages?period=30d&detailed=true&limit=100"
curl -s "$BASE/exit-pages?period=30d&detailed=true&limit=100"
curl -s "$BASE/sources?period=30d&detailed=true"
curl -s "$BASE/screen-sizes?period=30d&detailed=true"
curl -s "$BASE/countries?period=30d"
What ships with it
2 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.
- 10d ago Changed · +14 lines 1db168a6badb
- 1mo ago First seen · 179 lines · 122 tokens per session scan A 38880c49c6d3
audience-audit is a skill published in the GitHub repository big-emotion/agent-atelier (3 stars, last pushed 2d ago), licensed MIT. It adds 122 tokens to every session and 2,081 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-08.
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