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 skills/wattdata/plugin/audience-activatenpx skills add wattdata/plugin --skill audience-activategit clone --depth 1 https://github.com/wattdata/pluginWhat 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 | $0.00168 | $0.12742 |
| Opus 5 | $0.00084 | $0.06371 |
| Sonnet 5 | $0.00034 | $0.02548 |
| Haiku 4.5 | $0.00017 | $0.01274 |
Grade A, and why
audience-activate 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 yesterday.
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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Activate an audience
Purpose
audience-activate — the export step behind /watt:audience — turns a built audience into the deliverable: a file per platform, each shaped to that platform's spec by its bundled writer script — one script per platform under scripts/writers/. The writer scripts present are the platforms that ship — Meta, Google, Reddit, and TikTok, each its own self-contained writer script. The user picks one platform or several, confirms exactly what will happen, and walks away with the files, their row counts, and the reproducibility handle. The audience is materialized once, however many platforms are picked — the pull off Signal Graph is the expensive part, so it happens a single time and each platform's file is shaped from that one pull.
Nothing exports unconfirmed. Before the run, state plainly: the platforms, roughly how many people, which identifier types ride along, what each platform's spec does to them, and the exact row ceiling. Each platform's writer owns that transform, and they differ — confirm each one the user picked: a Meta file hashes emails, phones, names, cities, states, zips, and country, with mobile-ad IDs riding raw (the one identifier Meta keeps in the clear); a Google file hashes emails, phones, and names but keeps country and zip in the clear, with mobile device IDs written to a separate unhashed list; a Reddit file hashes emails and takes mobile-ad IDs raw, both in one combined list; a TikTok file hashes emails and phones and takes mobile-ad IDs raw, all in one row per person (with a 1,000-person upload floor). Device IDs are off by default — every export is contact-only unless the user asks for mobile-ad IDs (or "device IDs" / "MAIDs"); when they do, the confirmation says so and the after-export pass runs once the contact files are delivered. The user's explicit yes — including that number — is the gate. Anything truncated or pruned is named before the run, never discovered after.
What ships with it
6 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.
- yesterday First seen · 197 lines · 168 tokens per session scan A d3c2d4af9df2
audience-activate is a skill published in the GitHub repository wattdata/plugin (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 168 tokens to every session and 12,742 once invoked, about $0.0008 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 2026-08-31.
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