audience-review

audience-review is a skill for Claude Code from logly/mureo. It costs 147 tokens per session (4,319 once invoked), scanned A, original, Apache-2.0.

An advertising-audience review that compares the people and placements an ad campaign targets with the intended customer described in STRATEGY.md. Placements are the websites, apps, or network locations where ads appear.

In plain words
What is it for?
Use it to inspect audience segments, demographics, placements, devices, lookalike audiences, spend, and conversions, then propose changes tied to the stated customer persona.
Why use it?
It exposes targeting drift, such as spending on excluded groups or low-value placements, before the campaign continues wasting budget.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is PREREQUISITE: Read `../_mureo-shared/SKILL.md` for auth, security rules, output format, and **Tool Selection** (Read/Write on Code, `mureo_strategy_*` / `mureo_.

Part of the mureo plugin — 27 skills, 1 MCP server shipped together

Install

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.

Clone the repo
git clone --depth 1 https://github.com/logly/mureo
agentmods
npx agentmods add skills/logly/mureo/audience-review

Made for: Claude Code.

Or install mureo, the plugin that ships this one along with the rest of its 27 skills, 1 MCP server.

Wrote 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.

agentmods badge for audience-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/logly/mureo/audience-review.svg)](https://agentmods.dev/skills/logly/mureo/audience-review)
Your own site
<a href="https://agentmods.dev/skills/logly/mureo/audience-review"><img src="https://agentmods.dev/badge/skills/logly/mureo/audience-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 147 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,319 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00147 $0.04319
Opus 5 $0.00073 $0.02159
Sonnet 5 $0.00029 $0.00864
Haiku 4.5 $0.00015 $0.00432

Measured 2d ago against content hash 9deb7b57b3f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

audience-review 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 2d 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.

mureo/_data/skills/audience-review/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audience Review

PREREQUISITE: Read ../_mureo-shared/SKILL.md for auth, security rules, output format, and Tool Selection (Read/Write on Code, mureo_strategy_* / mureo_state_* MCP on Desktop / Cowork).

Reconcile who you say you want (the STRATEGY.md Persona / Target Audience) with who you are actually paying to reach (the live targeting and the segments where spend lands). Accounts drift: a broad audience quietly spends on a segment the Persona excludes, a placement like Audience Network burns budget with zero conversions, or the Persona implies a lookalike that was never built. This skill inventories current targeting, scores performance by segment, flags the mismatches, and proposes Persona-anchored changes.

Prerequisites

  • STRATEGY.md and STATE.json must exist (run the onboard skill first)

Steps

Before you start: Run the Diagnostic preamble from ../_mureo-shared/SKILL.md — load learning insights (mureo_learning_insights_get) and consult advisors (mureo_consult_advisor) before drawing conclusions.

  1. Establish today: call mureo_state_get first, on every host (including Claude Code, where you would otherwise Read the file) and take server_now from its response — ISO 8601 with UTC offset, e.g. 2026-07-28T10:12:33+09:00. Its date is the only source of the current date for this run: the observation_due you write in step 10 is server_now's date + 14 days. Do not shell out (this skill must run in Bash-less headless hosts) and do not read the date off STATE.json — last_synced_at, reports.*.period and action_log timestamps are history, never evidence of what day it is now. Never write server_now into STATE.json: it is a response field, and a persisted copy becomes tomorrow's stale "today".

  2. Load context: Read STRATEGY.md — especially the Persona and Target Audience (age, gender, interests, geography, device intent, exclusions the Persona implies) and each Goal's success metric — and STATE.json. The Persona is the yardstick for every judgement below; if STRATEGY.md has no Persona, say so and offer to capture one via /onboard rather than inventing demographics.

Read the full file on GitHub · 93 lines

Changes

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.

  1. 2d ago Changed 9deb7b57b3f2
  2. 6d ago First seen · 93 lines · 147 tokens per session scan A c33a3c6b9660

Subscribe to this mod's changes

audience-review is a skill published in the GitHub repository logly/mureo (43 stars, last pushed 4d ago), licensed Apache-2.0. It adds 147 tokens to every session and 4,319 once invoked, about $0.0007 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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