audience-research

audience-research is a skill for Claude Code from Motion-Creative/motion-creative-plugin. It costs 44 tokens per session (3,435 once invoked), scanned A, original, MIT.

A research workflow for understanding an audience, including who they are, how customers describe their needs, and what competitors emphasize.

In plain words
What is it for?
Use it to define target audiences, extract recurring themes and language from customer reviews, or analyze competitors before creating concepts, hooks, or other creative work.
Why use it?
Creative work is harder when the target audience and their real concerns are unclear. This workflow organizes audience definition, customer-review analysis, and competitor analysis.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; names the AskUserQuestion tool.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the motion-creative plugin — 17 skills, 1 MCP server shipped together

Good fit Use it to define target audiences, extract recurring themes and language from customer reviews, or analyze competitors before creating concepts, hooks, or other creative work.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add Motion-Creative/motion-creative-plugin
Claude Code
/plugin install motion-creative

Made for: Claude Code.

Or install motion-creative, the plugin that ships this one along with the rest of its 17 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-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/motion-creative/motion-creative-plugin/audience-research/github.svg)](https://agentmods.dev/skills/motion-creative/motion-creative-plugin/audience-research)
Your own site
<a href="https://agentmods.dev/skills/motion-creative/motion-creative-plugin/audience-research"><img src="https://agentmods.dev/badge/skills/motion-creative/motion-creative-plugin/audience-research/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.

agentmods 80×15 button for audience-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/motion-creative/motion-creative-plugin/audience-research"><img src="https://agentmods.dev/badge/skills/motion-creative/motion-creative-plugin/audience-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,435 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00044 $0.03435
Opus 5.5 $0.00018 $0.01374
Sonnet 5.5 $0.00009 $0.00687
Haiku 4.5 $0.00004 $0.00344

Measured 1mo ago against content hash 074644655afa, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

audience-research 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 1mo 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.

Plugin/skills/audience-research/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audience Research

Three types of audience intelligence that feed creative strategy: defining who you're talking to, understanding how they actually talk and think, and reading what competitors are betting on.


Phase 0: Orient

  1. Acknowledge: "I'll help you understand your audience -- who they are, how they talk, and what competitors are doing."
  2. Detect mode from $ARGUMENTS and user message:
    • definition -- who to target (tension-based audience mapping)
    • reviews -- how they talk (5-bucket review mining)
    • competitive -- what competitors bet on (competitive audience analysis)
    • full -- all three, sequentially
    • If ambiguous, ask: "Do you want audience definition, review mining, competitive analysis, or the full picture?"
  3. Connected workflows: After audience work, the user can flow into /create-concepts, /write-hooks, or /concept-engine with the audience context established here.

If the user already specified a mode or their intent is clear, skip questions and proceed.


Phase 1: Setup

1a. Parse Arguments

  • --mode: One of definition, reviews, competitive, full. Default: detect from user message, or ask.
  • --datePreset: Controls performance data window. Default: LAST_30_DAYS. Options: LAST_7_DAYS, LAST_14_DAYS, LAST_30_DAYS, LAST_90_DAYS.

1b. Load Settings & Auth

  1. Read ${CLAUDE_PLUGIN_ROOT}/motion-creative.config.md for org-specific configuration. If the file does not exist, use these defaults and suggest the user run /customize:
    • primary_kpi: use goalMetric from first get_creative_insights response
    • default_date_preset: LAST_30_DAYS
    • Brand guidelines + competitors: pull from Motion API
  2. Call get_auth_context() to resolve workspaceId.
  3. Call get_workspace_brand(workspaceId) for positioning context -- brand voice, target audience, product details.
  4. Use default_date_preset from settings as the datePreset for all calls unless the user provided a --datePreset argument.

Read the full file on GitHub · 285 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. 1mo ago First seen · 285 lines · 44 tokens per session scan A 074644655afa

Subscribe to this mod's changes

audience-research is a skill published in the GitHub repository Motion-Creative/motion-creative-plugin (24 stars, last pushed 4mo ago), licensed MIT. It adds 44 tokens to every session and 3,435 once invoked, about $0.0002 per session on Opus 5.5. 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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