Agent skill

Audience Research

by gooseworks-ai in gooseworks-ai/goose-skills

Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals.

MITAuto-check passedMarketing & SEO

Install Audience Research

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill audience-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills audience-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/social/composites/audience-research .claude/skills/audience-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
audience-research
GitHub stars
1.2k
Token cost
~586 tokens
SKILL.md length
261 words
Files
2
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals.

  • Works in 6 steps: Define the target audience and the… → Use scrapecreators-api to collect public… → Sample recent comments with… → …
  • Creator comparisons
  • SKILL.md covers Inputs, Workflow, Output and Guardrails
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Audience Research is an agent skill from gooseworks-ai/goose-skills. Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals. Use for creator comparisons, sponsorship fit, market fit, and audience-quality research.

Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).

It sits in Marketing & SEO, covering Market research and Influencer and creator marketing. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Creator comparisons
  • Sponsorship fit
  • Audience-quality research

Example prompts

  • “/audience-research”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Define the target audience and the decision this research must support.
  2. Use scrapecreators-api to collect public profile data, available aggregate audience demographics, profile-region signals, recent content…
  3. Sample recent comments with comment-mining when audience interest or purchase intent matters. Preserve the post and comment source links.
  4. Assess market, language, category, product, community, and engagement-quality fit. Treat content and comment signals as directional…
  5. Score each fit dimension and attach a confidence level based on source coverage, sample size, recency, and agreement across signals.
  6. Compare accounts on the same dimensions and recommend good fit, possible fit, or poor fit with the evidence behind the decision.

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Audience Research loads about 586 tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 261 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~586

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 261 words, ~586 tokens.

Download SKILL.mdSave it as .claude/skills/audience-research/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
audience-research
description
Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals. Use for creator comparisons, sponsorship fit, market fit, and audience-quality research.

Audience Research

Evaluate audience fit without pretending public social data is more complete than it is.

Inputs

  • Target audience, countries, languages, category, product, platform, and campaign goal.
  • One or more creator or brand profiles.
  • Optional Brand Core, exclusions, minimum thresholds, and comparison criteria.

Workflow

  1. Define the target audience and the decision this research must support.
  2. Use scrapecreators-api to collect public profile data, available aggregate audience demographics, profile-region signals, recent content, follower or following samples, and public link-in-bio or shop pages. Separate creator location from audience location.
  3. Sample recent comments with comment-mining when audience interest or purchase intent matters. Preserve the post and comment source links.
  4. Assess market, language, category, product, community, and engagement-quality fit. Treat content and comment signals as directional evidence, not exact audience composition.
  5. Score each fit dimension and attach a confidence level based on source coverage, sample size, recency, and agreement across signals.
  6. Compare accounts on the same dimensions and recommend good fit, possible fit, or poor fit with the evidence behind the decision.

Output

  • Target-audience definition and coverage summary.
  • Audience-fit table with market, language, category, engagement quality, evidence, fit score, and confidence.
  • Account-by-account evidence with source links.
  • Important mismatches, unknowns, and verification gaps.
  • Sponsorship, creator-test, or market recommendation with the next validation step.

Guardrails

  • Use only public and aggregate signals. Never infer protected or sensitive attributes about individuals.
  • Do not convert weak proxies into exact demographic percentages.
  • Do not confuse creator location, follower location, commenter language, and audience geography.
  • Mark unavailable data and low-confidence conclusions instead of filling gaps with assumptions.

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/social/composites/audience-research of gooseworks-ai/goose-skills.

  • SKILL.md
  • skill.meta.json

Open the folder on GitHubat commit c650c6d

Compare with similar skills

Audience Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Audience Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Audience Research this skillgooseworks-ai/goose-skills1.2k—~586Automated safety check: PassMIT
Audience ResearchScrapeCreators/social-media-research-skills3.4k—~635Automated safety check: NotesMIT
Youtube Channel API Skillbrowser-act/skills6.1k1 repos~1.5kAutomated safety check: PassMIT
Interactive Contentsocial-media-skills/skills134—~2kAutomated safety check: PassMIT
Social Proof And Testimonialssocial-media-skills/skills134—~1.9kAutomated safety check: PassMIT
Customer ResearchNexus-JPF/note-companion8706 repos~3.2kAutomated safety check: PassMIT

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    3.4k GitHub stars~635 tokensUpdated 1 mo ago
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  • Youtube Channel API Skill

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Categories

Questions about Audience Research

What does Audience Research do?

Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals. Audience Research is an agent skill from gooseworks-ai/goose-skills. Evaluate whether a creator, influencer, or brand account reaches the right audience using public profile, aggregate demographic, geography, language, content, comment, and commerce signals.

When should I use Audience Research?

Audience Research fits situations like: creator comparisons; sponsorship fit; audience-quality research.

How do I install Audience Research in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill audience-research -a claude-code`. Or copy the skill folder (skills/social/composites/audience-research in gooseworks-ai/goose-skills) into .claude/skills/audience-research in your project. Claude Code loads it when a task matches its description.

How do I install Audience Research in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill audience-research -a codex`. Or copy the skill folder (skills/social/composites/audience-research in gooseworks-ai/goose-skills) into .agents/skills/audience-research in your project. Codex loads it when a task matches its description.

Can I use Audience Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill audience-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audience-research, .gemini/skills/audience-research, .github/skills/audience-research and .opencode/skills/audience-research in your project.

What does Audience Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Audience Research is instructions for the agent only.

Does Audience Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Audience Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Audience Research use?

Audience Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Audience Research use?

About 586 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Audience Research?

Skills that share tags, products or a category with Audience Research: Audience Research (ScrapeCreators/social-media-research-skills, 3.4k stars), Youtube Channel API Skill (browser-act/skills, 6.1k stars), Interactive Content (social-media-skills/skills, 134 stars) and Social Proof And Testimonials (social-media-skills/skills, 134 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Audience Research?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.