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Run Organic Social Account Audit

OrganizationPopular
gooseworks-ai
run-organic-social-account-audit

Reviews a brand's own social accounts: what each is for, the last ~30 posts ranked against the account's own median with the likely reason for top and bottom posts, cadence actually kept, best posting times, and bio and pinned-post fixes. Use alone when you already know which accounts to review and can read their posts; otherwise run run-organic-social.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namerun-organic-social-account-audit
Stars
1.3K
Forks
219
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Run Organic Social Account Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gooseworks-ai/goose-skills/tree/main/skills/marketing/run-organic-social-account-audit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/marketing/run-organic-social-account-audit .claude/skills/run-organic-social-account-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Run Organic Social Account Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Run Organic Social Account Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Run Organic Social Account Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Account audit

Run before the first calendar, and lightly (reconciliation only) on later runs.

1. Which accounts exist and what each is for

  • gooseworks:brand_read sections: ["accounts","sources","organic"]. organic.own_accounts lists the brand's own TikTok/IG handles. sources lists saved public sources, including relationship: self social accounts. accounts lists connected accounts.
  • gooseworks:social_account_list: the TikTok/IG accounts the product manages, with their setup status. Read each with gooseworks:social_strategy_get (pillars, voice, rules, plug-ratio cap).
  • The brain has no record of LinkedIn, X, Threads, YouTube, Pinterest or Facebook accounts today, so check social/accounts.md in the workspace for a previous run's answers. Ask only for what is still missing: handles, which ones matter, brand vs founder, who approves founder posts, the time zone, the tool they post from, their free windows for the first hour after posting.

2. What has worked (per account)

  • TikTok/IG: own_posts from brand_read organic give caption, posted_at, views, likes and comments. gooseworks:social_analytics_get adds more for managed, connected accounts (it says not_available otherwise).
  • More history, or LinkedIn, X and Threads: read the account's own posts through the proxy (the marketing-data-access skill (../marketing-data-access/SKILL.md); verified endpoints only, as listed in ../run-organic-social/references/voice-card.md). Use the author's own posts only. For X: /v1/twitter/profile, then /v1/twitter/user-tweets (popular posts, not the newest: check created_at; the numbers are in legacy). This runs under the spend-gate skill (../spend-gate/SKILL.md) branch B: one yes to a ceiling, asked in the draft-report message (SKILL.md step 2), with the probe run inside it and every charge logged. Without the yes: the public profile in the host browser, or 5–10 pasted posts.
  • State the window you actually got (e.g. "7 IG posts, Oct 5–12"). The server returns recent posts only, and some captions come back cut off mid-word: flag those.
  • Rank by engagement relative to the account's own median, not absolute numbers. For the top and bottom posts (5 each with 15+ posts, 3 each below that), note the likely why: hook, format, topic, person featured, length, time.
  • Note efficacy or other claims in past captions that are not signed off, so drafts don't copy them.
  • Cadence actually kept: posts per week over the window you have (up to ~8 weeks). Say how long the window is.
  • Best posting slots: day and hour (in the account's time zone; ask it if unknown, since the server gives UTC) of the top performers. With fewer than ~10 posts, use the account's own usual posting times as the starting guess (label it so), not generic charts.
  • Competitor and category references: gooseworks:social_inspiration_search, then brand_read organic.competitor_top_posts. These are for formats and hooks only; never copy them. Skip any that are clearly outside the brand's category (a mis-resolved competitor).

3. Profile hygiene (text the human can paste)

  • Bio and pinned posts: no tool returns these today, so read the public profile in the host browser; if it won't open, ask in the draft-report message. Then: does the bio say who it's for and why to follow, in the voice? If not, draft one rewrite within the platform limit (IG 150, TikTok 80, X 160, LinkedIn headline 220).
  • Link in bio / pinned posts: do they point at the current priority? Suggest the swap.

Output

Account audit — <brand> · <date>
| Account | Platform | Job | Cadence kept (8 wks) | Median engagement | Best slots | Voice card? |
Top 5 / bottom 5 per account, with the why
What to make more of / stop: …
Bio + pinned suggestions: …
Unknowns asked: …

Write it to social/audit/<YYYY-MM-DD>.md. Write the account roster (jobs, handles, time zone, posting tool, free windows) to social/accounts.md. Both use gooseworks:file_write in the brand coworker scope.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Run Organic Social Account Audit AI skill do?

Reviews a brand's own social accounts: what each is for, the last ~30 posts ranked against the account's own median with the likely reason for top and bottom posts, cadence actually kept, best posting times, and bio and pinned-post fixes. Use alone when you already know which accounts to review and can read their posts; otherwise run run-organic-social.

Why use Run Organic Social Account Audit on TypingMind?

Because you install it once and use it with any model. Run Organic Social Account Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Run Organic Social Account Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/marketing/run-organic-social-account-audit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Run Organic Social Account Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Run Organic Social Account Audit?

As many as you like. As long as a model supports skills, you can use Run Organic Social Account Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Run Organic Social Account Audit AI skill free?

Yes. It is published on GitHub by gooseworks-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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