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Analytics Report

Organization
PostPeer-API
analytics-report

Retrieve and summarize PostPeer social analytics for posts, platforms, connected accounts, date ranges, impressions, views, likes, comments, shares, saves, clicks, and engagement. Use when the user asks for performance reports, analytics dashboards, best or worst posts, account metrics, direct platform analytics, or metrics for posts not created through PostPeer.

Overview

PublisherPostPeer-API
Repositoryskills
Skill nameanalytics-report
Stars
73
Forks
1
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • 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 PostPeer-API on GitHub. Read the source before you install it.

Installation

Install the Analytics Report 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/PostPeer-API/skills/tree/main/skills/analytics-report
  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/PostPeer-API/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/analytics-report .claude/skills/analytics-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analytics Report 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 Analytics Report 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 Analytics Report 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.

Analytics Report

Use the bundled PostPeer MCP tools for live analytics. Never retrieve credentials from the user's machine or ask the user to paste a secret into chat. If authentication fails, direct the user to update the PostPeer API key in Claude's plugin configuration UI.

Routing

  • Single PostPeer post: call get_analytics with postId.
  • Recent PostPeer posts: call get_analytics with fromDate, toDate, sorting, pagination, and an optional platform.
  • Direct platform account analytics: call get_analytics with source: "platform", platform, and accountId.
  • External platform post ID: include platform and accountId so PostPeer can resolve it.
  • If the connected server advertises a more specific analytics tool for the requested platform, use that documented tool rather than inventing parameters.

Workflow

  1. Resolve the date range to absolute YYYY-MM-DD values and state the timezone used.
  2. Resolve account IDs with list_integrations when needed.
  3. Fetch analytics with the narrowest MCP query that satisfies the request.
  4. Sort by the requested metric when supported: date, likes, comments, impressions, views, shares, saves, clicks, or engagement.
  5. Report the key result, data limitations, and a useful next action.

Caveats

  • Platform APIs differ. Do not compare views and impressions as if they were identical.
  • Some platforms expose delayed, sampled, or partial metrics.
  • If a published platform post cannot be matched, report that resolution is needed instead of fabricating metrics.
  • Reading analytics is non-destructive. Confirm before any follow-up action that changes posts, accounts, or notification settings unless the user explicitly requested it.

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 Analytics Report AI skill do?

Retrieve and summarize PostPeer social analytics for posts, platforms, connected accounts, date ranges, impressions, views, likes, comments, shares, saves, clicks, and engagement. Use when the user asks for performance reports, analytics dashboards, best or worst posts, account metrics, direct platform analytics, or metrics for posts not created through PostPeer.

Why use Analytics Report on TypingMind?

Because you install it once and use it with any model. Analytics Report 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 Analytics Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PostPeer-API/skills/tree/main/skills/analytics-report. 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 Analytics Report?

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 Analytics Report?

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

Is the Analytics Report AI skill free?

Yes. It is published on GitHub by PostPeer-API 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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