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post-scorer

Score a social post draft against the user's historical performance data or, when no history is supplied, with a clearly labeled heuristic rubric.

Skill by imMamdouhaboammar

IndexedMIT
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/immamdouhaboammar-post-scorer

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Score a social post draft against the user's historical performance data or, when no history is supplied, with a clearly labeled heuristic rubric. Use when the user asks to score, benchmark, predict, or critique a draft for performance.

Use cases: data

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/post-scorer

What's inside

Skill name
post-scorer
Description
Score a social post draft against the user's historical performance data or, when no history is supplied, with a clearly labeled heuristic rubric. Use when the user asks to score, benchmark, predict, or critique a draft for performance.
License
MIT
Instructions
50 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • openai.yaml · agents/

SKILL.md (first lines)

# Post Scorer

## Preferred evidence

Use one of:

- LinkedIn analytics export
- CSV of post history
- spreadsheet with impressions, reactions, comments, saves, clicks, followers, or dates
- a set of past posts paired with performance metrics

If the data is available as files, use host file tools. Use Python for deterministic calculations when the host provides it.

## Data-backed mode

1. Clean the post history.
2. Choose metrics that are actually present.
3. Normalize rate metrics where possible.
4. Compare the draft's structural features to the user's stronger and weaker posts.
5. Separate correlation from causation.
6. Produce a score from 0 to 100 with an explanation of how it was derived.
7. Give the smallest set of changes most likely to improve the draft.

## Heuristic mode

If no historical performance data exists, label the result `Heuristic score`. Evaluate:

- clarity
- opening strength
- specificity
- credibility
- reader relevance
- pacing
- novelty
- payoff
- CTA fit

Do not imply the heuristic predicts actual reach.

## Output

- mode: data-backed or heuristic
- score
- strongest element
- main risk
- 3 highest-priority edits
- revised opening if useful
- evidence limits

From imMamdouhaboammar/creator-workbench, MIT.

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Last commit (this folder)
Sep 24, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

post-scorer skill. Agent Mart. https://agentmart.dev/skills/immamdouhaboammar-post-scorer (last updated 2026-10-24)