markdown-token-optimizer Skill
Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI, token efficiency, verbose markdown, reduce file size Published by microsoft in GitHub-Copilot-for-Azure.
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Documentation, Includes SKILL.md, Reusable instructions
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Copy skill directory
2 months ago · NOASSERTION license
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What is markdown-token-optimizer Skill?
Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI, token efficiency, verbose markdown, reduce file size Published by microsoft in GitHub-Copilot-for-Azure. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Documentation
- Documentation use cases
Declared skill metadata
- Declared author: Microsoft
- Declared license: MIT
- Source file: .github/skills/markdown-token-optimizer/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use markdown-token-optimizer Skill
- Use it for documentation.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/GitHub-Copilot-for-Azure
- Skill file: .github/skills/markdown-token-optimizer/SKILL.md
What it does
Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI, token efficiency, verbose markdown, reduce file size
Skill instructions
Markdown Token Optimizer This skill analyzes markdown files and suggests optimizations to reduce token consumption while maintaining clarity. When to Use - Optimize markdown files for token efficiency - Reduce SKILL.md file size or check for bloat - Make documentation more concise for AI consumption Workflow 1. Count - Calculate tokens (~4 chars = 1 token), report totals 2. Scan - Find patterns: emojis, verbosity, duplication, large blocks 3. Suggest - Table with location, issue, fix, savings estimate 4. Summary - Current/potential/savings with top recommendations See ANTI-PATTERNS.md for detection patterns and OPTIMIZATION-PATTERNS.md for techniques. Rules - Suggest only (no auto-modification) - Preserve clarity in all optimizations - SKILL.md target: <500 tokens, references: <1000 tokens References - OPTIMIZATION-PATTERNS.md - Optimization techniques - ANTI-PATTERNS.md - Token-wasting patterns
Verified compatibility and discovery
Frequently asked questions
What is markdown-token-optimizer?
markdown-token-optimizer is a open-source AI agent skill with Copy skill directory. Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI.
Who is markdown-token-optimizer best for?
markdown-token-optimizer is best for reusing agent instructions, scripts, and references, documentation workflows.
How do I install markdown-token-optimizer?
Install or run markdown-token-optimizer using Copy skill directory. Check markdown-token-optimizer for the latest setup command.
Is markdown-token-optimizer actively maintained?
markdown-token-optimizer may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
