Eikonoikari1 Skillport Skillport

Note: Run scripts/render-context.sh before first use to inject dynamic context.

skillport: Universal Skill/Rule Adapter

Step 1: Understand the Request

Parse the user's prompt to extract three things:

1. WHAT — Which skill/rule/config to convert
   • A path (e.g., .claude/skills/my-skill, CLAUDE.md, .cursor/rules/)
   • A skill name (e.g., "clearshot", "toc") — resolve to its installed path
   • "all" or "everything" — scan for all detected configs
2. FROM — Source harness format
   • Explicit: "from claude", "from cursor", etc.
   • Implicit: auto-detect from path and file contents
3. TO — Target harness format(s)
   • Explicit: "to cursor", "to codex and openclaw", "to all"
   • One or more of: claude, cursor, codex, openclaw, copilot, windsurf, all

Examples of natural language parsing:

Resolution Rules:

• If WHAT is a name (not a path), search these locations:

  • ~/.claude/skills/<name>/
  • ~/.agents/skills/<name>/
  • .claude/skills/<name>/ (project-local)
  • .agents/skills/<name>/ (project-local)
  • .cursor/skills/<name>/
  • .cursor/rules/<name>.mdc

• If FROM is not stated, auto-detect by running the CLI:

  npx tsx ~/.claude/skills/skillport/bin/skillport.ts detect .
  

• NEVER start conversion until WHAT, FROM, and TO are all resolved.

Step 2: Confirm Before Converting

Always show the user what you're about to do:

I'll convert:
  Skill:  <name> (<path>)
  From:   <harness> (auto-detected / specified)
  To:     <target harness(es)>

Proceed?

Wait for confirmation. If the user says "just do it" or similar, proceed.

Step 3: Run the Conversion

Execute the CLI:

npx tsx ~/.claude/skills/skillport/bin/skillport.ts convert <source-path> --to <targets> --output <dir>

For dry run (preview without writing):

npx tsx ~/.claude/skills/skillport/bin/skillport.ts convert <source-path> --to <targets> --dry-run

For project scan:

npx tsx ~/.claude/skills/skillport/bin/skillport.ts detect <dir>

Step 4: Present the Result Report

After conversion, ALWAYS present the full report to the user. The report has three mandatory sections:

Section 1: Conversion Summary

Show what was converted and where files were written:

skillport: <name> (<from> → <to>)

  Source:  <source path>
  Target:  <target path>

  Fields:  N total
    ✓  X native   (fields that mapped 1:1)
    ⚡  Y shimmed  (fields with functional approximations)
    ⚠  Z dropped  (fields with no equivalent)

Section 2: Parity Assessment

Show a percentage score and per-feature breakdown:

Parity: NN% (Full|High|Partial|Low)

  Feature Coverage:
    ✓ Core instructions       100%  Markdown body preserved
    ✓ Activation trigger      100%  description-based discovery
    ⚡ Tool restrictions        80%  Instruction text, not enforced
    ⚠ Hooks                     0%  No equivalent in target
    ...

  Verdict: <plain-English assessment>

Parity levels:

• 95-100% Full — skill works identically
• 80-94% High — core behavior preserved, minor features shimmed
• 50-79% Partial — key features approximated, some lost
• <50% Low — significant gaps, manual adaptation recommended

Section 3: Tradeoffs & Key Points

Short bullet list of the most important things to know:

Key Points:
• <what changed and why it matters>
• <what the user should watch out for>
• <round-trip safety notes>

Supported Harnesses

Feature Adaptation Quick Reference

• Hooks: CC→Cursor maps PreToolUse→beforeShellExecution. Others get wrapper scripts or annotations.
• Subagents: CC→Cursor is near-native. Codex has fork. Others get instruction annotations.
• allowed-tools: Only CC enforces per-skill. Others get instruction text (agent may ignore).
• Globs: CC uses paths:, Cursor uses globs:, Copilot uses applyTo:. Others get annotations.
• Dynamic context (!cmd``): CC-only native. Others get preprocessor scripts or preamble blocks.
• Model/effort overrides: CC-only. Dropped with annotation for others.

Source: eikonoikari1/skillport — distributed by TomeVault.