Skill Translate

Skill Translate — Cross-Platform Skill Porting

Gets a skill running on a platform other than the one it was written for. That means one of two very different jobs, and picking the wrong one wastes the whole run — so Step 0 exists to decide which.

Read references/platform-matrix.md for the full compatibility matrix and per-platform conversion rules.

Required Input

1. Source skill — path to a skill directory or SKILL.md file
2. Target — one of: claude-code, codex, cursor, native-all, chatgpt, gemini, perplexity, hermes, or all

If no target is specified, ask which tier the user means rather than guessing — "install everywhere I code" and "make this work in ChatGPT" are different jobs with different costs.

Step 0 — Decide whether this is an install or a translation

Do this first, every time. Agent Skills is an open standard (agentskills.io), and as of mid-2026 it is read natively by a large and growing set of tools. For those, the skill is already in the right format — copying the folder is the port. Translating it would be work that degrades a working artifact.

Tier 1 — native standard. Install, do not translate. These read SKILL.md with name + description frontmatter unchanged:

Verified July 2026 against the agentskills.io specification and Cursor's skills docs. Cursor additionally reads .claude/skills/ and .codex/skills/ as legacy paths. Tool support moves fast — check the target's current docs before asserting a path that is not in this table.

For Tier 1, run the bundled installer and stop:

scripts/install_skill.sh <path-to-skill-dir> [claude|codex|cursor|all]

It copies the skill folder, strips packaging cruft (.zip, .skill, .DS_Store, __pycache__), fixes script permissions, and validates that name matches the parent directory — the single most common reason a correctly-written skill silently fails to load.

Tier 2 — proprietary format. Translate. ChatGPT (Custom GPTs + Actions), Gemini (Gems, GEMINI.md), Perplexity (Spaces), Hermes Agent. These have their own configuration surfaces and hard character limits. Continue to Step 1.

Mixed request ("get this everywhere"): install Tier 1 first, report it, then translate for Tier 2. Never make the user wait on a lossy conversion to find out the lossless copy already worked.

Step 1 — Read and Analyze the Source Skill

Read the source SKILL.md and all files in references/, scripts/, and assets/. Identify:

• Core instructions — the behavioral logic in the SKILL.md body
• MCP dependencies — which MCP tools the skill calls (search_thoughts, save_thought, etc.)
• Bundled resources — reference docs, scripts, templates
• Triggers — the MANDATORY TRIGGERS list from the description
• Character budget — total token count of the skill body + references

Step 2 — Assess Platform Compatibility

For each target platform, check the compatibility matrix in references/platform-matrix.md:

Step 3 — Convert

For each target platform, follow the conversion procedure in references/platform-matrix.md. The output for each platform is different:

ChatGPT → Custom GPT Configuration

• Instructions block (max 8,000 chars) — compressed skill body
• Knowledge files — references/ docs uploaded as files
• Actions (if MCP tools needed) — OpenAPI 3.0 spec pointing to Open Brain REST API
• Paste-ready text for the GPT Builder UI

Gemini → Gem + optional GEMINI.md

• Gem instructions (target ~2,000 chars) — compressed skill body
• GEMINI.md (for Gemini CLI) — full skill body as markdown
• MCP config snippet — for ~/.gemini/settings.json if MCP tools needed

Perplexity → Space Configuration

• Space instructions (target ~1,500 chars) — heavily compressed, search-oriented
• Knowledge files — references/ docs uploaded to Space
• MCP workaround — instructions to use Perplexity as a research tool called FROM the skill, not as the skill host

Hermes Agent → SKILL.md + tools/

• SKILL.md — near-identical to Claude format (Hermes uses agentskills.io standard)
• Hermes-specific frontmatter — add platforms, metadata.hermes.tags, metadata.hermes.related_skills
• tools/ integration — map MCP tool calls to Hermes tool registry entries
• Memory integration — map Open Brain writes to Hermes memory system if applicable

Step 4 — MCP Dependency Resolution

When the source skill depends on MCP tools (like Open Brain), handle per platform:

Step 5 — Produce Output

For each target platform, produce:

1. The converted artifact — ready to paste or deploy
2. Installation instructions — exact steps to install on that platform
3. Capability delta — what the original skill does that the converted version cannot do (honest assessment)
4. MCP setup instructions — if the skill uses MCP tools, how to connect them on that platform

Format the output with clear section headers per platform. If producing all, use a separator between platforms.

Step 6 — Compression Strategy (when hitting character limits)

When the source skill exceeds the target platform's character limit:

1. Cut references first — move them to uploaded knowledge files instead of inlining
2. Collapse tables into prose — tables are token-expensive
3. Remove examples — keep the rules, cut the examples
4. Merge similar steps — combine steps that share logic
5. Use imperative shorthand — "Save decisions with permanent:true" not "For each qualifying decision, call save_thought with the permanent parameter set to true"
6. Never cut the triage logic — the classification rules are the skill's core value

If still over limit after all compression, split into a primary instruction block + a knowledge file that the model retrieves on demand.

Edge Cases

Skill has no MCP dependencies: Straightforward text conversion. Most skills translate cleanly.

Skill relies on bash/filesystem: ChatGPT Actions can proxy some operations. Gemini CLI has full bash. Perplexity cannot. Hermes has native Python. Document what's lost.

Skill uses Claude-specific features (subagents, worktrees, hooks): These have no equivalent on other platforms. Document as capability delta, don't try to fake them.

User wants a single "universal" version: Partly possible now, and the answer differs by tier. Across Tier 1 the same SKILL.md folder is the universal version — one source of truth, copied to each skills directory, no per-platform variant to maintain. Across Tier 2 it remains impossible; the character limits and configuration surfaces are too different, so produce platform-specific outputs there. Say which half of the answer applies rather than giving a flat no.

Target is a tool not in the matrix: Check its docs for Agent Skills support before assuming translation is needed. The standard's adoption is still expanding, and the default assumption in this skill's v1.0 — that everything outside Claude needs conversion — is now wrong more often than it is right.

Skill uses a bundled script: Tier 1 carries it intact. Confirm the target runtime has the interpreter (Cursor and Codex both shell out; check Python availability rather than assuming), and preserve the execute bit — the installer does this, a manual cp often does not.

Skill Translate v2.0 — July 2026 Tier 1, install unchanged: Claude Code, Codex CLI, Cursor (Agent Skills open standard, agentskills.io) Tier 2, translate: ChatGPT (Custom GPTs + Actions), Gemini (Gems + CLI + API), Perplexity (Spaces), Hermes Agent