| name | skill-to-prompt-porter |
| description | Port Claude Code skills into standalone prompts for external LLMs (Grok, ChatGPT, Gemini, NotebookLM) — methodology extraction, infrastructure stripping, modality adaptation, source-grounded adaptation |
| license | MIT |
| metadata | {"version":"1.1.0","hermes":{"tags":["Skills","LLM","Portability"],"related_skills":["skill-pattern-alignment","skill-decomposition-methodology"]}} |
Porting Skills to Standalone LLM Prompts
Core Principles
- Methodology is portable, infrastructure is not: Decision trees and quality standards transfer. Git, MCP, wiki-links do not.
- Preserve the quality floor: Non-negotiable standards are the skill's real value — never drop them to simplify.
- Adapt modality, not methodology: If original reads files, ported prompt processes screenshots or pasted text. Analysis stays identical.
- Self-contained means self-contained: Works with zero context about your notes system or specific tools.
Three-Layer Separation
| Layer | Action | Contents |
|---|
| Methodology (KEEP) | Port entirely | Decision trees, quality standards, forbidden patterns, templates, grouping heuristics |
| Infrastructure (STRIP) | Remove completely | Git ops, MCP calls, wiki-link verification, README updates, archival, file paths, batch processing |
| Modality (ADAPT) | Transform for platform | Input/output interfaces |
Modality Adaptation Table
| Original (Claude Code) | Adapted (External LLM) |
|---|
Read tool on .md files | Screenshot, pasted text, URL |
Write tool to create files | Raw markdown in chat |
Grep/Glob for existing notes | User handles deduplication |
Wiki-links [[Note Name]] | Plain text or omit |
| Archival workflow | Omit entirely |
Source-Grounded Platforms (NotebookLM)
The Modality Adaptation Table above targets chat LLMs (Grok, ChatGPT, Gemini) that generate from model knowledge — port quality standards to constrain generation. Source-grounded tools (NotebookLM) answer only from uploaded sources — adapt differently:
| Original (Claude Code) | Adapted (NotebookLM) |
|---|
| Resource suggestions per item | "Best source in this notebook" per item |
| Analysis from model knowledge | Require a source citation on every output node |
| Quality floor vs hallucination | Instruct: mark uncovered items "GAP — not in sources", never invent to fill |
| Interactive clarification steps | Inline placeholders the user fills ([TOPIC], [LEVEL]) |
The GAP rule has a side benefit: the output doubles as a coverage audit of the notebook's source bundle.
Added 2026-06-07 from porting skill-tree-generator to NotebookLM.
7-Step Porting Workflow
- Read source skill — classify every section as Layer 1/2/3. Pull in any files the SKILL.md points to (
references/, scripts/, assets/); a port that omits them drops content the skill declares required. Scrub before porting: source content going into a third-party LLM must carry no secrets, internal hostnames, or private-infra names, even inside Layer-1 methodology kept verbatim.
- Extract decision tree — core analysis logic transfers verbatim
- Extract quality standards — consolidate all REQUIRED/CRITICAL/FORBIDDEN into one section
- Extract forbidden patterns — port ones that apply without infrastructure
- Build output template — strip tool-specific fields, replace with platform equivalents
- Add input handling — screenshot (transcribe first, describe visuals, flag incomplete), pasted text (accept as-is, ask for source), URL (fetch and extract metadata)
- Write prompt document — single markdown file.
- Verify the floor survived — before declaring done, list every REQUIRED/CRITICAL/FORBIDDEN item from the source and confirm each appears in the port. If the target platform has a length ceiling (Custom GPT ~8k chars, Gem limits) and the source overflows it, cut illustrative examples and prose FIRST; never drop a quality-floor rule to fit — if the floor itself won't fit, say so rather than shipping a silently weakened port.
# [Skill Name] Prompt
> **Usage**: [One-line instruction]
---
## System Prompt
[Instructions: input handling + methodology + output template + quality standards + forbidden patterns]
---
*Methodology adapted from [skill name].*
Key Rules
- Never keep wiki-link syntax on platforms where it's meaningless
- Collapse multi-phase workflows into single-pass: analyze input, produce output
