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Create a new LLP document with the next available number, the NNNN-slug.type.md filename convention, and a scaffolded metadata header — or extend an existing LLP when one already covers the topic.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | llp-create |
| description | Create a new LLP document with the next available number, the NNNN-slug.type.md filename convention, and a scaffolded metadata header — or extend an existing LLP when one already covers the topic. |
| source | ccheever/llp@v0.3.0 |
Author one LLP in a corpus that already exists. Handles numbering, filename, and the metadata scaffold so the author can focus on content.
Invoke as /llp-create <title>, or bare and the skill asks.
"Capture this decision" / "write an LLP for this" — during or after a design conversation.
Grep the **Systems:** and **Related:** headers across llp/ and propose extending an existing LLP over creating a new one when the topic is already covered.max(existing) + 1, zero-padded — scanning the whole llp/ tree including subdirectories and tombstones/. Numbers are never reused and never invented.NNNN-slug.type.md with the lowercased type matching the header's **Type:**, and start every new LLP as Draft.Recipe (advisory) — next number:
ls llp | grep -oE '^[0-9]{4}' | sort -n | tail -1(+1); for nested trees globllp/**/[0-9]*.mdand excludereviews/. Slug: lowercase, non-alphanumerics →-, collapse repeats, keep it under ~6 words. Type cues: proposal →rfc; requirements →spec; settled choice →decision; steps →plan; teaching →explainer; always/never →principles; how-to →guide; bug →issue; findings →research. Scaffold sections: Summary · Motivation · Design · Open questions (Decisions use Context/Options/Decision/Consequences; Research uses Findings/Confidence).
A new Draft LLP with a complete metadata header (Type, Status, Systems, Author, Date; Related: where relevant) — plus an offer to draft the body from the current conversation. Confirm the assigned number and path back to the user.
llp-adopt.llp-review, scaled to stakes (LLP 0005).Author-invoked dual-family refine loop for one or more Draft/Review LLPs — each round, two fresh mutually-blind reviews from different model families, orchestrator revision, verdict-lined artifacts — until both families mark the same revision READY, a delta round finds no MATERIAL concern in pre-existing text across families, or a bounded stop rule escalates to the author. Use when the user invokes /llp-super-refine or asks to refine an LLP until independent models agree it is ready.
Keep an LLP corpus in sync with its code. Detects code/doc drift, validates @ref annotations interactively, checks provenance tags, and proposes reconciliations, ref repairs, and status changes. Modes — pre-pr, audit, reconcile, retire-proposal. Proposes; never applies.
Before editing a subsystem, file, or starting a task, assemble the governing LLP context — read the root LLP, follow the @ref annotations on the code in scope, and find the LLPs covering the relevant systems. Produces a compact context pack of the constraints a change must respect. Read-only.
Run the LLP 0005 review loop for an LLP document — orchestrate reviews from other model families, write one provenance-tracked artifact per review actually received under llp/reviews/, and never fabricate a review or accept on the author's behalf. Review intensity scales with stakes; the author decides when it's enough.
Take one or more tasks (Linear tickets, ticket files, accepted LLPs, free text) end to end — plan lanes, implement in run-namespaced worktrees, integrate on a run branch, verify and review the exact integrated commit, deliver per repo policy (direct push by default), and clean up without destroying recoverable work. Use when the user invokes /llp-ship or hands over tasks to be implemented and shipped.
Bring LLP to a repository and keep its installed skills current — the single entry point for "set up LLP here" and "update the LLP skills". Scaffold mode (fresh structure), retrofit mode (survey the codebase, draft a provenance-tagged root LLP, propose an adoption plan), install step (copy skills from a tagged release with a receipt), and update mode (verified, diff-approved skill updates).