autopilot
The whole coding loop on one deliberate yes: map, spec, critic-hardened plan, GitHub issues, parallel worktree implementers, fresh-context review loops, one PR…
Prior-art check before you build — does this idea already exist? Takes a project/tool/library idea, reframes it in the vocabularies different communities would use, searches where builders publish (code registries, Show HN, arXiv), traces each match one dependency-layer down to
$ npx -y skills add duthaho/skillhub --skill priorart --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/priorartContext preview
The summary Claude sees to decide when to auto-load this skill.
Prior-art check before you build — does this idea already exist? Takes a project/tool/library idea, reframes it in the vocabularies different communities would use, searches where builders publish (code registries, Show HN, arXiv), traces each match one dependency-layer down to
name: priorart description: >- Prior-art check before you build — does this idea already exist? Takes a project/tool/library idea, reframes it in the vocabularies different communities would use, searches where builders publish (code registries, Show HN, arXiv), traces each match one dependency-layer down to the real incumbent, and returns a locator-backed landscape plus exactly one verdict: Build / Fork X / Contribute to Y / Use Z / Investigate first. Checked ideas persist in out/priorart/checked.md, so re-checking one opens with what changed. Keyless. Use for "does something like X already exist", "has anyone built this", "am I reinventing the wheel", "check prior art before I build" — e.g. "/priorart <idea>". For your existing project vs its peers use scout; for choosing between named options use verdict.
`/priorart <idea>` — check whether the idea already exists `/priorart` — list ideas already checked (from `out/priorart/checked.md`)
Answer one question: **has someone already built this — and what does that mean for whether you should?** The deliverable is one honest verdict with the landscape as its evidence, not a survey. Advisory throughout: it recommends; the human decides what, if anything, gets built.
Read `out/priorart/checked.md` if it exists. If this idea (or a close variant) was checked before, open with **"Since last check"**: re-verify the previous brief's findings (status changes, new arrivals since that date) instead of redoing the whole search. The pipeline below is for ideas not yet in the log.
Restate the idea in one sentence — what it does, who it's for, and the constraint that makes it distinctive — and confirm it with the user. Too vague to restate → ask exactly **one** clarifying question, offering at most 3 example dimensions (it's a question, not a questionnaire).
Before any search, write 6–10 framings of the idea from distinct vantage points: the builder's terms, the end-user's terms, the academic field's terms, the infrastructure/implementation terms, and the adjacent discipline that likely solved this first. Map each planned query to a framing — this is what prevents five queries landing in the same semantic neighborhood and calling it coverage. Most "novel" ideas are existing ideas under a different name; the framings are where that name gets found.
Budget: **≤10 queries for the whole check, with 1–2 held back for Step 4's lead-tracing.** Fan out 2–3 sub-agents grouped by venue class, each briefed with 2–3 framings and an explicit share of the rest (say the numbers; agents without a stated allowance keep searching). Together the briefs cover every vantage point from Step 2 — framings left out of every brief defeat the point of writing them:
Hugging Face for ML.
target users live. Product venues matter because the incumbent may be closed-source; this stays a builder's check — market sizing and business-model analysis are a different job and out of scope.
When the domain has a high-signal venue where serious players cite the incumbent (model cards, RFCs, regulator guidance), check it over generic search.
Every finding returns with a **locator**: the URL plus a fetched signal — last-commit/push date, downloads, release date. A signal that couldn't be fetched is reported as "unknown", never asserted; one repo with real usage beats any listicle.
Read what each direct match is built on: "wraps X", "built on top of W", "official harness for Z" are leads, not background — follow each with a dedicated query. This check fails most often not at finding projects but at stopping one layer too early and crowning a thin wrapper the incumbent. Stop early only when the landscape is clear after 3–4 queries AND at least one of them followed such a lead; at the cap without confidence, say so plainly and report what was found.
Cluster findings into four buckets, **max 3 rows each** — curation, not a dump: **direct matches** · **adjacent solutions** · **partial solutions** · **abandoned attempts** (note when each died and, where findable, why). Each row: Name | Link | Status | Relevance, where the Status cell quotes its fetched locator ("last commit 2026-05", "1.2k dl/mo") or says "unknown" — liveness is looked up, never assumed. Found nothing for a bucket? Leave it empty and say so; **never invent a competitor** — "no direct prior art found, searched: <where>" is a valid, useful result. But treat a clean landscape from same-neighborhood queries as a local minimum, not a green light: three queries returning the same project means a semantic cluster was searched, not the space — vary the framing before believing the blank.
Then extract the **standard patterns** across matches (common architecture, libraries, naming, pricing): the default playbook the user would be competing with or building on. Close with one honest **differentiator paragraph**: name the real differentiator, or say plainly there isn't one — manufactured novelty costs the user their next quarter.
State exactly one of these in the verdict section's heading itself — `## Verdict: <one of the five>` — no hedging (nuance goes after the verdict, not instead of it):
Give Claude Code a memory and make it cite its sources — skills for research, daily work, and shipping code. They started as prompts I kept retyping, so I wrote each one down once. Keyless: no API keys, no signups.
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