mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
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249 lines
14 KiB
Markdown
249 lines
14 KiB
Markdown
# Agent skill
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The published Agent Skill lives in
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[`skills/remove-ai-watermarks/`](../skills/remove-ai-watermarks/). It teaches
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coding agents to drive the `remove-ai-watermarks` CLI on content the user
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generated or edited. It is not a fifth release surface: it ships with this
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repository and updates when the skill files change.
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## Install
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Any agent that speaks the [Agent Skills](https://agentskills.io/specification)
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format:
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```bash
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npx skills add wiltodelta/remove-ai-watermarks
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```
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Claude Code, from this repository as a marketplace:
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```text
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/plugin marketplace add wiltodelta/remove-ai-watermarks
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/plugin install remove-ai-watermarks@remove-ai-watermarks
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```
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SkillsMP indexes public GitHub `SKILL.md` files and does not need a separate
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upload. ClawHub and the Claude community marketplace are explicit publishes;
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see [Release and distribution](release-and-distribution.md#agent-skill).
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## Where the skill can actually be listed
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Most skill catalogs are install registries, not discovery engines. A listing
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without search traffic does not bring people to the CLI or to
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[raiw.cc](https://raiw.cc). Prefer channels that a stranger can find, and keep
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the intended-use boundary in every public description. Official review may
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still reject a watermark-removal listing; that is a risk, not a reason to
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widen the scope.
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Do these in order after the skill is on the default branch.
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1. **GitHub default branch.** Unlocks `npx skills add wiltodelta/remove-ai-watermarks`.
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Cursor, OpenCode, Pi, Codex, and Copilot have no separate skill store; they
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consume this repo or a copied `SKILL.md`.
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2. **SkillsMP.** Aggregates public GitHub `SKILL.md` files. No submit form. A
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search for `remove-ai-watermarks` now returns this skill. Neighboring
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`watermark` hits are PDF-add and detection skills, not removal.
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3. **skills.sh.** No submit form. A row appears on the leaderboard only after
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people run `npx skills add`. The listing is live and has recorded real
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installs; the README install line remains the seed, not a registration.
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4. **Awesome-list PRs.** Hand-curated GitHub lists are how people browse skills
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today. One accurate PR per list, with the scope sentence intact.
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- `ComposioHQ/awesome-claude-skills`: submitted 2026-09-05 as PR 1841
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(Creative & Media); no maturity bar in its contribution rules. Rechecked
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2026-09-11: still open, CI green, no review comments, waiting on the
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list maintainers.
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- `heilcheng/awesome-agent-skills`: submitted 2026-09-09 as PR 483 under
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Community Skills > Media. The skill's three concrete input/output examples
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satisfy the list's working-example requirement. Rechecked 2026-09-11:
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still open; the only check failure is their Vercel deploy authorization,
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which a contributor cannot grant.
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- `VoltAgent/awesome-agent-skills`: DEFERRED. Its CONTRIBUTING rejects
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brand-new skills ("give your skill time to mature and gain users before
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submitting"). The skill now has real installs and shipped releases, but
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adoption remains too small to make the list's maturity claim comfortably.
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- `VoltAgent/awesome-openclaw-skills`: DEFERRED on adoption only. Entries
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are indexed via clawskills.sh, and the ClawHub prerequisite in step 6 is
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now met. The list still requires proven real-world usage. Re-attempt once
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the ClawHub listing shows organic installs.
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5. **Claude community marketplace.** Form at
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[platform.claude.com/plugins/submit](https://platform.claude.com/plugins/submit)
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(individuals) or the claude.ai directory form (Team/Enterprise). Validate
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with `claude plugin validate` first. SUBMITTED 2026-09-07 for Claude Code
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only (strict validation passed; Apache 2.0; description carries the
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scope boundary; platform selection limited to Claude Code because Cowork
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was not tested). Pending review; the team may reach out by email.
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Rechecked 2026-09-11: `platform.claude.com/plugins` is 404, and
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`claude.ai/directory` is the MCP connector catalog, not plugins; a search
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there does not list this skill. Do not open a second submission. The
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official Anthropic marketplace is curated and has no application.
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6. **ClawHub.** `clawhub login` then `clawhub skill publish` from
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`skills/remove-ai-watermarks/`. LISTED 2026-09-09: versions 1.0.5, 1.0.6,
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and 1.0.8, submitted by the `clawhub` job in `distribute.yml` during the
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0.39.0, 0.39.1, and 0.40.0 releases, are public. A green job proves only a
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submission, so read the catalog itself:
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`clawhub search remove-ai-watermarks` returns the row and
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`https://clawhub.ai/api/v1/skills/remove-ai-watermarks` reports
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`latestVersion.version` 1.0.8, while its `/versions` endpoint returns
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1.0.5, 1.0.6, and 1.0.8. The earlier 1.0.3 and 1.0.4 submissions never became
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public and do not appear in that version list, so they were bypassed rather
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than recovered. 1.0.7 was a post-0.39.1 bump that never reached ClawHub.
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The issue that tracked 1.0.3 and 1.0.4, openclaw/clawhub#3643, was closed
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by the reporter on 2026-09-09 once
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1.0.5 went through; nothing upstream was confirmed fixed, and it is the
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fifth report of this shape (#3624, #3466, #3351, #3284), so treat a stalled
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submission as recurring and file a fresh one rather than assuming the
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pipeline is repaired. Release-time publishing is automated (see
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[release-and-distribution.md](release-and-distribution.md)), and the job
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fires only on a published GitHub Release: a skill version bumped after a
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release reaches ClawHub with the next one. Do not publish by
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hand to close that gap. The listing records the license as MIT-0 while
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`SKILL.md` declares Apache-2.0, and that is not a listing error to repair:
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MIT-0 is a platform-wide constant in ClawHub's own client
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(`dist/schema/license.js`, and its version schema accepts only `"MIT-0"`
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or null), so every skill published there is offered under MIT No
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Attribution. Publishing to ClawHub means offering this skill on those
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terms in addition to the repository's Apache-2.0; do not try to edit the
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field, and do not read the mismatch as drift. The public catalog
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already has an add-watermark skill; this is the removal counterpart, framed
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as the user's own content. ClawHub disallows deception, impersonation, and
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fake-engagement install loops.
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7. **OpenAI ChatGPT / Codex plugin directory.** Skills-only plugins are a
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supported submission type at
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[platform.openai.com/plugins](https://platform.openai.com/plugins). This is
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the largest consumer surface that actually reviews listings. It needs Apps
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Management write access, a verified Platform identity, public website /
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support / privacy / terms URLs, starter prompts, and five positive plus three
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negative test cases. Claude marketplace approval does not transfer. Contact
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your OpenAI partner before submitting: this skill's core value requires local
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execution, arbitrary file access, and optional hardware access, which the
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official guide routes through that product-specific review. Convert with
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[Submit your Claude Code plugin to OpenAI](https://developers.openai.com/plugins/guides/submit-claude-plugin).
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8. **AgenticSkills.** SUBMITTED 2026-09-09 as review issue 174 under AI/ML
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Development. The submission carries the user-owned-content boundary and
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links to the repository rather than hosting a separate copy. Rechecked
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2026-09-11: the public index still does not list it (`/skills/remove-ai-watermarks`
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is 404; search for `wiltodelta` returns 0 of 192). Their form promises a
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48-hour review; that window has passed. Issue 174 is not a public GitHub
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issue. Do not open a second submission. Followed up 2026-09-11 through
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their contact form as a listing correction.
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9. **AI Skills Catalog.** SUBMITTED 2026-09-09 as reference 2 under Video Media,
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with Codex as the primary agent and every supported harness marked compatible.
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Rechecked 2026-09-11: the public catalog at skillscatalog.ai shows 0 skills
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from 0 publishers, `/api/featured` returns 401, and `/api/auth/session`
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returns 500, so a stranger cannot confirm the listing. Do not open a
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duplicate while that initial review is pending. Once accepted, treat
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material skill-version updates as manual because the catalog stores
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compatible packages in addition to source metadata and does not promise
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that a GitHub change refreshes those packages. Use the update route
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supplied with acceptance; if none is supplied, contact the catalog or
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resubmit, then verify the live result.
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The conditional update actions for every catalog are part of the canonical
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release checklist in
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[Release and distribution](release-and-distribution.md#agent-skill).
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Do not treat Smithery or other MCP directories as skill catalogs. Do not open
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a second near-identical skill to farm installs. The conversion path that
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matters is: agent cannot run CUDA locally, so it sends the user to raiw.cc.
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## When to edit the skill
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Update `SKILL.md` and `references/` in the same change as any CLI edit that
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alters:
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- command names or routing;
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- extras a command needs;
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- no-signal or exit-code behavior;
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- registered visible mark keys;
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- the CUDA-only invisible-image rule;
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- the intended-use boundary.
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Keep `SKILL.md` under 500 lines. Put flag lists in `references/`. Do not copy
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calibration numbers or retired pipeline names into the skill.
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Write for every harness and a weaker model, not only Claude Opus:
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- third-person description, keywords first, so a truncated listing still matches;
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- a numbered checklist in `SKILL.md`;
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- `scripts/probe.py` for CUDA, ffmpeg, CLI, and installer detection. It measures
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CAPABILITY, not presence: it writes a blank PNG with `zlib` and `struct` and
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runs the installed `visible` on it, because exit `2` is a state only a working
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pixel stack reaches. Reporting a found binary as ready is what sent an agent
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into a missing-cv2 crash on the Homebrew build, which carries no extras. It
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also compares the installed release against `MIN_CLI_VERSION`, so a stale CLI
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is named instead of being reported as a broken flag. Video capability is
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checked separately in the installed CLI's Python environment:
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`video_stacks.pixels` reports `ok`, `missing`, or `unknown`, and
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`video_stacks.invisible` reports `installed`, `missing`, or `unknown`.
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These checks load no weights. An unrecognized launcher leaves video
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guidance unverified rather than inferring readiness from image support;
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- uv, pipx, and pip as installer fallbacks;
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- forward slashes only;
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- no `allowed-tools` (that field is experimental and host-specific).
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Raise `MIN_CLI_VERSION` in `scripts/probe.py` in the same change as any reference
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that names a command, flag or value the previous release lacked. Left behind, it tells an agent its
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CLI is current right before it types an option that build rejects.
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Bump `metadata.version` in `SKILL.md` plus `version` in
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`skills/.claude-plugin/plugin.json` and `.claude-plugin/marketplace.json` when
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the skill instructions change. That version is independent of the PyPI package
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version.
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## Behavior evals
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The deterministic suite proves the skill's prose matches the CLI. It cannot prove
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the only thing a skill exists for: that a model reaches for it on a real request
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and then obeys it. `scripts/skill_eval.py` measures that.
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Each case builds a throwaway project with the skill installed and a recording
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stand-in for the CLI first on `PATH`, runs a headless agent on one user prompt,
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and grades the recorded command trace. Grading is mechanical wherever it can be:
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"did it run `all` on a machine the probe said writes nothing" is a fact in the
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trace, and "did it name an output file that is not on disk" is how a fabricated
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result is caught without asking a model to judge itself.
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```bash
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python3 scripts/skill_eval.py --model haiku --repeat 3
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python3 scripts/skill_eval.py --case visible_ru --model sonnet --out /tmp/eval.json
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```
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Cases live in `data/evaluations/skill/cases.json`; each carries the prompt, the
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scenario the stand-in replays, and the expectations. Run outputs stay outside the
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repository, per `data/README.md`. This never runs in `maintain.sh`: it spends model
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tokens and needs the `claude` CLI.
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Agents are nondeterministic, so the report is a pass RATE per check over `--repeat`
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runs, never one verdict. Weak models are the point: run haiku before opus.
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Four things the first runs found, all on haiku and none visible to the
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deterministic suite:
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- a skill that never triggered on "скажи, видно ли, что она сгенерирована ИИ",
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because the description sold removal and not the question;
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- a finished-looking removal report, with a size table for a file nobody wrote,
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on a machine whose pixel stack was missing;
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- `--mark gemini-sparkle`, a key that does not exist, guessed instead of read;
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- a removal command run to answer a question that only needed `identify`.
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`tests/test_skill_evals.py` keeps the harness honest: the stand-in's exit codes are
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compared against the real CLI where the state is reproducible locally, the grader is
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driven over hand-built traces, and every case is checked for internal consistency. A
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scenario where `identify` names a visible mark that `visible` then cannot find sends
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any agent into a retry loop and measures the case, not the skill.
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## Validate
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```bash
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claude plugin validate .
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claude plugin validate --strict .
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claude plugin validate ./skills
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```
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The suite also checks frontmatter and manifest agreement in
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`tests/test_agent_skill.py`, plus two things a catalog cannot see: that the
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skill's prose still matches the live click application (mark keys, flag choices,
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batch modes, exit codes, extras) and that a machine without the pixel stack gets
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an install hint from the CLI, a caveat from `identify`, and `pixel_stack:
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missing` from the probe.
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