agentleFS
alanvaa06alanvaa06/award-craft/skills/verify/SKILL.md

verify

Skill1 starsChanged 3 months agoMITView on GitHub

Mandatory visual verification loop for award-craft landings — screenshot desktop+mobile, critique against the quantitative checklist, fix, re-shoot until verified. Use when craft/elevate reach the verify phase, or standalone after manual edits ("/award-craft:verify"). An edit that ran without errors is NOT done — only verified_ screenshots are done.

188 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use instinct-export, instinct-import and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • TheKREATORSSkill

    instinct-export

    Export instincts from project/global scope to a file

    Also in 3 projects that use this

  • TheKREATORSSkill

    instinct-import

    Import instincts from file or URL into project/global scope

    Also in 3 projects that use this

  • AviadPSkill

    risk-assess

    Assess the risk and blast radius of a proposed code change before implementing it. Evaluates CI impact, framework-wide vs localized scope, rollback path, and identifies blindspots. Use when user says "what's the risk", "is this safe", "assess the impact", "risk assess", "blast radius", or before applying framework-wide or CI-affecting changes. Do NOT use for code quality review (use code-quality) or plan validation (use design-validator).

    Also in 3 projects that use this

  • diego-tobalinaSkill

    build-fix

    Fix build and compilation errors systematically. Run when build fails.

    Also in 6 projects that use this

  • AaravChadhaSkill

    secure

    Security review with a confidence gate - a finding exists only with a concrete exploit scenario and a high/medium/low confidence rating; everything else goes to a worth-hardening list, never inflated. Sweeps five surfaces: auth gates, secrets hygiene, injection and unsafe sinks, unsafe deserialization/crypto/transport, and LLM tool-use trust boundaries. Reports only, never fixes. Use when the user asks for a security review or to check vulnerabilities, secrets, or auth.

    Also in 3 projects that use this

  • ArvorCoSkill

    specify

    Create feature specification from natural language description. Use when starting a new feature or creating a spec. Triggers on: create spec, specify feature, new feature spec.

    Also in 10 projects that use this

  • +1 more from TheKREATORS

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 167 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Ensure production build passes (npm run build) — fix before any screenshots.

    line 11
  2. Distinctive:

    Start the dev server; open the page in the available browser tooling.

    line 12
  3. Very specific:

    Run impeccable's detector once per pass over the changed targets — node <impeccable-base>/scripts/detect.mjs --json <targets>, base dir …

    line 19
  4. Very specific:

    When a comp was approved (docs/comps/), the critique is a SIDE-BY-SIDE: view the comp region and the built region together, the hero and …

    line 24

“Common” is measured: kept by at least 6 in 10 of the 167 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Verify — the loop that makes doctrine real

"Build succeeded" ≠ done. Done = rendered, screenshotted, critiqued, passing.

Protocol

  1. Ensure production build passes (npm run build) — fix before any screenshots.
  2. Start the dev server; open the page in the available browser tooling.
  3. Screenshot set: desktop 1280px AND mobile 375px, at minimum: top of page, each script section, the signature moment mid-animation, the footer. Mobile is evaluated as ITS OWN designed choreography, not shrunk desktop.
  4. Critique each screenshot against ${CLAUDE_PLUGIN_ROOT}/skills/verify/references/checklist.md — enumerate concrete deltas, no vibes. Code checks (grep items) run once per pass. Run impeccable's detector once per pass over the changed targets — node <impeccable-base>/scripts/detect.mjs --json <targets>, base dir resolved in preflight — and fold its findings into the same list (checks 26-27). It catches the mechanical tells this checklist deliberately does not duplicate; do not eyeball them, and do not run it twice in one pass. When a comp was approved (docs/comps/), the critique is a SIDE-BY-SIDE: view the comp region and the built region together, the hero and each section as its own crop at legible scale — never one full-page thumbnail, which hides crude controls, wrong lettering character and flattened material behind a similar section order (checks 24-25).
  5. Fix findings. Re-shoot affected screenshots.
  6. A screenshot that passes is renamed with the verified_ prefix. Loop until the whole set carries the prefix, then run ONE final confirmation pass.
  7. Max 3 iterations per issue. Non-converging issues go to the report as pending — never loop infinitely, never silently drop.
  8. Output: verify report — checks passed/failed, pending issues, screenshot inventory, score against the Awwwards anatomy checklist (${CLAUDE_PLUGIN_ROOT}/skills/direction/references/awwwards-rubric.md).

Reduced-motion pass (mandatory)

Emulate prefers-reduced-motion; screenshot the same set. Full content must be visible and usable with no pin, no scrub, no parallax.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.