agentleFS
DojoGenesisDojoGenesis/openclaw-plugin/skills/static-tool-verify/SKILL.md

static-tool-verify

Skill0 starsChanged 9 months agoMITView on GitHub

Browser-verify a self-contained single-page tool before shipping — start it via .claude/launch.json, exercise the core mechanic, assert zero console errors, screenshot, and catch the content/logic bugs (seasonal incoherence, misleading severity labels, dead interactions) that pass a syntax check but fail a human. Use when "verify the tool", "check the page before deploy", "browser-test this POC", or as Phase 3 of poc-tool-forge. Never trust an agent's self-report of "done".

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

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

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

    If real-data: spot-check that the inlined DATA matches the source snapshot (a couple of values), to confirm nothing was paraphrased or …

    line 20
  2. Very specific:

    Use the preview MCP (preview_*), driven off .claude/launch.json:

    line 24
  3. Distinctive:

    Look for output that is *valid* but *wrong*:

    line 36
  4. Distinctive:

    Dead interactions: do "see also" / regenerate / toggles actually do something?

    line 41
  5. Distinctive:

    When you find one, fix the source (root cause, per the debugging protocol), reload, re-assert — then move on.

    line 43

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

OpenClaw Integration: This skill is invoked by the Dojo Genesis plugin via /dojo run static-tool-verify. The agent receives project context automatically via the before_agent_start hook. Use dojo_get_context for full state, dojo_save_artifact to persist outputs, and dojo_update_state to record phase transitions and decisions.

static-tool-verify — prove it works before it ships

The discipline that caught real bugs this session. An agent reporting "verified, HTTP 200, zero errors" is not verification — confirm it yourself. Part of poc-tool-forge; applies to anything house-poc-builder produces (and any static single-page tool).

Step 1 — Structural / syntax (cheap, do first)

  • File exists + non-trivial size; balanced <script>/<style> tags.
  • Extract the inline JS and node --check it (catches the syntax errors that would white-screen the page).
  • If real-data: spot-check that the inlined DATA matches the source snapshot (a couple of values), to confirm nothing was paraphrased or invented.

Step 2 — Real browser pass (the part that matters)

Use the preview MCP (preview_*), driven off .claude/launch.json:

  1. Register a launch entry if missing: {"name":"<slug>","runtimeExecutable":"python3", "runtimeArgs":["-m","http.server","<port>","--directory","trespies-poc/<slug>"],"port":<port>}.
  2. preview_start the slug → get the serverId.
  3. Exercise the core mechanic, don't just load the landing: set the input / click the real generate button via preview_eval (example chips often only prefill — trigger generation explicitly), then assert the artifact rendered (body length jumps, expected sections + SVG element counts present).
  4. preview_console_logs level:error → must be empty.
  5. preview_screenshot → eyeball the actual render (layout, the hero element, the disclaimer banner).

Step 3 — Catch what a syntax check can't (this is the point)

Look for output that is valid but wrong:

  • Coherence: does generated vocab contradict the inputs? (A "Summer" almanac that cites a "March" driver — vocab pool wasn't season-filtered.)
  • Honesty of framing: does a label overstate reality? (A public-health page labeling a quiet summer "HIGH" because severity was banded on cross-state rank instead of absolute %-of-peak.)
  • Dead interactions: do "see also" / regenerate / toggles actually do something?
  • Guardrail present: disclaimer banner + footer actually render in the artifact, not just the source. When you find one, fix the source (root cause, per the debugging protocol), reload, re-assert — then move on.

Step 4 — Hand off proof

Screenshot(s) of the working mechanic are the deliverable to the operator. Then proceed to cf-pages-trespies-deploy.

Notes

  • Foreground sleep is blocked; to wait on something, use a background poll or a preview_eval reload with a short settle, then re-query.
  • Kill stray python3 -m http.server you started manually; launch.json-managed servers are fine to leave.

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.