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BC dyagil-oganim-deploy

Develop, deploy, and verify changes to a Vercel + Supabase project (marketing site, CRM, and customer portal). Use whenever your agent needs to ship a code change, run Supabase migrations safely, cache-bust the CDN correctly, verify the deploy with headless Playwright, or apply canonical fixes for known bugs (modal class mismatch, profile duplication, RLS holes, magic-link redirects, FAB stacking).

ClawHub Agent Skills author: dyagil v1.0.0 MIT-0 5 files · 1 script body ≈ 1 999 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSupabasePlaywrightInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
85
Quality 40%
86
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 3

    ✓ No critical or high findings

    Medium and low: 3
    • medium Exfiltration net-credential-use references/playwright-recipes.md:35
      Credential used in a network call (verify the destination is the intended service)
      const gen = await fetch(`${cred.SUPABASE_URL}/auth/v1/admin/generate_link`, {
    • medium Exfiltration net-credential-use references/playwright-recipes.md:142
      Credential used in a network call (verify the destination is the intended service)
      await fetch(`${cred.SUPABASE_URL}/auth/v1/admin/users/${USER_ID}`, {
    • medium Exfiltration net-credential-use references/playwright-recipes.md:155
      Credential used in a network call (verify the destination is the intended service)
      await fetch(`${cred.SUPABASE_URL}/auth/v1/admin/users/${USER_ID}`, {

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 63/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 11 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 19 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1999 tokens
    • low The response is described with custom markup (5 tags): a typed call is more reliable

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 401: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (9 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This deployment skill is coherent, but it gives an agent broad live-production powers over deploys, databases, admin login, and customer accounts without enough guardrails.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026