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BD clerk-auth

Clerk auth with API Keys beta (Dec 2025), Next.js 16 proxy.ts (March 2025 CVE context), API version 2025-11-10 breaking changes, clerkMiddleware() options, webhooks, production considerations (GCP outages), and component reference. Prevents 15 documented errors. Use when: API keys for users/orgs, Next.js 16 middleware filename, troubleshooting JWKS/CSRF/JWT/token-type-mismatch errors, webhook verification, user type inconsistencies, or testing with 424242 OTP.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 26 files · 1 script body ≈ 5 945 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Clerk auth with API Keys beta (Dec 2025), Next.js 16 proxy.ts (March 2025 CVE context), API version 2025-11-10 breaking changes, clerkMiddleware() options…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGoogle CloudGitHubPlaywrightInfrastructureData and analyticsSecuritytype 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
86/100
safety, quality, tests
Safety 60%
99
Quality 40%
67
Run on models
none yet
Process rating
D
44/100
Unfinished process
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

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token references/jwt-claims-guide.md:49
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "sub": "user…LLY" // Subject (user ID)
    quoted

Files scanned: 26. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5945 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 129, 516, 540, 541): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 44/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 18 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5945 tokens
  • 85Steps. 38 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (12 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
  • -45 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 464: enough signal without eating the budget
  • +4Structure: 51 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (29 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.