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AB tencent-cloud-rum-2.1

Query Tencent Cloud RUM data, analyze Web performance (LCP/FCP/WebVitals), troubleshoot JS/Promise errors, analyze API latency & error rates, diagnose slow static resource loading, and view PV/UV. Supports RUM-APM correlation. Not for: backend-only performance, native mobile performance, or non-Tencent Cloud RUM platforms.

ClawHub Agent Skills author: lauraytwu v0.1.3 MIT-0 7 files · 1 script body ≈ 3 123 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 70/100 · Nearly there — weak spots: consistency, running it twice

AnalyzerInfrastructureSoftware developmenttype 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
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
B
70/100
Nearly there
Running it twice w 4
30
Consistency w 8
40
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 0

✓ No critical or high findings

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 70/100

  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (tencent-cloud-rum-2.1) differs from the folder (tencent-cloud-rum-skill)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 81 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Execution cost. Instruction body is 3123 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 top-level sections: this looks like several domains in one skill
  • 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
  • -215 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 324: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 81 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a coherent Tencent Cloud RUM analysis skill, but it requires sensitive cloud credentials and can access detailed user telemetry.
LLM: benign (high) · VirusTotal: · 29 May 2026