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BD 媒体广告流量市场分析

查询广告投放流量分布与趋势的数据分析技能。支持按行业、地域、媒体（OTT/移动端）、目标受众等多维度分析广告曝光数据，适用于媒体策略评估、竞品投放监测、行业广告趋势研究等场景。

ClawHub Agent Skills author: nonorongrong-design v1.1.2 MIT-0 7 files body ≈ 1 193 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
61
Run on models
none yet
Process rating
D
39/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Obfuscation obf-base64-blob scripts/submit_ad_task.py:28
    Long base64-looking blob (quoted — discussed, not commanded)
    "eyJl…WVu"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/submit_ad_task.py:30
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "I2k6…7Xs"
    quoted

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")

Process rating: all ten parameters 39/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (媒体广告流量市场分析) differs from the folder (mediainsight-ad-traffic-universal)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 45 steps
  • 100Execution cost. Instruction body is 1193 tokens
  • low 12 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 88: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
The skill is a coherent MediaInsight advertising analysis integration, but it creates real remote tasks and stores reusable session credentials on disk by default.
LLM: suspicious (high) · VirusTotal: · 29 May 2026