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BF delonix-web-intelligence

德胧AI龙虾军团外网信息舆情采集工具 v1.0。整合 miaoda-web-search（网页搜索摘要）+ AutoCLI（50+平台深度采集）+ 飞书卡片推送 + 定时自动化。 触发词：舆情、情报、网情、监控、搜索、行业动态、竞争对手动态、竞品分析、外网信息采集 使用场景： - 酒店行业舆情监控（华住/锦江/亚朵/德胧） - 竞品动态追踪 - 行业趋势分析 - 危机公关预警 - 每日行业报告自动生成

ClawHub Agent Skills author: Chaoliuzhu v1.0.1 MIT-0 4 files · 1 script body ≈ 1 579 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 35/100 · Will not run — References files that are not bundled: url

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
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: url
  • note frontmatter-key unknown frontmatter key "override-tools"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 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
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1579 tokens
  • 100Running it twice. No mutating operations
  • low 11 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 204: enough signal without eating the budget
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
This skill is a disclosed hotel-industry web monitoring and report-pushing workflow, but users should review its broad triggers, optional third-party tools, and Feishu delivery settings before enabling automation.
LLM: benign (medium) · VirusTotal: · 29 May 2026