SKILLEMALL.ai
GitHub ↗ RU Sign in

BF company-information

企业舆情监测与风险预警技能。基于 FEEDAX API 查询特定上市公司的新闻资讯和舆情动态，支持情感分析（正面/负面/中性）、舆情热度评估、行业分类和关联公司识别。 使用场景：用户查询特定公司新闻、监测企业舆情风险、分析公司口碑、研究上市公司动态、追踪企业负面事件、评估投资风险、了解行业竞争格局等。 触发示例："查询万科最近的新闻"、"宁德时代有什么负面消息"、"比亚迪最新动态"、"恒大集团舆情怎么样"、"腾讯近期报道"、"茅台公司新闻"、"京东负面舆情"、"阿里巴巴最新资讯"等。 支持按公司名称或关键词查询，按情感倾向筛选，返回情感得分、资讯热度、行业分类、关联公司等多维度分析数据。

ClawHub Agent Skills author: longGGGGGG v1.0.0 MIT-0 5 files body ≈ 2 526 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 28/100 · Will not run — References files that are not bundled: scripts/config.json

IntegrationInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
74
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: scripts/config.json
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
This is a copy of a skill from another catalog; the rating counts the canonical one: company-information (ClawHub)

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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration read-dotenv SKILL.md:26
    Reads a .env file
    cat .env
  • low Exfiltration read-dotenv SKILL.md:509
    Reads a .env file
    cat .env | grep FEEDAX_API_KEY

Files scanned: 5. 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: scripts/config.json

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: scripts/config.json
  • 0Tools and files. 1 referenced file(s) missing: scripts/config.json
  • 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. 9 mutating operations with no state check
  • 40Consistency. Frontmatter name (company-information) differs from the folder (companyinformation)
  • 100Steps. 58 steps
  • 100Execution cost. Instruction body is 2526 tokens
  • low 13 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 300: enough signal without eating the budget
  • +4Structure: 49 headings
  • +3Step-by-step instructions: 58 items
  • +4Has examples (14 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill appears to perform the advertised company-news lookups, but it handles API keys in unsafe ways that users should review before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026