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BF brand-geo-analysis-plus

中国互联网品牌感知监测统一工具。聚合全网热榜追踪（hub）、小红书/抖音/公众号近30天深度讨论研究（cn30）、豆包/Kimi/DeepSeek AI 搜索品牌可见度分析（geo）三个互补模块，帮助品牌方/市场运营/内容创作者从「话题热度—真实口碑—AI 回答」三层视角全面感知品牌。当用户需要研究中国社交媒体热点、分析品牌舆情、对比竞品口碑、分析品牌在 AI 搜索中的表现、做 GEO 优化、追踪全网热点时使用。触发词：品牌感知、舆情监测、社媒研究、热榜聚合、AI 搜索可见度、GEO 分析、跨平台舆情、热点追踪、品牌口碑、品牌竞品对比、社媒热榜。

redfox-data/redfox-community Agent Skills author: redfox-data 17 files body ≈ 2 983 tokens Open the sourcegithub.com↗ analyzed 5 h ago

中国互联网品牌感知监测统一工具。聚合全网热榜追踪（hub）、小红书/抖音/公众号近30天深度讨论研究（cn30）、豆包/Kimi/DeepSeek AI 搜索品牌可见度分析（geo）三个互补模块，帮助品牌方/市场运营/内容创作者从「话题热度—真实口碑—AI…

As a process F 35/100 · Will not run — References files that are not bundled: 链接, HTML文件路径

AnalyzerGitHubMarketingtype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
69
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: 链接, HTML文件路径
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write AskUserQuestion WebSearch

Files scanned: 17. 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: 链接
  • warning missing-ref reference to a missing file: HTML文件路径
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: 链接, HTML文件路径
  • 0Tools and files. 2 referenced file(s) missing: 链接, HTML文件路径
  • 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. 58 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2983 tokens
  • 100Running it twice. No mutating operations
  • 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 276: enough signal without eating the budget
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 58 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.