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BF TrendScope

舆情趋势洞察技能。根据用户需求自动生成专业的舆情分析报告，包含情感分布、地域分布、关键词分析、媒体分布、时间趋势等多维度分析。触发词：舆情、报告、生成报告、舆情报告、分析报告、品牌分析、市场分析、竞品分析、趋势分析。

ClawHub Agent Skills author: longGGGGGG v1.0.2 MIT-0 5 files body ≈ 4 121 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 26/100 · Will not run — References files that are not bundled: references/domains.json, references/scenes.json, references/media_names.json

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
81/100
safety, quality, tests
Safety 60%
99
Quality 40%
55
Run on models
none yet
Process rating
F
26/100
Will not run
References files that are not bundled: references/domains.json, references/scenes.json, references/media_names.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: TrendScope (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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Exfiltration read-dotenv README.md:35
    Reads a .env file
    cp .env.example .env

Files scanned: 5. 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")
  • warning missing-ref reference to a missing file: references/domains.json
  • warning missing-ref reference to a missing file: references/scenes.json
  • warning missing-ref reference to a missing file: references/media_names.json
  • warning missing-ref reference to a missing file: references/aggregation_types.json
  • warning missing-ref reference to a missing file: assets/area_codes.json

Process rating: all ten parameters 26/100

Will not run. References files that are not bundled: references/domains.json, references/scenes.json, references/media_names.json
  • 0Tools and files. 5 referenced file(s) missing: references/domains.json, references/scenes.json, references/media_names.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. 8 mutating operations with no state check
  • 40Consistency. Frontmatter name (TrendScope) differs from the folder (trend-scope)
  • 70Execution cost. Instruction body is 4121 tokens
  • 100Steps. 45 steps
  • low 11 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 108: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 49 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (9 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: suspicious
This skill mostly matches its report-generation purpose, but it sends report queries and an API key to an unencrypted raw-IP service, so users should review it before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026