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BD trend-radar

키워드 트렌드 신호 탐지 및 Rising/Peaking/Declining 분류 에이전트

ClawHub Agent Skills author: jinu4you v1.0.1 16 files body ≈ 85 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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%
94
Quality 40%
69
Run on models
none yet
Process rating
D
45/100
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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-high-entropy-token package-lock.json:25
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…MpU+oaUdKLpOfmylLMRojGrAgebV+kDtP…HXg+vsA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:103
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…xCA+ORZv…wO5/ywWF…Tag==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:143
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…ibj+tODHI5/+l06Au2Pcriv/Gmet…weg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:155
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…GD3+82K6JgJlm/Y+KI92…no5+4jh9sw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:181
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…8fQ+wE2m…hIQ==",
    detector
  • low Exfiltration read-dotenv README.md:10
    Reads a .env file (quoted — discussed, not commanded)
    1. `cp .env.example .env`
    quoted

Files scanned: 16. 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")

Process rating: all ten parameters 45/100

  • 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
  • 40Consistency. Frontmatter name (trend-radar) differs from the folder (agent-trend-radar)
  • 75Steps. 3 steps
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 85 tokens
  • 100Running it twice. No mutating operations

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 48: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 3 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (1 code blocks)

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

External checks

ClawHub: clean
This is a coherent trend-analysis skill that uses web search and LLM APIs as advertised, with ordinary third-party data-sharing and API-key considerations.
LLM: benign (high) · VirusTotal: · 29 May 2026