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AC influencer-research

Automated KOL/influencer research across platforms. Use when user needs influencer lists for any niche (ADHD, travel, beauty, DTC, tech, etc.) in any region. Triggers on "find influencers", "KOL research", "influencer list", "creator database", or any request to compile influencer data for outreach or partnerships.

ClawHub Agent Skills author: Lucius Pang v1.0.2 MIT-0 2 files body ≈ 1 413 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

ProcedureSoftware developmentSales and CRMInfrastructuretype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (influencer-research) differs from the folder (phy-influencer-research)
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 1413 tokens

    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 4 example trigger phrases
    • +3Description length 316: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This skill is a coherent influencer-research helper that searches public web sources and creates a local spreadsheet, with no evidence of hidden execution, credential use, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: benign · 28 May 2026