SKILLEMALL.ai

AB brightdata-research

Use when the user asks to batch-search candidates, verify public web evidence, dedupe results, and organize them into Feishu/Lark docs. Use especially for requests like "继续搜更多并追加到飞书", "帮我批量找一批候选并整理到飞书", "搜索+抓取+汇总+落文档/落表", "帮我调研一批XX平台", "扩展候选池", even if the user does not explicitly name this skill. Also use when the user says "检查飞书文档里有没有重复" or "去重" in the context of a research document — this skill covers dedup-and-cleanup as a sub-workflow. Do NOT use for: single-page summaries, one-off Q&A, pure code tasks, or tasks that don't involve batch research + structured output.

ClawHub Agent Skills author: 16Miku v1.0.0 MIT-0 11 files body ≈ 1 259 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 69/100 · Nearly there — weak spots: result and completion, progress reporting

AnalyzerSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 80 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1259 tokens
    • 100Running it twice. No mutating operations
    • medium 9 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 577: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 80 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.

    External checks

    ClawHub: suspicious
    The skill mostly matches its advertised research-to-Feishu workflow, but it also allows automatic global installs, adding external skills, and git repository changes without enough user control.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026