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AB wos-feishu-literature

Use when the user mentions wos, WOS, WoS, or Web of Science and wants topic-based literature search, Shenzhen University library login, paper screening, abstract extraction, and writing results into a Feishu Base/multidimensional table via local lark-cli. Also use when the user wants a reusable WOS-to-Feishu workflow, academic literature collection, SSCI-focused retrieval, or a 中文文献检索到飞书多维表格流程.

ClawHub Agent Skills author: SamadhiFire v1.0.1 MIT-0 4 files body ≈ 1 146 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 70/100 · Nearly there — weak spots: result and completion, consistency, running it twice

IntegrationInfrastructureResearchtype 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
B
70/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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: 4. 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 70/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (wos-feishu-literature) differs from the folder (zijiyong)
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 46 steps
    • 100Failures and branches. 6 branches, has a failure section
    • 100Execution cost. Instruction body is 1146 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

    • +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 397: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 46 items
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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

    External checks

    ClawHub: clean
    This skill is a disclosed Web of Science-to-Feishu workflow that can use authenticated services and update Feishu tables, but its artifacts require user confirmation and show no hidden code or credential theft.
    LLM: benign (high) · VirusTotal: · 29 May 2026