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BF literature-research-pipeline

端到端学术文献检索与下载全流程自动化。当用户请求检索文献、下载论文、查找学术资料、搜索论文，或提到"帮我找XX相关的文献"、"下载这篇论文"、"需要某篇文献"时触发本技能。完整流程：检索 → 推荐 → 多渠道下载 → 科研通常控监控 → 通知 → 进度追踪。

ClawHub Agent Skills author: Oreosofat v1.0.3 MIT-0 4 files body ≈ 1 671 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 33/100 · Will not run — References files that are not bundled: scripts/search.py

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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: scripts/search.py
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

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 · 0

✓ No critical or high findings

Files scanned: 4. 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")
  • warning missing-ref reference to a missing file: scripts/search.py
  • note frontmatter-key unknown frontmatter key "env"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/search.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/search.py
  • 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. 1 mutating operations with no state check
  • 100Steps. 34 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1671 tokens
  • low 12 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 129: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
This skill has a real academic-paper workflow, but it also reuses a logged-in browser session, posts to Ablesci, downloads files, and creates recurring monitoring jobs without strong consent gates.
LLM: suspicious (high) · VirusTotal: · 29 May 2026