SKILLEMALL.ai
RU Sign in

BD pdf-literature-parser

从学术论文 PDF 中提取元信息，包含标题、关键词、摘要，输出结构化 JSON。适用于文献整理、引用格式整理、论文信息快速提取。

ClawHub Agent Skills author: Y-EGG v1.0.0 MIT-0 3 files body ≈ 65 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 42/100 · 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
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
51
Run on models
none yet
Process rating
D
42/100
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 · 0

✓ No critical or high findings

Files scanned: 3. 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")
  • note frontmatter-key unknown frontmatter key "command"
  • note frontmatter-key unknown frontmatter key "inputs"
  • note frontmatter-key unknown frontmatter key "output"

Process rating: all ten parameters 42/100

  • 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
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 75Steps. 3 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 65 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 64: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -15SKILL.md body under 300 characters: nearly empty
  • +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: 51.

External checks

ClawHub: suspicious
This PDF parser is useful, but it sends PDF text to Moonshot's AI API without clearly telling users in the skill instructions.
LLM: suspicious (high) · VirusTotal: · 29 May 2026