AC google-scholar-paper-finder
Use when the user wants to find more relevant academic papers through real-time Google Scholar retrieval with google-scholar-search-mcp, expand search terms from a research topic or seed paper, screen papers by venue quality, or return a ranked literature table with title, authors, year, journal/conference, impact factor, JCR/CAS/CCF/EI/core tags, citations, download/access links, source evidence, and recommendation reasons. Triggers include "Google Scholar 找论文", "google-scholar-search-mcp", "实时搜索论文", "找更多相关论文", "高质量论文筛选", "影响因子", "CCF", "EI", "CSSCI", "北大核心", "文献检索", "参考文献滚雪球", and "返回论文表格".
Use when the user wants to find more relevant academic papers through real-time Google Scholar retrieval with google-scholar-search-mcp, expand search terms…
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 12. 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 55/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 8 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 76 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1787 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
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 599: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 76 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.