AC literature-deep-read-report
This skill should be used when a user provides an academic paper (PDF file, DOI, arXiv link, or title) and asks for a structured deep-read report or literature summary. It extracts the full paper text, quotes exact numbers from the original, and produces a deep, visually structured report with a mechanism diagram, covering background, variables, paradigm/method, task flow, design details, statistical analysis, and main results. Trigger on phrases such as 精读这篇论文, 做一份文献精读报告, 分析这篇文章的方法与设计, 总结这篇研究, summarize this paper, or deep-read report.
This skill should be used when a user provides an academic paper (PDF file, DOI, arXiv link, or title) and asks for a structured deep-read report or…
As a process C 59/100 · Has gaps — weak spots: inputs and preconditions, consistency, progress reporting
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: 3. 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 59/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (literature-deep-read-report) differs from the folder (deepreadtemplate)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 44 steps, 1 vague phrases
- 100Execution cost. Instruction body is 1448 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 542: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 44 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.