AC research-compiler
This skill should be used when the user wants to compile and organize scientific research project outcomes. It guides WorkBuddy through a structured five-phase workflow: (1) intake and topic analysis, (2) building a master framework for all outcomes and seeking user confirmation, (3) splitting each outcome into blocks and enriching content with existing materials plus web research, (4) merging all blocks into a complete document, and (5) outputting a final Word (.docx) file. Language is concise, innovation-focused, and free of filler text. Frameworks follow standard academic formats (research report, policy brief, technical standard, monograph, etc.) sourced from authoritative templates. Trigger phrases include "汇总科研成果", "整理课题成果", "科研课题汇编", "帮我整理研究成果", "生成研究报告", "课题成果Word", "科研成果汇编".
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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: 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 59/100
- 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
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 34 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1376 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
- +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
- +5Description quotes 7 example trigger phrases
- +3Description length 794: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.