AC notes
Manage Cornell Method notes as Markdown files using the bundled cornell.py CLI script. Use this skill whenever the user wants to take notes, create a new note, view, list, search, edit, or delete Cornell-style notes. Trigger on phrases like "take a note", "create a note", "show my notes", "list notes", "search notes", "open my note on X", "delete note", "edit my note", or any request involving personal notes or note-taking. Also trigger when the user says things like "save this as a note" or "what did I write about X". Always prefer this skill over ad-hoc solutions for anything note-related.
As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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 50/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (notes) differs from the folder (cornell-notes)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 85Steps. 16 steps, 1 vague phrases
- 100Execution cost. Instruction body is 689 tokens
- 100Progress reporting. Reports progress
- low The response is described with custom markup (6 tags): a typed call is more reliable
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 10 example trigger phrases
- +3Description length 599: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.