SKILLEMALL.ai

AC make-skill

Create a focused workspace Skill from reusable decisions, knowledge, templates, or workflows in the current conversation. Use for /make-skill with a focus argument and requests such as save this workflow or turn this into a skill; do not use for one-off summaries or ordinary file creation.

agentscope-ai/CoPaw Agent Skills author: agentscope-ai Apache-2.0 8 files · 4 scripts body ≈ 2 281 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Create a focused workspace Skill from reusable decisions, knowledge, templates, or workflows in the current conversation.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

GeneratorData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

How to improve

    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: 8. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 19 mutating operations with no state check
    • 40Consistency. Frontmatter name (make-skill) differs from the folder (make-skill-en)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 75Steps. 3 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Execution cost. Instruction body is 2281 tokens
    • low The response is described with custom markup (8 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 290: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 3 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.