SKILLEMALL.ai

AC crewai

Build role-based multi-agent systems with CrewAI. Agents with Role/Goal/Backstory, task design, crew composition (sequential or hierarchical), tool integration, callbacks, and production deployment. Use when orchestrating multi-agent teams or comparing agent frameworks. Do not use this skill for unrelated requests; route to the nearest named specialist.

magnus919/agent-skills Agent Skills author: magnus919 MIT 16 files · 4 scripts body ≈ 1 531 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Build role-based multi-agent systems with CrewAI.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 15. 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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 10 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1531 tokens
    • low No test case covers injection arriving through data

    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
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 355: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 10 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (8 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.