SKILLEMALL.ai

AD Coding Team Setup v2.1 — Flexible Multi-Agent Development Team

The wizard guides you through: 1. Team naming — Give your team a name (supports multi-team setup) 2. Select roles — Choose 2–10 from 10 preset roles or add custom ones 3. Assign models — Auto-detec...

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 3 416 tokens Open the sourcegithub.com analyzed 2 d ago

The wizard guides you through: 1.

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 43/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (Coding Team Setup v2.1 — Flexible Multi-Agent Development Team) differs from the folder (coding-team-setup)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 85Steps. 86 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 3416 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (4 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -220 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 200: enough signal without eating the budget
    • +4Structure: 43 headings
    • +3Step-by-step instructions: 86 items
    • +4Has examples (18 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.