SKILLEMALL.ai

CD team-composition-patterns

Design optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection. Use this skill when deciding how many agents to spawn for a task, when choosing between a review team versus a feature team versus a debug team, when selecting the correct subagent_type for each role to ensure agents have the tools they need, when configuring display modes (tmux, iTerm2, in-process) for a CI or local environment, or when building a custom team composition for a non-standard workflow such as a migration or security audit.

wshobson/agents Agent Skills author: wshobson MIT 3 files body ≈ 1 883 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Design optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection.

As a process D 35/100 · Unfinished process — References files that are not bundled: ../parallel-feature-development/SKILL.md, ../team-communication-protocols/SKILL.md

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
35/100
Unfinished process
References files that are not bundled: ../parallel-feature-development/SKILL.md, ../team-communication-protocols/SKILL.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../parallel-feature-development/SKILL.md
  • warning missing-ref reference to a missing file: ../team-communication-protocols/SKILL.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: ../parallel-feature-development/SKILL.md, ../team-communication-protocols/SKILL.md
  • 0Tools and files. 2 referenced file(s) missing: ../parallel-feature-development/SKILL.md, ../team-communication-protocols/SKILL.md
  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 38 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1883 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 553: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.