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AF team-composition-analysis

This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 2 404 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity…

As a process F 48/100 · Will not run — References files that are not bundled: references/compensation-benchmarks.md, references/equity-calculator.md, examples/seed-stage-hiring-plan.md

AnalyzerPeople and hiringData and analyticsFinancetype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: references/compensation-benchmarks.md, references/equity-calculator.md, examples/seed-stage-hiring-plan.md
Tools and files w 18
0
Result and completion w 14
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/compensation-benchmarks.md
  • warning missing-ref reference to a missing file: references/equity-calculator.md
  • warning missing-ref reference to a missing file: examples/seed-stage-hiring-plan.md
  • warning missing-ref reference to a missing file: examples/org-chart-evolution.md

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: references/compensation-benchmarks.md, references/equity-calculator.md, examples/seed-stage-hiring-plan.md
  • 0Tools and files. 4 referenced file(s) missing: references/compensation-benchmarks.md, references/equity-calculator.md, examples/seed-stage-hiring-plan.md
  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 154 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2404 tokens
  • low 14 top-level sections: this looks like several domains in one skill

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 5 example trigger phrases
  • +3Description length 240: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 154 items
  • +4Has examples (6 code blocks)

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