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AB agent-team-workflows

Universal multi-agent workflow orchestration using Claude Code Agent Teams. Use when user asks to run a team workflow, create an agent team, or coordinate parallel work across multiple teammates — for any domain (software, content, data, strategy, research, etc.).

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 435 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Universal multi-agent workflow orchestration using Claude Code Agent Teams.

As a process B 65/100 · Nearly there — weak spots: result and completion, failures and branches, consistency

ProcedureAI and agentstype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
65/100
Nearly there
Failures and branches w 10
0
Running it twice w 4
30
Result and completion w 14
40
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: 4. 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 65/100

    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 6 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (agent-team-workflows) differs from the folder (claude-agent-team-workflows)
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 32 steps
    • 100Execution cost. Instruction body is 2435 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 264: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 32 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.