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AB todokan-review-loop

Process Todokan task and thought boards with a review-loop workflow. Use when a task enters doing and the agent should pick it up, read latest comments, respond to the newest comment with a high-quality context-aware reply, add an execution update comment, and move the task back to done (Review). Use for recurring polling/cron automation with Todokan MCP.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 3 279 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Process Todokan task and thought boards with a review-loop workflow.

As a process B 75/100 · Nearly there — weak spots: when it triggers, inputs and preconditions

ProcedurePersonal productivityAI 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
B
75/100
Nearly there
When it triggers w 12
20
Inputs and preconditions w 11
30
Result and completion w 14
60
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 75/100

    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 140 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3279 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +3Description length 357: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 140 items
    • +3Output format is stated explicitly

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