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CB bundle-builder

Render accumulated workflow state from memory into a valid Agent Skills bundle directory for workflow-architect, with sub-skills, manifest, decision map, and optional kanban board. Loaded after the interviewer or observer achieves convergence.

magnus919/agent-skills Agent Skills author: magnus919 MIT 3 files body ≈ 3 408 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Render accumulated workflow state from memory into a valid Agent Skills bundle directory for workflow-architect, with sub-skills, manifest, decision map, and…

As a process B 77/100 · Nearly there — weak spots: when it triggers, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
B
77/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 77/100

  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 14 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 36 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 5 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3408 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (8 tags): a typed call is more reliable
  • medium 6 test cases, all positive: not one "should refuse" or "should ask first"
  • low No test case covers injection arriving through data

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)
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 243: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 36 items
  • +3Output format is stated explicitly
  • +4Has examples (16 code blocks)
  • +1License stated

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