CD build
Fully automate a coding task with make-plan, do, and babysit.
Promises full automation of coding tasks via plan-do-babysit pipeline. Files contain one instruction at 48 tokens, no scripts, no critical errors. Quality score of 46 out of 100 signals modest scope: the logic exists, but detail work is sparse.
Checks found no blocks or safety issues (100 score), yet process score of 47 hints at incomplete development. No model runs, no sandbox tests. Compatible across all major platforms from Claude to DeepSeek. Install if you need a basic automation skeleton and don't mind patching it yourself; for production work—underwhelming.
Fully automate a coding task with make-plan, do, and babysit.
As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 75Steps. 3 steps
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 48 tokens
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)
- +3Description length 61: 120–800 characters recommended
- +4Structure: 1 headings, hard to scan
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -15SKILL.md body under 300 characters: nearly empty
- +1No license
- +2Single-language instructions
- +3Step-by-step instructions: 3 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 46.