AC self-improving-business
Captures business administration issues, policy gaps, KPI misalignment, decision delays, handoff failures, and stakeholder misalignment to improve operational decision quality. Use when: (1) approval or execution bottlenecks appear, (2) KPI definitions conflict across teams, (3) process governance is inconsistent, (4) SLA commitments are missed or trending late, (5) budget variance requires triage, (6) vendor or cross-team handoff breaks, (7) policy documentation drifts from actual practice.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6030 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 62/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 70Execution cost. Instruction body is 6030 tokens
- 100Steps. 126 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 22 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 496: enough signal without eating the budget
- +4Structure: 51 headings
- +3Step-by-step instructions: 126 items
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (2 of 3)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.