BB cost-optimizer
Smart cost optimization skill for OpenClaw. Reduces API costs by 70-97% through intelligent model routing, session management, output efficiency, and free model usage. Includes 29 executable scripts for auditing, monitoring, backup/restore, health checks, and automated reporting. Walks user through setup on first activation.
As a process B 65/100 · Nearly there — weak spots: when it triggers, consistency, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 41. 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") - warning
body-longSKILL.md body ≈ 6848 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 65/100
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (cost-optimizer) differs from the folder (open-optimise)
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6848 tokens
- 100Steps. 140 steps
- 100Failures and branches. 20 branches, has a failure section
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 17 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
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)
- -42 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 326: enough signal without eating the budget
- +4Structure: 65 headings
- +3Step-by-step instructions: 140 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
- +3All 29 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.