BC prompt-optimizer
Prompt Optimizer Skill — AI roundtable debate persona optimizer for OpenClaw shrimp. Creates anthropomorphic personas, debate constraints, and owner position expression for AI agents participating in panel discussions alongside human guests.
Prompt Optimizer Skill — AI roundtable debate persona optimizer for OpenClaw shrimp.
As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected flow-seq-start at node end at line 3, column 58: argument-hint: [new|roast|polish|list-templates|preview] [forum-type] [--name=X… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 52/100
- 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
- 40Consistency. Frontmatter name (prompt-optimizer) differs from the folder (roundtable-prompt-optimizer)
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 4176 tokens
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 12 steps
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)
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 241: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 12 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.