AA gstack-openclaw-office-hours
Product interrogation with six forcing questions. Two modes: startup diagnostic (demand reality, status quo, desperate specificity, narrowest wedge, observation, future-fit) and builder brainstorm. Use when asked to brainstorm, "is this worth building", "I have an idea", "office hours", or "help me think through this". Proactively use when user describes a new product idea or wants to think through design decisions before any code is written.
As a process A 82/100 · Runs to the end — weak spots: when it triggers
How to improve
- 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: 2. 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: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Product interrogation with six forcing questions. Two modes: start… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 82/100
- 20When it triggers. No condition that starts the skill
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 10 branches
- 70Execution cost. Instruction body is 4177 tokens
- 100Tools and files. No external tools needed
- 100Steps. 74 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +4Description does not say when NOT to use the skill (false activations)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 446: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 74 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.