AB llm-benchmark-analyst
search and analyze llm benchmark results within a fixed benchmark universe, then produce evidence-based model strength and weakness reports or domain-leader summaries. use when comparing a model across benchmarks, ranking the best models by domain, explaining what a benchmark measures, checking predecessor-vs-current progress, or writing benchmark reports that must prioritize exact model version, evaluation date, benchmark variant, score semantics, sub-scores, and benchmark defect warnings. works with browser, web, and multimodal extraction for text, table, canvas, or image-only leaderboards.
As a process B 72/100 · Nearly there — weak spots: inputs and preconditions
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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 72/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 50When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 5 branches
- 85Steps. 79 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1735 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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)
- +1No license
- +2Single-language instructions
- +3Description length 599: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 79 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.