AB autoresearch
Autonomous experiment loop for AI agents. Use when the user wants to run systematic experiments — optimizing hyperparameters, searching for better configurations, ablation studies, or any task where an agent should iteratively try changes, measure results, and keep or discard based on a metric. Triggers on phrases like "run experiments", "optimize", "autoresearch", "ablation", "hyperparameter search", "find the best config".
As a process B 66/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice
The same skill appears in 2 more places: ClawHub, ClawHub
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: 3. 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 66/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 9 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 85Steps. 47 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Failures and branches. 4 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2446 tokens
- 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 428: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.