AC researchclaw
OpenClaw integration for AutoResearchClaw - fully autonomous research from idea to paper. Use when user requests academic research, literature review, or paper writing such as: (1) "Research [topic]", (2) "Write a paper about [topic]", (3) "Find literature on [topic]", (4) "Analyze [research question]", (5) "Generate academic paper from [idea]". Auto-installs AutoResearchClaw, configures LLM backend, runs 23-stage pipeline, returns LaTeX paper + experimental code + real citations.
As a process C 58/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
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: OpenClaw integration for AutoResearchClaw - fully autonomous resea… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 58/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (researchclaw) differs from the folder (autoresearchclaw-integration)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 63 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1532 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
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)
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 485: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 63 items
- +3Output format is stated explicitly
- +4Has examples (13 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.