AC deep-research-zh
中文深度调研工具。基于 academic-deep-research fork，针对中文场景优化：自动生成中文 PDF（内嵌样式、容错降级）、Tavily 搜索集成、飞书自动交付。适用于竞品分析、行业调研、政策研究等需要严格方法论的场景。使用 native OpenClaw 工具（web_search, web_fetch, sessions_spawn）进行多源调研。
As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6386 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 59/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 12 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6386 tokens
- 85Steps. 215 steps, 2 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 18 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 186: enough signal without eating the budget
- +4Structure: 74 headings
- +3Step-by-step instructions: 215 items
- +4Has examples (8 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
This research skill is useful and mostly coherent, but it under-discloses online behavior and requires automatic report saving and Feishu delivery without a final user approval step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026