技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 29 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：amdf01-debug/sw-autoresearch
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill's instructions, metadata, and required resources are internally consistent with an autonomous iterative research assistant and do not request unexpected credentials or installers.
目的
Name/description (autoresearch, iterative verification) matches the SKILL.md loop. The skill requests no binaries, env vars, or installs that would be unrelated to performing research.
说明范围
SKILL.md gives an open-ended methodology (search/analyse/synthesise/verify) and requires verification from multiple sources and iteration caps (max 10). The instructions are high-level and intentionally leave the agent discretion about how to search and which sources to use — this is coherent for a research skill but gives the agent broad authority to query external sources or tools. There are reasonable guardrails (iteration limit, require di…
安装机制
Instruction-only skill with no install spec and no code files; nothing is written to disk or downloaded. This is the lowest-risk install profile.
证书
No environment variables, credentials, or config paths are requested. The lack of requested secrets is proportionate to a research-oriented skill.
持久
always is false and the skill is user-invocable; the skill can be invoked autonomously by the agent (platform default) but does not request elevated or persistent privileges. Combined with no requested credentials, the privilege footprint is minimal.
综合结论
This skill appears coherent and low-risk because it is instruction-only and requests no credentials. Before installing or enabling autonomous invocation, consider: 1) Review what tools your agent has (web browsing, external API access, filesystem access) — the skill's instructions allow the agent to use whatever search/synthesis tools it already has. 2) If you don't want the agent to access the web or local files, disable those capabilities or…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Autoresearch Loop」。简介：Conducts autonomous, iterative research by defining goals, generating hypothese…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/amdf01-debug/sw-autoresearch/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
# Autoresearch Skill
## Trigger
Autonomous goal-directed iteration — agent modifies, verifies, keeps/discards, and repeats.
**Trigger phrases:** "research this thoroughly", "autonomous research", "iterate until complete", "deep dive", "autoresearch"
## Core Loop
Inspired by Karpathy's autoresearch methodology:
```
1. Define goal and success criteria
2. Generate hypothesis or approach
3. Execute (search, analyse, synthesise)
4. Verify result against criteria
5. If criteria met → keep result, move to next
6. If criteria not met → modify approach, retry
7. Repeat until all criteria satisfied
```
## Implementation
```markdown
# Autoresearch: [Topic]
## Goal
[What you're trying to find/prove/analyse]
## Success Criteria
- [ ] [Criterion 1 — specific and measurable]
- [ ] [Criterion 2]
- [ ] [Criterion 3]
## Iteration Log
### Attempt 1
- Approach: [what was tried]
- Result: [what was found]
- Assessment: [met criteria? why/why not?]
- Next: [what to try differently]
### Attempt 2
...
## Final Output
[Synthesised result that meets all criteria]
```
## Rules
- Always define success criteria BEFORE starting research
- Maximum 10 iterations per research question (prevent infinite loops)
- Each iteration must try a DIFFERENT approach (no repeating failed strategies)
- Log every attempt — the failures are as valuable as the successes
- Verify findings from multiple sources before accepting
- Be explicit about confidence level: high/medium/low for each finding