ml-paper-writing Eval
=====================

Status: failed
Score: 73/100
Risk: high
Decision: do_not_auto_install
Policy: block
Reason: Permission surface: shell or command execution, filesystem or document access

Install:
npx skills add OpenRaiser/NanoResearch --skill ml-paper-writing

Required checks:
- PASS Task fit: Task wording matches this skill metadata.
- PASS Install path: Install handoff is available.
- PASS Install command safety: standard package or runtime install path
- WARN Trust score: Good trust signals with a few areas worth checking before rollout.
- WARN Audit score: Needs review
- WARN Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
- PASS License clarity: MIT
- FAIL Permission surface: shell or command execution, filesystem or document access

Warnings:
- Trust score: Good trust signals with a few areas worth checking before rollout.
- Audit score: Needs review
- Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
- High-risk permission hints: Shell or command execution
- Permission surface may require sandboxing
- The skill relies on external MCP servers and APIs (Exa, Semantic Scholar, arXiv, Crossref) without explicit installation instructions or version pinning for dependencies.
- There is no explicit limitations section in SKILL.md clarifying boundaries such as venue policy changes, human oversight, or ethical review responsibilities.
- Dependencies are listed as Python package names but the skill does not provide setup commands, API key guidance, or failure handling for unavailable APIs.
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- Permission surface: shell or command execution, filesystem or document access

Validation plan:
1. Inspect repository, README/SKILL.md, license, and recent commits before production use.
2. Install in an isolated workspace or sandbox with no production secrets available.
3. Run the smallest representative task and record files touched, commands run, network access, and outputs.
4. Compare the selected skill against at least one alternative when the eval status is review or failed.
5. Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Do not use when:
- teams that need a vendor-supported SLA
- production agents without a repository review
- The skill relies on external MCP servers and APIs (Exa, Semantic Scholar, arXiv, Crossref) without explicit installation instructions or version pinning for dependencies.
- No OpenAgentSkill engagement data yet
- High-risk permission hints: Shell or command execution
- Permission surface may require sandboxing
- There is no explicit limitations section in SKILL.md clarifying boundaries such as venue policy changes, human oversight, or ethical review responsibilities.
- Dependencies are listed as Python package names but the skill does not provide setup commands, API key guidance, or failure handling for unavailable APIs.

URLs:
- Skill: https://www.openagentskill.com/skills/openraiser-ml-paper-writing
- Audit: https://www.openagentskill.com/skills/openraiser-ml-paper-writing/audit
- JSON: https://www.openagentskill.com/api/agent/evals?slug=openraiser-ml-paper-writing