mri-reconstruction Eval
=======================

Status: failed
Score: 65/100
Risk: high
Decision: do_not_auto_install
Policy: block
Reason: Install path: No install command or repository handoff is available.

Install:


Required checks:
- PASS Task fit: Task wording matches this skill metadata.
- FAIL Install path: No install command or repository handoff is available.
- PASS Install command safety: standard package or runtime install path
- WARN Trust score: Potentially useful, but at least one trust signal needs human inspection.
- 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
- WARN Permission surface: shell or command execution, filesystem or document access

Warnings:
- Trust score: Potentially useful, but at least one trust signal needs human inspection.
- Audit score: Needs review
- Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
- README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context
- Permission surface: shell or command execution, filesystem or document access
- High-risk permission hints: Shell or command execution
- Financial research output is not financial advice; require human review before any live investment decision
- The tracked source changed or could not be synchronized. Review the current source before installing.
- The helper script uses `mktemp -u` which is not race-safe; using `mktemp` without `-u` and then creating files would be safer.
- The script does not verify that the input k-space is actually Cartesian or non-Cartesian; it relies on the user to pass a trajectory only for non-Cartesian data, which could lead to silent errors if misused.
- Low GitHub adoption signal
- Financial research output is not financial advice; require human review before any live investment decision.

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
- Low GitHub adoption signal
- The helper script uses `mktemp -u` which is not race-safe; using `mktemp` without `-u` and then creating files would be safer.
- High-risk permission hints: Shell or command execution
- Financial research output is not financial advice; require human review before any live investment decision
- The tracked source changed or could not be synchronized. Review the current source before installing.
- The script does not verify that the input k-space is actually Cartesian or non-Cartesian; it relies on the user to pass a trajectory only for non-Cartesian data, which could lead to silent errors if misused.

URLs:
- Skill: https://www.openagentskill.com/skills/kewang0622-mri-reconstruction
- Audit: https://www.openagentskill.com/skills/kewang0622-mri-reconstruction/audit
- JSON: https://www.openagentskill.com/api/agent/evals?slug=kewang0622-mri-reconstruction