v1truv1us/ai-eng-system

check-agent-compatibility

Run the full repository compatibility pass: scanner score, startup path, validation loop, and docs reliability.

First seen Aug 17, 2026

Installation

$ npx skills add v1truv1us/ai-eng-system --skill check-agent-compatibility

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 8
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0
Declared agents cursor
More metadata
category
user-invoked
version
1.0.0
tags
cursor-import, agent-compatibility

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,771 B
  • docs SUMMARY.md 144 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Default output: return only the result, blockers, and required evidence. Omit preambles, process narration, repeated context, confidence scores, and follow-up offers. Use at most five bullets unless a required artifact or schema needs more.

Check agent compatibility

Trigger

Use when the user wants the full compatibility pass for a repo.

Workflow

  1. Launch compatibility-scan-review to run the CLI and capture the raw repository score and main issues.
  2. Launch startup-review to verify whether the repo can actually be booted by an agent.
  3. Launch validation-review to check whether an agent can verify a small change without an unnecessarily heavy loop.
  4. Launch docs-reliability-review to see whether the documented setup and run paths reliably match reality.
  5. Use one subagent per task. Do not collapse these checks into one agent prompt.
  6. Compute an internal workflow score as the rounded average of:

- Startup Compatibility Score - Validation Loop Score - Docs Reliability Score

  1. Compute an Agent Compatibility Score as:

- round((deterministicscore 0.7) + (workflowscore 0.3))

  1. Synthesize the results into one final response.

When scoring internally, use specific non-round workflow scores for the behavioral checks rather than coarse round buckets. If startup, validation, or docs mostly work, treat them as good-with-friction rather than defaulting to the mid-60s. Do not create a low workflow score just because logs are noisy or the error text is rough.

Output

Respond in markdown, but keep it minimal. Do not use fenced code blocks.

Show only one score, as a level-two heading: ## Agent Compatibility Score: N/100. Do not show how it was computed, including weights, formula, deterministic score, workflow score, per-check scores, or arithmetic, unless the user explicitly asks for a breakdown.

Then a flat, prioritized list labeled Top fixes with one issue per line, each line starting with - .

If the deterministic scanner cannot be run because of tool environment issues, say that separately and do not treat it as a repo defect or penalize the repo. Fold deterministic and behavioral findings into that one list instead of separate sections. Focus on the fixes that would most improve real agent workflows. Do not include a separate summary unless the user asks for more detail.

Example shape:

Agent Compatibility Score: 72/100

Top fixes

  • First issue
  • Second issue
  • Third issue