Assess a repository without changing it and report its type, suggested agent roles, risk, MCP connections, test confidence, and publication readiness. Use the results for setup decisions, comparisons over time, or automated risk checks in CI.
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7-section repo readiness report from `metaharness genome {path}`. Returns repo_type / agent_topology / risk_score / mcp_surface / test_confidence / publish_readiness. Pure-read; degrades gracefully (ADR-150).
安装前可以查看交给 AI 代理的指令内容。
Companion to harness-score. Where score is a 5-dimension numeric
scorecard, genome is a 7-section categorical/numeric report covering
repo type, agent topology recommendations, risk score (0-1), MCP
surface area, test confidence (0-1), and publish readiness (0-1).
Implementation: scripts/genome.mjs.
npx metaharness genome <path> --json (60s hard timeout).{ repo_type, agent_topology[], risk_score, mcp_surface, test_confidence, publish_readiness }.verdict and
verdictExitCode. Upstream exits 1 for needs-work and 2 for blocked;
these are valid reports, so the wrapper returns them successfully.--alert-on-risk-above N: exit 1 when risk_score > N.{
"repo_type": "node_mcp_ci",
"agent_topology": ["maintainer", "tester", "security", "release"],
"risk_score": 0.27,
"mcp_surface": "remote",
"test_confidence": 0.8,
"publish_readiness": 0.9
}
Ruflo's risk_score: 0.27 is low (good). publish_readiness: 0.9 is
high. The mcp_surface: "remote" reflects that ruflo's MCP servers are
hosted, not bundled.
agent_topology recommendations
drift away from a deliberate architecture choice.--alert-on-risk-above 0.5 fails the build when the repo's
risk profile crosses a threshold.harness-score — numeric readinessharness-mcp-scan — static MCP security findingsharness-threat-model — enterprise-review-grade threat model还没有评价。欢迎分享你的使用感受。
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
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Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
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Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
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Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
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Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
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Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.
中文简介正在准备中。当前显示英语简介。