name: knowledge-router description: Build a lightweight routing layer across existing knowledge sources such as MEMORY.md, daily memory files, self-improving notes, skill references, and audit records. Use when you need to decide where a question should be answered from before reading too much, when you want a unified knowledge index, or when you want to detect which knowledge should be promoted into a more durable layer.

Knowledge Router

Route queries to the right knowledge layer before doing broad reading.

Core workflow

1. Scan known knowledge sources and classify them by role.
2. Infer the query intent: rule, fact, method, evidence, or improvement.
3. Recommend primary and secondary sources.
4. Emit promotion hints when knowledge seems mature enough to move upward into a more durable layer.

Read references as needed

• Read references/source-types.md for the knowledge source model.
• Read references/routing-rules.md for intent-to-source routing rules.
• Read references/promotion-rules.md for when knowledge should be promoted or extracted.
• Read references/report-format.md for the report structure.
• Read references/release-minimal.md before packaging or publishing so the first public surface stays minimal.

Use scripts as needed

• Use scripts/knowledge_router.py "<query>" [--scope ...] [--output report.txt] to build a routing report.

Operating rules

• Prefer routing over re-storing knowledge.
• Prefer a small number of clearly justified sources over broad search noise.
• Treat audit logs as evidence, not as the first answer source for general method questions.
• Keep the first version focused on source typing, query intent, and recommendation quality.