The knowledge base is the team memory for agentic coding. It stores decisions, session notes, project vocabulary, skill notes, agent patterns, and source-of-truth links.

Plain Markdown is the default:

coding-scaffold knowledge --target ~/dev/my-project

This creates:

• .coding-scaffold/KNOWLEDGE.md
• .coding-scaffold/knowledge.json
• .coding-scaffold/knowledge/

Use a shared remote when multiple people should contribute:

coding-scaffold setup-knowledge --target ~/dev/my-project \
 --backend markdown \
 --shared-remote https://github.com/acme/team-ai-knowledge.git

You can keep the knowledge base inside the project repo, or clone a separate repo into .coding-scaffold/knowledge.

Hierarchical sharing is an optional organization pattern. Start with structure before adding multiple remotes:

.coding-scaffold/knowledge/
 company/
 unit/
 department/
 team/
 sharing/

Use each layer for a different audience:

• team: project facts, local prompts, first skill drafts, session findings.
• department: reusable runbooks, system patterns, validated agent roles.
• unit: domain vocabulary, reference architecture, shared provider policy.
• company: standards, approved skills, approved agents, security and privacy rules.

Use frontmatter to make ownership and promotion visible:

scope: team
maturity: draft
owner: platform-ai
tags: [testing, opencode]
source_project: billing-api
reviewed_by: ""
expires: 2026年12月31日

Use maturity levels as a trust ladder:

• draft: captured from real work but not reviewed.
• validated: tried in at least one project and reviewed by peers.
• recommended: useful across multiple teams or systems.
• standard: approved default for this scope.

Promote knowledge upward by pull request. Keep secrets out of every layer. Use separate Git remotes only when access boundaries differ; otherwise one shared repo with folders, tags, and CODEOWNERS is easier to operate.

Check the current state:

coding-scaffold knowledge-status --target ~/dev/my-project

The status command counts notes by scope and maturity, and flags missing frontmatter on layered notes.

Obsidian mode keeps Markdown as the source of truth while adding vault structure, backlinks, frontmatter templates, and graph-friendly navigation:

coding-scaffold setup-addon --target ~/dev/my-project --addon obsidian
coding-scaffold knowledge --target ~/dev/my-project --backend obsidian

Use this when humans want a better reading and navigation layer. In WSL, install the desktop app on Windows and open .coding-scaffold/knowledge as a vault.

MemPalace mode adds notes for optional local semantic retrieval and MCP-compatible memory workflows:

coding-scaffold knowledge --target ~/dev/my-project --backend mempalace

Use this when the Markdown corpus grows large enough that search and semantic retrieval matter.

Good knowledge entries answer:

• what did we decide?
• why did we decide it?
• where is the source of truth?
• which skill or agent should use this?
• when should this knowledge be reviewed or removed?