Agent Mesh
Canon's architecture is built in three tiers, from single-repo agents up to an organization-wide knowledge brain.
Three-Tier Architecture
┌─────────────────────────────────────────────────┐
│ ORG BRAIN (Tier 3) │
│ │
│ Knowledge graph · Cross-repo search · Patterns │
│ "Who owns payments?" · "What decided X?" │
│ Org-wide spec coverage · Dependency map │
│ Executive dashboards · Compliance reports │
├─────────────────────────────────────────────────┤
│ AGENT MESH (Tier 2) │
│ │
│ Agent-to-agent communication · Event bus │
│ "Repo A's spec references Repo B's API" │
│ Cross-team impact analysis · Conflict detection │
│ Shared vocabulary / taxonomy enforcement │
├─────────────────────────────────────────────────┤
│ REPO AGENTS (Tier 1) │
│ │
│ All-markdown indexing · PR analysis · Doc PRs │
│ Spec realization · Ticket sync · Stale detection │
│ MCP server · Slack Q&A · Coverage metrics │
│ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ │
│ │Repo 1│ │Repo 2│ │Repo 3│ │ ×300 │ │
│ └──────┘ └──────┘ └──────┘ └──────┘ │
└─────────────────────────────────────────────────┘Tier 1 is where you start. Tier 2 is the moat. Tier 3 is the platform.
Tier 1: Repo Agents
Each repository gets its own agent that handles:
- All-markdown indexing — Parses specs, ADRs, guides, READMEs into a searchable knowledge base
- PR analysis — Analyzes pull requests against spec acceptance criteria and indexed docs
- Spec realization — Verifies code implements what specs say, with evidence
- Doc-update PRs — Generates pull requests to update stale documentation
- Ticket sync — Bidirectional link between spec sections and Jira/Linear/GitHub Issues
- Stale detection — Flags docs that haven't been updated when related code changes
- MCP server — Exposes spec knowledge to coding agents (Claude Code, Cursor, VS Code)
Analysis Pipeline
The PR analysis pipeline is the core workflow:
Interactive Commands
Users interact with the bot by commenting on PRs:
| Command | Behavior |
|---|---|
@canon dismiss | Deletes the bot's analysis comment |
@canon reanalyze | Re-runs the full analysis pipeline |
@canon apply docs | Creates a PR with suggested doc updates applied |
Tier 2: Agent Mesh
Status: Planned
Tier 2 is on the roadmap. The features below describe the design vision.
When multiple repos have agents, the mesh layer enables cross-repo awareness:
- Cross-repo references — Repo A's spec references Repo B's API; changes to B trigger analysis in A
- Impact analysis — A breaking change in a shared library flags all downstream specs
- Conflict detection — Two teams' specs make contradictory assumptions about the same system
- Shared taxonomy — Enforce consistent terminology and patterns across the organization
Tier 3: Org Brain
Status: Planned
Tier 3 is on the roadmap. The features below describe the design vision.
The org brain aggregates knowledge from all repo agents:
- Cross-repo search — "What does our retry policy look like across all services?"
- Ownership graph — "Who owns the payments domain?"
- Decision index — "What ADRs relate to database choices?"
- Compliance reports — "Which specs lack acceptance criteria?"
- Executive dashboards — Organization-wide spec coverage and documentation health
The Network Effect
1 repo → nice spec workflow, all docs searchable
10 repos → cross-repo references, shared knowledge base
50 repos → the agent mesh becomes indispensable
300 repos → the org brain knows more than any human
about how the company's software worksEach new repo makes every existing repo's agent smarter. Each indexed doc enriches the knowledge base. Each PR analysis teaches the platform what changed.
Related
- Guide: Self-Hosting — deploy Canon on your own K8s cluster
- Guide: CI Integration — run
canon verifyin your CI pipeline - Reference: MCP Tools — the 11 tools exposed to coding agents
- Reference: Claude Code Skills —
/canon-*commands for interactive agent workflows - Architecture: System Design — component diagram and deployment architecture
- Architecture: Data Flow — PR analysis and ticket sync request flows