Grounding
Every edge is a source claim.
Nodes, transitions, guards, and refinements can link back to requirements, code, tests, logs, policies, or upstream diagrams for review.
Mermaid diagrams · LLM semantics · verifiable logic
Mermaid Engine treats every diagram as an abstraction of source data, links nodes and edges back to evidence, and compiles the result into deterministic forms with honest verification manifests that logic tools and AI agents can review and traverse.
mdd update
The copied text installs from https://mermaidengine.com/install.sh, asks the agent to inspect mdd-engine --help, mdd-agent --help, and mdd --help, tells the agent to use mdd update for a future website re-install, prefers deterministic replay when no Ollama/Qwen is configured, mentions extract-targets, obligations, eval-run, and learn failure, and tells the agent not to claim proof unless verification.json records a deterministic backend run.
Why use it?
Specs, prompts, issues, source code, logs, policies, and architecture notes often describe the same system in conflicting ways. Mermaid Engine refines domain knowledge into one reviewable graph whose parts can be checked back against linked source evidence, then compiled into a portable bundle for deterministic agent traversal.
Grounding
Nodes, transitions, guards, and refinements can link back to requirements, code, tests, logs, policies, or upstream diagrams for review.
Deployment
Run heavyweight refinement and concrete checks once, then distribute the lightweight mdd CLI with compiled .mddbundle diagrams and their verification manifests.
Verification
Compiled artifacts make legal paths deterministic, so agents can evaluate complex systems without inventing unsupported moves.
Replayable source-to-target loop
Mermaid Engine now includes an Autoform-inspired source-to-target workflow without copying Autoform Bot code, prompts, docs, or data. Autoform Bot is non-commercial prior art; MDD keeps the product boundary in deterministic CLI artifacts and replayable evidence.
mdd-targets/v0 plus source-map draftsmdd-obligation-dag/v0 work itemsOpt-in ingest integration
Add --extract-targets, --obligation-dag, and --eval-report when a run needs the target/DAG/evaluation loop. Live LLM extraction remains replayable through saved files for deterministic tests.
mdd-agent ingest docs/requirements/auth.md \
--task-type generic_domain_ingest \
--extract-targets \
--llm-extractions-file fixtures/extractions.json \
--obligation-dag build/run/obligations.json \
--eval-report \
--out-dir build/run \
--llm-diagrams-file fixtures/diagrams.md
How it works
Use it to link requirements, code, tests, logs, or policies to a Mermaid diagram, then either run the deterministic commands directly or let mdd-agent process --source-map perform source-link, source-check, Qwen source-review, source-grounded bundling, and runtime traversal as one replayable lane. Gold edge approval still requires supported current mdd-source-review/v0 evidence, and deployed mdd runtimes expose evidence status per operation. If source evidence goes stale, the lifecycle model drops the diagram below Bronze/Silver/Gold until remapped, re-reviewed, and re-approved.
Current parser subset
The fail-closed compiler currently accepts deterministic event syntax like Draft -- all_edges_approved --> Gold. Common Mermaid pipe labels such as Draft -->|all edges approved| Gold are valid Mermaid, but not accepted by the current MDD compiler yet.
flowchart TD
Draft[Draft]
Gold[Gold]
Draft -- all_edges_approved --> Gold
Built for general users and developers: describe the source reality, refine it into an auditable diagram, compile a bundle, then give agents a reviewed map they can follow with only the lightweight runtime.
View install script