LogicChart

<p align="center"> <img src="docs/assets/codedebrief-wordmark.svg" alt="CodeDebrief" width="420"> </p> <p align="center"> <strong>Source-grounded workflow diagrams for coding agents and codebase exploration.</strong> </p> <p align="center"> <a href="https://pypi.org/project/codedebrief/"><img alt="PyPI" src="https://img.shields.io/pypi/v/codedebrief"></a> <a href="https://pypi.org/project/codedebrief/"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/codedebrief"></a> <a href="LICENSE"><img alt="License" src="https://img.shields.io/github/license/ferdinandobons/CodeDebrief"></a> <img alt="MCP first" src="https://img.shields.io/badge/MCP--first-local--first-6b8cff"> </p> <p align="center"> <a href="https://ferdinandobons.github.io/CodeDebrief/">Website</a> · <a href="#quick-start">Quick Start</a> · <a href="#coding-agent-workflow">Agent Workflow</a> · <a href="#manual-viewer">Manual Viewer</a> · <a href="CHANGELOG.md">Changelog</a> </p> CodeDebrief turns a local codebase into deterministic workflow flowcharts that coding agents can inspect, render, expand, translate, and explain. It statically maps entrypoints, decisions, branches, internal calls, returns, exceptions, and outcomes before the agent answers, so the visual explanation is grounded in reusable artifacts instead of a fresh best-effort reconstruction. The analyzer, artifacts, viewer, and MCP server are local-first and do not require an LLM provider key. CodeDebrief is not a documentation generator, a bug finder, a generic graph database, or an LLM enrichment service; it is a workflow navigation layer for understanding how code paths actually connect.  Example output: a compact presentation layer generated from local CodeDebrief artifacts. Canonical workflow visuals are vertical by default; horizontal diagrams are used when the user explicitly asks for a compact overview. > Status: pre-1.0 alpha. The model is versioned, but schema and MCP payloads may evolve > before 1.0. Latest release: > [v0.17.0](https://github.com/ferdinandobons/CodeDebrief/releases/tag/v0.17.0). ## Quick Start CodeDebrief requires Python 3.10 or newer. Install it from PyPI with `uv`: ```bash uv tool install codedebrief codedebrief setup claude ``` Replace `claude` with `codex`, `gemini`, or `cursor` for another supported agent surface. To analyze only selected folders while keeping `codedebrief-out` in the current project root, pass them during setup: ```bash codedebrief setup claude --source backend/ frontend/ ``` For a multi-repo workspace, create or choose one folder to hold CodeDebrief config and artifacts, then point `--source` at the repos: ```bash mkdir pipeline-map cd pipeline-map codedebrief setup claude --source ../ingest-service ../transform-service ../warehouse-ui ``` Scope size matters. Pointing CodeDebrief at the whole repository or at many large folders can materially increase `setup`, `update`, and MCP response times because there are more files to hash, parse, link, and search. Prefer the smallest source roots that still contain the workflows you want agents to explain. MCP responses are bounded by `token_budget`. If an agent passes an explicit budget, CodeDebrief honors it. For broad `agent_context` requests that use the default budget, CodeDebrief automatically raises the effective budget on large projects so the first slice has enough room without forcing the agent to retry with a bigger request. After setup, ask ordinary questions: ```text Show me the checkout workflow. Which branches handle a failed payment? What workflows are affected by this file? Where is this status handled? Expand this workflow one level deeper. ``` For manual exploration: ```bash codedebrief view ``` `setup` keeps CodeDebrief-owned config and artifacts in `codedebrief-out/` by default: ```text codedebrief-out/ ├── codedebrief.toml optional project config created by setup ├── codedebrief.html local interactive full-project viewer ├── codedebrief.md reviewable Mermaid flowcharts ├── codedebrief.json canonical model for MCP, CI, scripts, and the viewer ├── codedebrief.hash.json model hash sidecar for faster MCP cold starts └── codedebrief.errors.jsonl saved CLI/MCP diagnostics, when errors occur ``` Provider-required files still live where the client expects them, for example `.mcp.json`, `AGENTS.md`, `CLAUDE.md`, `GEMINI.md`, `.cursor/rules/codedebrief.mdc`, and agent skill directories. For explicit refresh during development: ```bash codedebrief update codedebrief validate --check-sync ``` The default CLI output is intentionally compact. Add `--verbose` to `setup`, `update`, `validate`, or `doctor` when you need detailed progress and file paths. To inspect saved local errors from failed CLI/MCP operations: ```bash codedebrief doctor --errors codedebrief doctor --errors --clear ``` To remove CodeDebrief from the current project folder: ```bash codedebrief clear ``` `clear` removes `codedebrief-out/`, legacy root `codedebrief.toml`, `.codedebriefignore`, installed CodeDebrief skills, MCP server entries, and managed instruction blocks. It asks for confirmation by default; use `codedebrief clear --yes` in scripts. To install a pinned GitHub release instead: ```bash uv tool install "git+https://github.com/ferdinandobons/CodeDebrief.git@v0.17.0" ``` Or install from a source checkout: ```bash git clone https://github.com/ferdinandobons/CodeDebrief.git codedebrief cd codedebrief uv tool install . ``` ## Why It Exists A coding agent can reconstruct a workflow from raw source, but that reconstruction normally depends on the searches it performs, the files it selects, and the context it has room to read. Repeating that process is slow, and less obvious branches or cross-file paths can be left out. CodeDebrief creates a reusable navigation layer before the agent explains anything: - entrypoints, decisions, branches, calls, outcomes, and source ranges; - domain concepts such as statuses, roles, permissions, enums, and feature flags; - affected-workflow context for changed files, symbols, flows, and dependency paths; - canonical visual slices with stable diagram hashes; - optional language-friendly labels derived as a presentation layer from analyzer facts. ## Where It Fits CodeDebrief does not replace maintained project documentation. Documentation should capture architecture, intent, invariants, conventions, operational knowledge, and why important decisions were made. CodeDebrief serves a faster and narrower need: inspecting the workflow encoded in the current source while brainstorming, debugging, planning a change, or reviewing impact. Use it to: - visualize one focused part of a workflow on demand; - follow decisions and internal calls across files; - inspect workflows affected by a file, symbol, or planned change; - give a coding agent a shared structural slice to reason over immediately. Documentation explains the system over time. CodeDebrief provides an on-demand visual slice of the current source when you need to reason about it. Any agent-written explanation or language-friendly label is a presentation layer over the analyzer-generated flowchart, not the source of the flowchart itself. The generated agent instructions treat CodeDebrief artifacts as part of done for workflow-relevant changes: after meaningful source, route, config, or agent-instruction edits, run `codedebrief update` and `codedebrief validate --check-sync` before finalizing or committing so MCP answers, Markdown summaries, and `codedebrief view` use current graphs. ## What You Can Verify A returned `workflow_slice` can expose: - source ranges for modeled steps; - explicit decisions, branches, calls, and outcomes; - callers, callees, and unresolved-call context; - omissions caused by token budget, ambiguity, stale artifacts, or unsupported capabilities; - stable handles for expanding the slice, tracing a path, or opening the related visual. These signals make the source-level model inspectable. They do not prove business correctness or runtime behavior. ## Map First, Then Explain Once `setup` has configured the project MCP server and agent instructions, supported agents should start code-logic questions with MCP `agent_context`. The agent receives a bounded `workflow_slice` before deciding whether it needs more source, a deeper slice, or a path trace. ```text Show me a visual workflow for the invitation system. Explain this code path with a source-grounded flowchart. Which workflows are affected by this change? Where is this status handled? Expand the omitted branches in this workflow_slice. Rewrite the diagram labels in plain English. ``` The agent can explain the flowchart, but the static analyzer creates the underlying map. ## Setup Supported targets: ```bash codedebrief setup codex codedebrief setup claude codedebrief setup claude --source backend/ frontend/ codedebrief setup claude ../my-app --source backend-api frontend/src codedebrief setup claude ../pipeline-map --source ../repo-a ../repo-b codedebrief setup cursor --full ``` The selected target controls which files are written: | Target | Files | | --- | --- | | `codex` | `AGENTS.md`, `.agents/skills/codedebrief/SKILL.md`, project MCP config | | `claude` | `CLAUDE.md`, `.claude/skills/codedebrief/SKILL.md`, project MCP config | | `gemini` | `GEMINI.md`, `.gemini/skills/codedebrief/SKILL.md`, `.gemini/settings.json` MCP config | | `cursor` | `.cursor/rules/codedebrief.mdc`, project MCP config | `setup <target>` writes only that target's files. Run it separately for each agent surface you want to configure. `setup` creates `codedebrief-out/codedebrief.toml` when needed, installs the selected agent instruction file, installs a provider-native CodeDebrief skill where supported, registers project-scoped MCP where supported, generates initial artifacts, runs `doctor`, and validates the result. Use `--source` to set `source_roots` before that initial artifact generation starts. On Windows, run `setup` in the same environment that will run the coding agent when possible. If you run `setup` from WSL inside a `/mnt/c/...` project, CodeDebrief writes JSON MCP configs that launch the server through `wsl.exe` with `--cd <project>` and `bash -lc "codedebrief mcp ."`, so Windows-native agent clients do not receive a raw WSL path as their command target. The `gemini` target follows Gemini CLI / Antigravity conventions: `GEMINI.md` provides project context, `.gemini/skills/codedebrief/SKILL.md` provides provider-native workflow guidance, and `.gemini/settings.json` registers the project-scoped CodeDebrief MCP server. ## Agent Workflow For natural-language questions, agents should start with MCP `agent_context`. `agent_context` returns a `workflow_slice` with: - normalized intent and task type; - primary and supporting flows; - ordered source-grounded steps; - decision nodes, branches, values, and outcomes; - calls, callers, callees, and unresolved call context; - domain logic for relevant state-like concepts; - source ranges the agent can cite; - visual handles for `snapshot_slice` and `codedebrief view`; - omissions caused by token budget, ambiguity, stale artifacts, or unsupported capability; - follow-up tools for expansion, path tracing, focused explanation, and snapshots. When a user asks for a visual workflow, the agent should first render the deterministic Mermaid visual returned by CodeDebrief: 1. Render `workflow_slice.presentation.canonical_visual.diagram` exactly as returned only when the client renders Mermaid inline. 2. If the client cannot render Mermaid inline, use `snapshot_slice` with `include_svg=false` and provide the returned `.mmd` or Mermaid Markdown artifact before prose. Do not paste a long Mermaid code block as the primary visual unless the user asks for raw or copyable Mermaid. These generated files are meant to be opened with the best available local preview path, for example by opening the Markdown artifact in VS Code and using Markdown or Mermaid preview support. 3. Use SVG snapshot artifacts only when the user explicitly asks for SVG or local inspection. They are not the canonical chat visual. The model may choose the first visible depth, but the text inside shown blocks must come from CodeDebrief payloads. After the visual, the answer should include a short high-level written flow in the user's language, derived from ordered steps, selected flows, decisions, domain logic, and source ranges. That written flow should explain the happy path first and include only the branches needed by the request. The answer should also say that the diagram is a bounded summary and can be expanded. If the user wants a more language-friendly view, the agent may rewrite both labels and the written flow in the user's language as a separate presentation layer, preserving ids or source anchors and without adding facts. ## MCP Surface Primary MCP tools: | Tool | Purpose | | --- | --- | | `agent_context` | Default entrypoint for natural-language questions and changed-code context. | | `expand_slice` | Widen or deepen a workflow slice from stable flow handles. | | `workflow_path` | Trace a deterministic path between flows, symbols, or concepts. | | `snapshot_slice` | Render a deterministic visual snapshot for a slice. | | `explain_flow` | Explain one flow with ordered steps, decisions, calls, and source anchors. | | `explain_node` | Explain one flowchart node with local edge and source context. | | `explain_edge` | Explain one modeled edge with source context. | | `validate_artifacts` | Check generated model validity and optional JSON/Markdown sync. | | `update_codedebrief` | Refresh JSON, Markdown, and HTML artifacts from local source. | Use `codedebrief view` for the manual UI. The CLI intentionally stays small: `setup`, `update`, `view`, `validate`, `doctor`, `clear`, and `mcp`. ## Generated Artifacts | File | Commit? | Purpose | | --- | --- | --- | | `codedebrief.json` | Yes | Canonical model consumed by MCP, CI, scripts, and the viewer. | | `codedebrief.md` | Yes | Generated inspection artifact with Mermaid flowcharts. It is not a replacement for maintained project documentation. | | `codedebrief.errors.jsonl` | Usually no | Append-only local diagnostics for failed CLI/MCP operations. Inspect it with `codedebrief doctor --errors`. | | `codedebrief.html` | Usually no | Local interactive viewer generated from the model. | Commit `codedebrief.json` and `codedebrief.md` when CodeDebrief is part of the project workflow. `codedebrief validate --check-sync` verifies that the JSON model matches current source and that `codedebrief.md` was rendered from that model. Regenerate HTML locally when a human needs the viewer. `codedebrief doctor` also reports legacy `logicchart` MCP server configs left from older installs. Re-run `codedebrief setup <target>` for the affected agent to replace them with project-scoped `codedebrief` MCP config. `codedebrief doctor --errors` shows recent saved diagnostics from `codedebrief-out/codedebrief.errors.jsonl`; use `codedebrief doctor --errors --clear` after you have resolved them. `codedebrief validate --quality` reports analyzer health. Its call-resolution rate is based on project calls only: deterministic runtime, standard-library, DOM/browser, and dynamic receiver calls are counted separately as `runtime_or_dynamic` so they do not look like unresolved workflow edges. ## Team Workflow A simple shared workflow is: 1. Run `codedebrief setup <target>` in the project. 2. Commit `codedebrief.json` and `codedebrief.md`. 3. Let teammates pull the same source-grounded model. 4. After workflow-relevant source, route, config, or agent-instruction changes, run `codedebrief update` and `codedebrief validate --check-sync` before finalizing or committing. The HTML viewer is normally regenerated locally rather than committed. ## Manual Viewer `codedebrief view` opens the complete interactive flowchart for a human. It is the official manual experience for broad exploration: ```bash codedebrief view codedebrief view --render-only --no-open ```  Example manual view: the interactive browser canvas for exploring scopes, files, entry points, and connected workflow flows. Use the viewer when you need to inspect the whole project graph, navigate scopes, compare neighboring flows, or visually follow callers and callees. Use MCP when an agent should answer a bounded question with a focused `workflow_slice`. ## Domain Logic CodeDebrief extracts and aggregates domain concepts such as: - enum members; - status and lifecycle states; - roles and permissions; - feature flags; - handled values and the decisions that branch on them. `agent_context` includes relevant domain logic inside the returned `workflow_slice`, with links back to flows, nodes, source ranges, snapshots, and viewer targets. Value matching uses modeled code facts, including enum-style suffix matches such as `PAID` for `Status.PAID`. ## Supported Code CodeDebrief currently extracts control flow for 11 language ids: | Language | Current coverage | | --- | --- | | Python (`.py`) | AST analyzer with functions, methods, decisions, loops, calls, returns, exceptions, tests, enum harvest, and import dependencies. | | TypeScript / TSX (`.ts`, `.tsx`) | Tree-sitter analyzer with Next.js and React entrypoint detection, decisions, loops, calls, returns, expression-bodied arrows, tests, enum harvest, and import dependencies. | | JavaScript / JSX (`.js`, `.jsx`, `.mjs`, `.cjs`) | Tree-sitter analyzer with JavaScript labeling, decisions, loops, calls, returns, expression-bodied arrows, tests, and import dependencies. | | Go (`.go`) | Profile-driven tree-sitter analyzer with functions, methods, decisions, loops, calls, returns, tests, and import dependencies. | | Java (`.java`) | Profile-driven tree-sitter analyzer with methods, decisions, loops, calls, returns, exceptions, tests, imports, and Spring route annotations. | | C# (`.cs`) | Profile-driven tree-sitter analyzer with methods, decisions, loops, calls, returns, exceptions, and tests. | | PHP (`.php`) | Profile-driven tree-sitter analyzer with functions, methods, decisions, loops, calls, returns, exceptions, and tests. | | C (`.c`, `.h`) | Profile-driven tree-sitter analyzer with functions, decisions, loops, calls, returns, and tests. | | C++ (`.cc`, `.cpp`, `.cxx`, `.hh`, `.hpp`, `.hxx`, `.ipp`, `.tpp`) | Profile-driven tree-sitter analyzer with functions, methods, decisions, loops, calls, returns, exceptions, and tests. | | Rust (`.rs`) | Profile-driven tree-sitter analyzer with functions, decisions, loops, calls, match handling, returns, and tests. | | Ruby (`.rb`) | Profile-driven tree-sitter analyzer with methods, decisions, loops, calls, returns, and tests. | Generated models include `metadata.language_capabilities`, with feature flags and limitation notes per language. Agents should use that contract when explaining analyzer depth. ## Privacy The analyzer, canonical artifacts, Mermaid generation, local viewer, and MCP server do not require an LLM API key. CodeDebrief itself builds the workflow model locally. When CodeDebrief is connected to a hosted coding agent, the agent may receive the workflow slices and source ranges returned through MCP. That transfer is governed by the coding agent and provider you use. ## Configuration CodeDebrief works without config. New `setup` runs create `codedebrief-out/codedebrief.toml` only when defaults are not enough; legacy root `codedebrief.toml` files are still read and preserved. ```toml [codedebrief] # Analyze only these folders or files. Paths are relative to the project root where you # run CodeDebrief unless absolute; sibling repos such as "../api" are supported. # Artifacts still write under output_dir relative to this project root. source_roots = ["."] exclude = [] exclude_dirs = [] include_public_functions = true max_call_depth = 4 output_dir = "codedebrief-out" self_exclude = true [codedebrief.entrypoints] include = [] exclude = [] [codedebrief.scopes] backend = ["backend/**", "services/**"] frontend = ["frontend/**", "web/**"] edge = ["edge/**", "workers/**"] ``` Defaults prune common VCS, dependency, cache, temporary, generated, and output directories, including `.git`, `node_modules`, virtualenv folders, `.next`, `.turbo`, `.svelte-kit`, `.nx`, `.pytest_cache`, `.mypy_cache`, `.ruff_cache`, `.pyre`, `.dart_tool`, `dist`, `build`, `out`, `target`, `obj`, `coverage`, `vendor`, `Pods`, and `codedebrief-out`. ### Analyze Selected Folders Or Repos Yes, this is supported. Run CodeDebrief from the directory where you want the workspace configuration and `codedebrief-out` folder to live, then pass the selected folders or repos to `--source`. For example, from the repository root: ```bash cd path/to/my-project codedebrief setup claude --source backend-api frontend/src ``` With that configuration: - CodeDebrief analyzes only `backend-api/` and `frontend/src/`; - `codedebrief-out/codedebrief.json`, `codedebrief-out/codedebrief.md`, the hash sidecar, and the local viewer HTML are still created in the current project root; - MCP and the manual viewer keep using the root project context, but the modeled workflows come only from the selected folders. For sibling repos, use a dedicated workspace folder: ```bash mkdir pipeline-map cd pipeline-map codedebrief setup claude --source ../repo-ingest ../repo-transform ../repo-app ``` With that configuration, CodeDebrief writes its config and artifacts under `pipeline-map/codedebrief-out/`, while model paths stay relative to the workspace, for example `../repo-ingest/src/pipeline.py`. Inferred scopes use the repo folder name (`repo-ingest`, `repo-transform`, `repo-app`) unless you define `[codedebrief.scopes]` manually. `--source` values may point to folders or individual source files. CodeDebrief writes them into the active config as `source_roots` before the initial analysis starts. If you want separate models for different parts of a monorepo or multi-repo workspace, use different workspace roots or profiles with different `output_dir` values. ## Limitations CodeDebrief does not run code, observe runtime state, perform full symbolic execution, prove business correctness, or reconstruct deep framework state. It statically models source files, control flow, selected framework conventions, and resolvable internal calls. Important practical limits: - dynamic dispatch may remain unresolved; - language capability varies by analyzer frontend; - generated or unsupported files may be skipped; - large slices are token-budgeted and report omissions; - the displayed first slice is a bounded summary and can be expanded with MCP tools. ## FAQ ### Does CodeDebrief replace project documentation? No. Maintained documentation should explain architecture, intent, design rationale, conventions, and operational knowledge. CodeDebrief is for fast, source-grounded workflow inspection during brainstorming, debugging, planning, and impact analysis. ### Does an LLM generate the flowcharts? No. The analyzer builds the canonical workflow model and Mermaid diagrams from source. A coding agent can choose a bounded slice, render it, translate labels, or explain it, but those actions remain a presentation layer over the deterministic graph. ### How is this different from a generated repository summary? A generated summary is prose produced for one request and one context window. CodeDebrief maintains a reusable structural model that can return bounded flowcharts, source anchors, omissions, and expansion handles for later questions. ### Is CodeDebrief an AI code review tool? No. CodeDebrief is for code comprehension and workflow navigation. It helps humans and coding agents understand modeled logic; it does not present possible defects as product output. ### Does CodeDebrief require an LLM API key? No. The analyzer, artifacts, Mermaid diagrams, manual viewer, and MCP server are local-first and deterministic. Coding agents can use the MCP tools without any required provider key. ### How is CodeDebrief different from a call graph? A call graph shows relationships between symbols. CodeDebrief models workflow slices with entrypoints, decisions, branches, ordered steps, source ranges, domain concepts, visual targets, and expansion tools for coding agents. ### Can CodeDebrief generate Mermaid workflow diagrams from code? Yes. `agent_context` returns a canonical top-to-bottom Mermaid visual for the selected `workflow_slice`, and `snapshot_slice` can persist Mermaid files for clients that cannot render Mermaid inline. ### Can I use CodeDebrief only as a manual visual explorer? Yes. Run `codedebrief view` to open the interactive local viewer. MCP is the primary agent surface, but the viewer remains the official manual exploration surface. ## Development For local development in this repository: ```bash uv sync --extra dev uv run codedebrief --help ``` Standard gates: ```bash UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run ruff check . UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run ruff format --check . UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run mypy UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run pytest --cov UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run codedebrief validate . --check-sync --json ``` Viewer gates: ```bash npm run viewer:typecheck npm run viewer:test npm run viewer:build UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run codedebrief update UV_CACHE_DIR=/tmp/codedebrief-uv-cache uv run codedebrief view --render-only --no-open ``` Schemas: - [schema/codedebrief.schema.json](schema/codedebrief.schema.json) documents the canonical artifact model. ## License Apache License 2.0. See [LICENSE](LICENSE).