Deciduous
Decision graph tooling for AI-assisted development. Track every goal, decision, and outcome. Survive context loss. Query your reasoning.
See It In Action
Browse the Live Decision Graph — 1,100+ decisions from building deciduous itself
Interactive Tutorial — Learn the workflow in 15 minutes
Watch the Demo — Full session walkthrough
The Problem
You're building software with AI assistance. The LLM generates complex code fast. But then:
- Sessions end. Context compacts. The LLM loses memory of what was tried.
- Decisions evaporate. Six months later, no one remembers why you chose approach A over B.
- PRs become incomprehensible. A 50-file diff tells you what changed, not why.
- Onboarding is archaeology. New teammates reverse-engineer decisions from code.
The code tells you what. But decisions tell you why.
The Solution
Deciduous creates a persistent, queryable graph of every decision made during development. Log decisions in real-time—as they happen—and they survive session boundaries, context compaction, and human memory.
1,174 nodes • 1,024 edges • Real development history from building this tool
Both you and your AI assistant can:
- Query past reasoning before making new decisions
- See what was tried and what was rejected
- Trace any outcome back to the goal that spawned it
- Recover context after sessions end or memory compacts
This isn't documentation written after the fact. It's a real-time record of how software gets built.
Installation
Homebrew (Recommended)
Pre-built Binaries
Download the latest release for your platform from GitHub Releases:
| Platform | Binary |
|---|---|
| Linux (x86_64) | deciduous-linux-amd64 |
| Linux (ARM64) | deciduous-linux-arm64 |
| macOS (Intel) | deciduous-darwin-amd64 |
| macOS (Apple Silicon) | deciduous-darwin-arm64 |
| Windows | deciduous-windows-amd64.exe |
# Example: Linux/macOS
Via Cargo
From Source
# Binary at target/release/deciduous
Quick Start
# Initialize in your project
# Start logging decisions
# View the graph
That's it. Your first decision graph is live.
The Canonical Flow
Every decision follows this path through the graph:
goal → options → decision → actions → outcomes
- Goals lead to options (possible approaches to explore)
- Options lead to a decision (choosing which option to pursue)
- Decisions lead to actions (implementing the chosen approach)
- Actions lead to outcomes (results of the implementation)
- Observations attach anywhere relevant
- Revisits connect old approaches to new ones when you pivot
Multi-Assistant Support
Deciduous integrates with multiple AI coding assistants:
# Claude Code (default)
# OpenCode
# Windsurf (Codeium)
# Multiple assistants
| Assistant | Flag | Integration Files |
|---|---|---|
| Claude Code | --claude (default) |
.claude/, CLAUDE.md |
| OpenCode | --opencode |
.opencode/, AGENTS.md |
| Windsurf | --windsurf |
.windsurf/hooks/, .windsurf/rules/ |
Auto-detection: deciduous update auto-detects which assistants are installed (.claude/, .opencode/, .windsurf/) and updates them all. Windsurf is also auto-detected during init if .windsurf/ already exists.
The Workflow
BEFORE you do something → Log what you're ABOUT to do
AFTER it succeeds/fails → Log the outcome
CONNECT immediately → Link every node to its parent
Example Session
# Starting a new feature
# Considering options
# Attach the design spec to the goal
# Making a choice
# Implementing the chosen approach
# Attach the architecture diagram to the action
# Recording the outcome
# Export the graph
Document Attachments
Attach files to any decision node — architecture diagrams, specs, screenshots, PDFs.
# Attach a diagram to a goal
# AI-generate a description
# List what's attached
# Open a document
# Soft-delete (recoverable)
# Clean up orphaned files
Documents are stored in .deciduous/documents/ with content-hash naming for deduplication. The web viewer displays attached documents in the node detail panel. Soft-delete with doc detach; garbage-collect orphaned files with doc gc --dry-run to preview.
Session Recovery
When context compacts or you start a new session:
Or open the web viewer and ask a question in plain English:
"What was I working on before the session ended?" "What approach did we take for rate limiting and why?"
The graph remembers what you don't. The Q&A interface lets you ask it.
Skills: Archaeology, Decision-Graph, and Narratives
Deciduous ships with skills that give your AI assistant structured ways to understand and work with a codebase's decision history.
/decision-graph — Visiting and documenting the past
The /decision-graph skill builds a full decision graph from your repository's commit history — perfect for bootstrapping a graph on an existing project that wasn't using deciduous from the start. It works in four layers:
- Commit analysis — Groups commits into logical narratives
- Code structure — Identifies architectural decisions from the codebase
- Narrative construction — Builds evolution stories with pivots and connections
- PR context — Uses
ghCLI to mine PR descriptions and review threads for decision rationale, alternatives considered, and trade-offs discussed
/archaeology — Revisit, correct, execute
Archaeology is for revisiting past decisions in the graph—finding what went wrong, correcting the record, and executing on a new direction. When you discover a past decision was flawed, archaeology gives you the workflow to trace it back, mark it superseded, and connect the new approach.
# Find the old decision and mark it
# Revisit: pivot from old approach to new
# Execute the new direction
After archaeology, you can query: "What did we try before?" (--status superseded), "What led to this decision?" (edges --to <id>), "What are the pivot points?" (--type revisit).
/narratives — Understand how the system evolved
Narratives are the conceptual stories—how a subsystem evolved over time, what pivots happened, and how different parts of the system connect.
**Current state:** JWT for API, sessions for web.
**Evolution:**
1. 2.3.
**Connects to:** "Rate Limiting"
Output: .deciduous/narratives.md with evolution stories that archaeology can transform into graph structure.
/pulse — Map the current design
Pulse maps the current architecture as a decision tree — the design choices that make the system work today. Your agent reads the code, identifies the design questions that had to be answered, and logs them as nodes. Useful for understanding what decisions you might affect before making changes.
Deep Q&A Interface
The web viewer includes a built-in Q&A interface where you can ask questions about your decision graph and get answers grounded in your actual development history.
POST /api/ask
{
"question": "Why did we switch from JWT to sessions for web auth?",
"context": {
"selected_node_id": 42,
"branch": "main"
}
}
The Q&A system:
- Sends your question + graph context to Claude — it sees the relevant nodes, edges, and narrative context
- Archaeology-aware — when asking from the archaeology view, the agent gets full narrative context including pivots, superseded approaches, and GitHub links
- Stores every interaction — questions and answers are saved with full-text search (FTS5), so you can search past Q&A sessions
- Searchable history —
GET /api/qa/search?q=authfinds past conversations about authentication decisions
This turns the graph into a conversational interface. Instead of manually traversing nodes, ask: "What was tried before the current approach?" or "What connects the auth system to rate limiting?"
# Browse Q&A history
&limit=20
# Search past questions
&limit=10
# Get a specific interaction
Viewing the Graph
Web Viewer
Five views:
| View | Purpose |
|---|---|
| Chains | Decision chains by session—see the story of a feature |
| Timeline | Chronological view merged with git commits |
| Graph | Force-directed interactive visualization |
| DAG | Hierarchical goal→decision→outcome flow |
| Archaeology | Narrative-driven exploration with Q&A |
Features: branch filtering, full-text search with type filters, resizable panels, deep linking, click-to-expand details, keyboard navigation (j/k/g/G/Space), Q&A panel, and auto-refresh.
Node Types
| Type | Purpose | Example |
|---|---|---|
goal |
High-level objective | "Add user authentication" |
option |
Approach considered | "Use JWT tokens" |
decision |
Choice point | "Choose auth method" |
action |
Implementation step | "Added JWT middleware" |
outcome |
Result | "Auth working in prod" |
observation |
Discovery or insight | "JWT tokens too large for mobile" |
revisit |
Pivot point—connects old approach to new | "Reconsidering token strategy" |
Node Status
| Status | Meaning |
|---|---|
active |
Current truth—how things work today |
superseded |
Replaced by a newer approach |
abandoned |
Tried and rejected—dead end |
Edge Types
| Type | Meaning |
|---|---|
leads_to |
Natural progression |
chosen |
Selected this option |
rejected |
Did not select (with reason) |
requires |
Dependency |
blocks |
Preventing progress |
enables |
Makes possible |
supersedes |
New approach replaces old (via revisit) |
Graph Maintenance
Made a mistake? Fix it:
# Remove an edge
# Delete a node (cascades to connected edges)
# Preview before deleting
Keeping AI Integration Updated
When deciduous releases new features, your existing projects can get the latest integration files:
# Check if an update is needed
# Update integration files (auto-detects installed assistants)
The update command auto-detects which assistants are installed and updates them:
Claude Code (.claude/)
| Files | What's Updated |
|---|---|
.claude/commands/*.md |
Slash commands (/decision, /recover, /work, /document, /build-test, /serve-ui, /sync-graph, /decision-graph, /sync) |
.claude/skills/*.md |
Skills (/pulse, /narratives, /archaeology) |
.claude/hooks/*.sh |
Enforcement hooks |
.claude/agents.toml |
Subagent configurations |
CLAUDE.md |
Decision Graph Workflow section (preserves custom content) |
OpenCode (.opencode/)
| Files | What's Updated |
|---|---|
.opencode/plugins/*.ts |
TypeScript hooks (pre-edit, post-commit) |
.opencode/commands/*.md |
Command templates |
.opencode/skills/*/SKILL.md |
Skill definitions |
.opencode/agents/*.md |
Custom deciduous agent |
.opencode/tools/*.ts |
Custom deciduous tool |
.opencode/opencode.json |
Plugin configuration |
AGENTS.md |
Decision Graph Workflow section |
Windsurf (.windsurf/)
| Files | What's Updated |
|---|---|
.windsurf/hooks.json |
Cascade hooks configuration |
.windsurf/hooks/*.sh |
Hook scripts (pre-write, post-command) |
.windsurf/rules/deciduous.md |
Always-on rules for Cascade |
Not touched: Settings files, .deciduous/config.toml, docs/ - your configs stay intact.
Automatic Version Checking
Deciduous always checks crates.io for new versions once per 24 hours via a lightweight hook. The notification varies by severity:
- Patch updates (e.g., 0.13.10 → 0.13.11): quiet one-line notification
- Minor/major updates (e.g., 0.13.x → 0.14.0): prominent banner encouraging upgrade
You can also check manually at any time:
The check is rate-limited (once per 24h), has a 3-second timeout, and never blocks your workflow. Results are cached in .deciduous/.latest_version.
How the Hooks/Plugins Work
Each AI assistant integration includes hooks and plugins that enforce the decision graph workflow:
Pre-Edit Hook (Blocks edits without context)
Before the AI can edit files, it must have logged a recent goal or action node (within 15 minutes). This ensures decisions are captured before code is written.
AI tries to edit → Hook checks for recent node → Blocks if missing → AI logs decision → Edit proceeds
Post-Commit Hook (Reminds to link commits)
After any git commit, the AI is reminded to:
- Create an outcome or action node with
--commit HEAD - Link it to the parent goal/action
This connects your git history to the decision graph.
Version-Check Hook (Notifies of new versions)
Checks crates.io once per 24 hours for newer versions of deciduous. Patch updates get a quiet one-liner; minor/major updates get a prominent banner encouraging upgrade. Always-on, non-blocking.
Session starts → Hook checks cached version → If stale, queries crates.io (3s timeout) → AI tells user
Assistant-Specific Implementation
| Assistant | Pre-Edit | Post-Commit | Version Check |
|---|---|---|---|
| Claude Code | PreToolUse on Edit|Write |
PostToolUse on Bash |
PreToolUse on Bash |
| OpenCode | TypeScript pre-edit |
TypeScript post-commit |
TypeScript pre-tool |
| Windsurf | Cascade pre_write_code |
Cascade post_run_command |
Cascade pre_write_code |
Pre-edit and post-commit hooks use exit code 2 to block/alert. Version-check hooks use exit code 0 (informational, never blocks).
The Premises
-
Decisions are the unit of institutional knowledge. Code tells you what, but decisions tell you why. Six months from now, you won't remember why you chose Redis over Postgres for that cache. The graph will.
-
Structured thinking produces better outcomes. The act of logging a decision—naming it, assigning confidence, connecting it to goals—forces you to think it through.
-
Real-time logging beats retroactive documentation. Capture reasoning in the moment. By the time you write post-hoc docs, you've forgotten the options you rejected.
-
Graphs beat documents. Goals spawn decisions, decisions spawn actions, actions produce outcomes. A graph captures these relationships. You can trace any outcome to its origin.
-
Complex PRs tell a story. A 50-file diff is incomprehensible. A decision graph shows the goal, the key decisions, the rejected approaches, and how each change connects to purpose.
-
Context loss is inevitable. Sessions end. Memory compacts. The graph survives.
-
The graph is a shared workspace. Decisions flow between sessions, between humans and AI, between teammates. The graph doesn't care who's typing—it preserves the reasoning.
Commands Reference
# Initialize
# Add nodes
# Node options
|
# Connect and disconnect
# Delete nodes
# Query
# Visualize
# Export
# Document attachments
# Shell completion
Who Uses Deciduous
You, the developer:
- Think through decisions by structuring them
- Remember why you made choices months later
- Review PRs by understanding the decision flow
- Onboard to codebases by reading decision history
- Ask questions about your own project's history and get grounded answers
Your AI assistant:
- Recover context after compaction or session boundaries
- Build on previous reasoning instead of starting fresh
- Leave a queryable trail for future sessions
- Use
/archaeologyto revisit and correct past decisions - Use
/decision-graphto build decision graphs from commit history - Use
/documentto generate comprehensive docs with test examples - Ask deep questions via the Q&A interface grounded in actual graph data
- Attach relevant documents (diagrams, screenshots, specs) to decision nodes
Your team:
- Share decision context via patch files
- Review PRs with full visibility into reasoning
- Build institutional knowledge that survives turnover
- Search past Q&A interactions to find answers that were already given
Why "deciduous"?
It almost has the word "decision" in it, and they're trees.