Decision Topology

An OpenClaw skill that records the structure of conversations where ideas evolve, branch, get rejected, pivot, or combine. Saves each structural shift as a node in a local JSON tree. Like git for thinking — the structure is always there when you want to inspect it. Zero network access, zero external dependencies.

What It Does

During conversations, the agent records how ideas evolve as a tree structure:

• Proposals — distinct ideas or directions suggested
• Pivots — new directions emerging from rejections
• Merges — insights combining elements from multiple branches
• Kills — rejected paths with captured reasoning

The result is a persistent tree structure that captures why a conversation evolved, not just what was said.

Features

• Low-noise operation — active during every conversation by default, viewable on request
• Auto-association — checks existing trees before creating new ones
• Concept indexing — cross-tree linking via keyword concepts
• ASCII rendering — visual tree display in terminal
• Mermaid export — diagram export for documentation
• Cross-tree analysis — find patterns across multiple explorations
• Companion .md files — auto-generated for semantic search indexing

Install

clawhub install decision-topology

Or manually copy the SKILL.md, scripts/, and references/ folders into your OpenClaw workspace skills directory.

Configuration

Storage: Trees are stored in {baseDir}/trees/ by default. Override with the TOPOLOGY_TREES_DIR environment variable to store trees elsewhere (e.g. in a memory directory for semantic search indexing).

Always-on mode: The skill ships with always: true in its metadata, meaning it is active during every conversation by default. If you prefer on-demand recording only, edit the metadata line in SKILL.md:

# Change always to false — the skill will only record when explicitly invoked
metadata: {"openclaw":{"always":false,"emoji":"🌳","requires":{"bins":["node"]}}}

Usage

The skill runs automatically — no setup needed. The user interacts naturally:

• "Show me what we explored"
• "What did we kill?"
• "What shape is this conversation?"
• "What paths did we reject and why?"
• "Go back to that idea about X"

CLI Commands

Args are piped via stdin to avoid shell injection from user-derived content:

echo '{"topic": "exploration topic"}' | node scripts/topology.js init
echo '{"file": "<path>", "parent_id": "<id>", "type": "proposal", "summary": "description"}' | node scripts/topology.js add-node
echo '{"file": "<path>", "node_id": "<id>", "reason": "why rejected"}' | node scripts/topology.js kill-branch
echo '{"file": "<path>", "source_ids": ["<id1>", "<id2>"], "summary": "merged insight"}' | node scripts/topology.js merge
echo '{"file": "<path>"}' | node scripts/topology.js render
echo '{"file": "<path>"}' | node scripts/topology.js export
node scripts/topology.js list
echo '{"file": "<path>"}' | node scripts/topology.js stats
node scripts/topology.js analyze
echo '{"list": true}' | node scripts/topology.js concept

Example Tree Output

What stack to use for the web app?

(*) What stack to use for the web app?
|-- [x] Use a full React SPA (killed: too heavy for our use case)
|-- [*] Server-rendered with HTMX
|   |-- [x] Go + templ (killed: team doesn't know Go)
|   `-- (*) Node + Express + HTMX
`-- [x] Static site with JS sprinkles (killed: need real-time features)

5 branches explored, 3 killed, 2 active, depth 2

Requirements

• Node.js (any recent version)
• OpenClaw (for skill integration)

Schema

See references/schema.md for the full v2 tree and node schema.

Changelog

See CHANGELOG.md for version history.

License

MIT