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---
name: mindgraph-rs-127917346dd3
description: "A high-performance, structured knowledge graph memory system for AI agents. Provides 18 cognitive tools for reasoning, decision tracking, and goal management. Runs fully local β no cloud, no external graph store. PRIVACY: The server never calls home. The optional extraction scripts read session transcripts and send summaries to your configured LLM provider (Gemini/Anthropic/Moonshot) β same provider your agent already uses. Extraction and dreaming are opt-in."
---
# MindGraph π§
MindGraph transforms AI memory from flat text files into a traversable, evidence-backed cognitive layer. It runs entirely on your machine using a Rust server backed by CozoDB, with a strict 28-node ontology and built-in vector search.
---
## Quick Start
```bash
# 1. Install the skill
clawhub install mindgraph-rs
# 2. Download the server binary (Linux x86_64)
bash skills/mindgraph-rs/scripts/setup.sh
# 3. Start the server
bash skills/mindgraph-rs/scripts/start.sh
# 4. Use the client in your agent
const mg = require('./skills/mindgraph-rs/scripts/mindgraph-client.js');
await mg.ingest('My first observation', 'Something worth remembering.', 'observation');
# 5. (Optional) Register the bootstrap hook for automatic context injection
# See "Bootstrap Context Injection" section below
```
> **Not on Linux x86_64?** See [INTEGRATION.md](references/INTEGRATION.md) for build-from-source instructions.
---
## How It Works
The skill has two parts:
| Component | What it does | External calls? |
|-----------|-------------|-----------------|
| **mindgraph-server** | Stores and queries the graph (CozoDB + vector search) | β None β fully local |
| **extract.js + scripts** | Reads session transcripts, extracts nodes via LLM | β
To your configured LLM provider (opt-in) |
Graph data never leaves your machine. Extraction uses the same LLM provider your agent already trusts.
---
## β οΈ Privacy Disclosure
The extraction scripts (`extract.js`, heartbeat flow) read your conversation transcripts and send excerpts to your LLM provider for summarization and node extraction. Specifically:
- **Reads:** Session JSONL transcripts from `agents/main/sessions/`
- **Reads:** `~/.openclaw/openclaw.json` to find your provider API keys
- **Transmits:** Conversation summaries to your configured LLM (Gemini, Anthropic, or Moonshot)
**What is NOT transmitted:** Raw transcripts, graph database contents, or any data to ClawHub or MindGraph maintainers.
You can use the server + 18 cognitive tools entirely without extraction β see [INTEGRATION.md](references/INTEGRATION.md).
---
## The 18 Cognitive Tools
Use these via `mindgraph-client.js` β never add nodes manually.
### Reality Layer
- `mg.ingest` β Capture sources, snippets, or observations
- `mg.manageEntity` β Create, alias, or merge entities (Person, Org, Concept, etc.)
### Epistemic Layer (Reasoning)
- `mg.addArgument` β Atomic Toulmin bundle (Claim + Evidence + Warrant)
- `mg.addInquiry` β Record hypotheses, anomalies, and open questions
- `mg.addStructure` β Crystallize concepts, patterns, and models
### Intent Layer (Commitments)
- `mg.addCommitment` β Declare goals, projects, or milestones
- `mg.deliberate` β Open decisions, add options, resolve choices
### Action Layer (Workflows)
- `mg.procedure` β Design flows, steps, and affordances
- `mg.risk` β Assess severity and likelihood for any node
### Memory Layer (Persistence)
- `mg.sessionOp` β Open, trace, and close conversational sessions
- `mg.distill` β Synthesize sessions into durable summaries
- `mg.memoryConfig` β Manage system-wide preferences and policies
### Agent Layer (Control)
- `mg.plan` β Create tasks and execution steps
- `mg.governance` β Set safety budgets and request approvals
- `mg.execution` β Register agent runs and track outcomes
### Connective Tissue
- `mg.retrieve` β Unified search (text, semantic, goals, questions)
- `mg.traverse` β Navigate graph (chains, neighborhood, paths, subgraphs)
- `mg.evolve` β Mutate, tombstone (cascade), and decay salience
---
## Design Principles
1. **Text is canonical; graph is logic** β Your Markdown files remain the source of truth. MindGraph provides relational logic and fast retrieval on top.
2. **Tools > nodes** β Always use the 18 cognitive tools, never raw node creation.
3. **Epistemic separation** β Separate speculation from verified facts.
4. **Opt-in extraction** β The server works fully without any scripts.
---
## Client API Example
```javascript
const mg = require('./skills/mindgraph-rs/scripts/mindgraph-client.js');
// Evidence-backed reasoning
await mg.addArgument({
claim: { label: "System is ready for launch", content: "All milestones completed." },
evidence: [{ label: "QA Report", description: "Zero critical bugs in final audit." }],
warrant: { label: "Launch policy", explanation: "Zero critical bugs = launch ready." }
});
// Session framing
const { session_uid } = await mg.sessionOp({ action: 'open', label: 'Morning review' });
await mg.sessionOp({ action: 'trace', sessionUid: session_uid, note: 'Checked Q1 goals.' });
// Semantic search
const results = await mg.retrieve('active_goals');
```
---
## Bootstrap Context Injection (OpenClaw Hook)
MindGraph ships an OpenClaw hook that automatically injects graph context into every session before your agent reads its first message β no manual `mg.retrieve()` calls needed at startup.
**What it injects into `BOOTSTRAP.md`:**
- Active Goals, Projects, Constraints, recent Decisions and Observations (fixed queries)
- Top 6 semantically relevant nodes based on your recent daily notes (dynamic, requires `OPENAI_API_KEY`)
### Setup (OpenClaw)
**1. Register the hook in `openclaw.json`:**
```json
{
"hooks": [
{
"event": "agent:bootstrap",
"handler": "skills/mindgraph-rs/hooks/mindgraph-context/handler.ts"
}
]
}
```
**2. Add `OPENAI_API_KEY` to your workspace `.env`** (for semantic search at bootstrap):
```bash
echo "OPENAI_API_KEY=sk-..." >> ~/.openclaw/workspace/.env
```
**3. Restart the gateway** β the hook fires on every new session automatically.
**For sub-agents and crons:** Pass a task description via a `.mindgraph-task-{sessionId}.tmp` file in the workspace β the hook will use it for task-specific semantic context retrieval instead of daily notes.
> The hook is fully silent on failure β it never blocks session start.
---
## References
- [INTEGRATION.md](references/INTEGRATION.md) β Full setup guide, binary install, build from source, OpenClaw service config
- [SCHEMA.md](references/SCHEMA.md) β Complete 28-node ontology and edge types
- [API.md](references/API.md) β Detailed signatures for all 18 tools
- [MAINTENANCE.md](references/MAINTENANCE.md) β Heartbeat watchdog, nightly dreaming, and graph hygiene
---
name: mindgraph-rs-127917346dd3
description: "A high-performance, structured knowledge graph memory system for AI agents. Provides 18 cognitive tools for reasoning, decision tracking, and goal management. Runs fully local β no cloud, no external graph store. PRIVACY: The server never calls home. The optional extraction scripts read session transcripts and send summaries to your configured LLM provider (Gemini/Anthropic/Moonshot) β same provider your agent already uses. Extraction and dreaming are opt-in."
---
# MindGraph π§
MindGraph transforms AI memory from flat text files into a traversable, evidence-backed cognitive layer. It runs entirely on your machine using a Rust server backed by CozoDB, with a strict 28-node ontology and built-in vector search.
---
## Quick Start
```bash
# 1. Install the skill
clawhub install mindgraph-rs
# 2. Download the server binary (Linux x86_64)
bash skills/mindgraph-rs/scripts/setup.sh
# 3. Start the server
bash skills/mindgraph-rs/scripts/start.sh
# 4. Use the client in your agent
const mg = require('./skills/mindgraph-rs/scripts/mindgraph-client.js');
await mg.ingest('My first observation', 'Something worth remembering.', 'observation');
# 5. (Optional) Register the bootstrap hook for automatic context injection
# See "Bootstrap Context Injection" section below
```
> **Not on Linux x86_64?** See [INTEGRATION.md](references/INTEGRATION.md) for build-from-source instructions.
---
## How It Works
The skill has two parts:
| Component | What it does | External calls? |
|-----------|-------------|-----------------|
| **mindgraph-server** | Stores and queries the graph (CozoDB + vector search) | β None β fully local |
| **extract.js + scripts** | Reads session transcripts, extracts nodes via LLM | β
To your configured LLM provider (opt-in) |
Graph data never leaves your machine. Extraction uses the same LLM provider your agent already trusts.
---
## β οΈ Privacy Disclosure
The extraction scripts (`extract.js`, heartbeat flow) read your conversation transcripts and send excerpts to your LLM provider for summarization and node extraction. Specifically:
- **Reads:** Session JSONL transcripts from `agents/main/sessions/`
- **Reads:** `~/.openclaw/openclaw.json` to find your provider API keys
- **Transmits:** Conversation summaries to your configured LLM (Gemini, Anthropic, or Moonshot)
**What is NOT transmitted:** Raw transcripts, graph database contents, or any data to ClawHub or MindGraph maintainers.
You can use the server + 18 cognitive tools entirely without extraction β see [INTEGRATION.md](references/INTEGRATION.md).
---
## The 18 Cognitive Tools
Use these via `mindgraph-client.js` β never add nodes manually.
### Reality Layer
- `mg.ingest` β Capture sources, snippets, or observations
- `mg.manageEntity` β Create, alias, or merge entities (Person, Org, Concept, etc.)
### Epistemic Layer (Reasoning)
- `mg.addArgument` β Atomic Toulmin bundle (Claim + Evidence + Warrant)
- `mg.addInquiry` β Record hypotheses, anomalies, and open questions
- `mg.addStructure` β Crystallize concepts, patterns, and models
### Intent Layer (Commitments)
- `mg.addCommitment` β Declare goals, projects, or milestones
- `mg.deliberate` β Open decisions, add options, resolve choices
### Action Layer (Workflows)
- `mg.procedure` β Design flows, steps, and affordances
- `mg.risk` β Assess severity and likelihood for any node
### Memory Layer (Persistence)
- `mg.sessionOp` β Open, trace, and close conversational sessions
- `mg.distill` β Synthesize sessions into durable summaries
- `mg.memoryConfig` β Manage system-wide preferences and policies
### Agent Layer (Control)
- `mg.plan` β Create tasks and execution steps
- `mg.governance` β Set safety budgets and request approvals
- `mg.execution` β Register agent runs and track outcomes
### Connective Tissue
- `mg.retrieve` β Unified search (text, semantic, goals, questions)
- `mg.traverse` β Navigate graph (chains, neighborhood, paths, subgraphs)
- `mg.evolve` β Mutate, tombstone (cascade), and decay salience
---
## Design Principles
1. **Text is canonical; graph is logic** β Your Markdown files remain the source of truth. MindGraph provides relational logic and fast retrieval on top.
2. **Tools > nodes** β Always use the 18 cognitive tools, never raw node creation.
3. **Epistemic separation** β Separate speculation from verified facts.
4. **Opt-in extraction** β The server works fully without any scripts.
---
## Client API Example
```javascript
const mg = require('./skills/mindgraph-rs/scripts/mindgraph-client.js');
// Evidence-backed reasoning
await mg.addArgument({
claim: { label: "System is ready for launch", content: "All milestones completed." },
evidence: [{ label: "QA Report", description: "Zero critical bugs in final audit." }],
warrant: { label: "Launch policy", explanation: "Zero critical bugs = launch ready." }
});
// Session framing
const { session_uid } = await mg.sessionOp({ action: 'open', label: 'Morning review' });
await mg.sessionOp({ action: 'trace', sessionUid: session_uid, note: 'Checked Q1 goals.' });
// Semantic search
const results = await mg.retrieve('active_goals');
```
---
## Bootstrap Context Injection (OpenClaw Hook)
MindGraph ships an OpenClaw hook that automatically injects graph context into every session before your agent reads its first message β no manual `mg.retrieve()` calls needed at startup.
**What it injects into `BOOTSTRAP.md`:**
- Active Goals, Projects, Constraints, recent Decisions and Observations (fixed queries)
- Top 6 semantically relevant nodes based on your recent daily notes (dynamic, requires `OPENAI_API_KEY`)
### Setup (OpenClaw)
**1. Register the hook in `openclaw.json`:**
```json
{
"hooks": [
{
"event": "agent:bootstrap",
"handler": "skills/mindgraph-rs/hooks/mindgraph-context/handler.ts"
}
]
}
```
**2. Add `OPENAI_API_KEY` to your workspace `.env`** (for semantic search at bootstrap):
```bash
echo "OPENAI_API_KEY=sk-..." >> ~/.openclaw/workspace/.env
```
**3. Restart the gateway** β the hook fires on every new session automatically.
**For sub-agents and crons:** Pass a task description via a `.mindgraph-task-{sessionId}.tmp` file in the workspace β the hook will use it for task-specific semantic context retrieval instead of daily notes.
> The hook is fully silent on failure β it never blocks session start.
---
## References
- [INTEGRATION.md](references/INTEGRATION.md) β Full setup guide, binary install, build from source, OpenClaw service config
- [SCHEMA.md](references/SCHEMA.md) β Complete 28-node ontology and edge types
- [API.md](references/API.md) β Detailed signatures for all 18 tools
- [MAINTENANCE.md](references/MAINTENANCE.md) β Heartbeat watchdog, nightly dreaming, and graph hygiene
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.