Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add divyanshailani/graph-memory --skill graph-memorygit clone --depth 1 https://github.com/divyanshailani/graph-memoryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/divyanshailani/graph-memory/graph-memory)<a href="https://agentmods.dev/skills/divyanshailani/graph-memory/graph-memory"><img src="https://agentmods.dev/badge/skills/divyanshailani/graph-memory/graph-memory/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/divyanshailani/graph-memory/graph-memory"><img src="https://agentmods.dev/badge/skills/divyanshailani/graph-memory/graph-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.00876 |
| Opus 5.5 | $0.00018 | $0.00350 |
| Sonnet 5.5 | $0.00009 | $0.00175 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
graph-memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Graph Memory
A local SQLite knowledge graph at .agents/graph_memory.sqlite that gives AI coding agents long-term project memory. Ingests codebase AST (Python, TypeScript, Go, Rust via Tree-sitter), tracks agent decisions in an append-only ledger, detects contradictions between agents, and produces prompt-cache-stable snapshots.
Installation
pip install epistemic-graph-memory[all]
MCP Server
{"mcpServers":{"graph-memory":{"command":"graph-memory-mcp"}}}
Streamable HTTP (for OpenCode, Docker, remote agents):
graph-memory-mcp-http # http://127.0.0.1:8765/mcp
CLI
Ingest
graph-memory ingest-code . # full codebase AST + call graphs
graph-memory ingest-file src/engine.py # single file re-parse (<5ms)
Snapshots
graph-memory snapshot --max-tokens 600 --min-trust 0.7
Output is deterministic and content-fingerprinted — unchanged graph returns identical bytes so prompt caches stay warm.
Search
graph-memory search "effective_tr" # FTS5 + identifier substring fallback
graph-memory search-sessions "trust decay" # episodic session logs
Decision History
graph-memory query-history --agent Hermes --days 7
graph-memory contradictions # surfaced conflicts between agents
Lifecycle Hooks
graph-memory hook install # auto-configure all 9 frameworks
graph-memory hook install --framework cursor
graph-memory hook status
graph-memory hook refresh # re-render snapshots now
Supported: Claude Code, ZCode, Cursor, Codex, OpenCode, Antigravity, Qoder, Hermes, Claude Desktop.
Events: PostToolUse (incremental AST ingest <5ms), Stop (transcript distillation + fact extraction), SessionStart (snapshot refresh).
Import / Export
graph-memory import-md CLAUDE.md # markdown sections → Knowledge_Nodes
graph-memory import-mem0 memories.json # mem0 JSON → Fact_Nodes
graph-memory export-obsidian ~/vault # Obsidian vault with [[wikilinks]]
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 114 lines · 45 tokens per session scan A 026225609258
graph-memory is a skill published in the GitHub repository divyanshailani/graph-memory (21 stars, last pushed 28d ago), licensed MIT. It adds 45 tokens to every session and 876 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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