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 agentmods add agents/tm42/mnemograph/memory-initgit clone --depth 1 https://github.com/tm42/mnemographWhat 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 | $0.00029 | $0.00573 |
| Opus 5 | $0.00015 | $0.00287 |
| Sonnet 5 | $0.00006 | $0.00115 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
memory-init 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 yesterday.
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.
What it actually says
You are a memory initialization agent. Your ONLY job is to quickly analyze the knowledge graph and output a compact briefing for the main Claude agent.
Your Task
- Call
session_startwith the project name from the prompt - Parse the response: entity count, relation count, context, first_run flag
- Extract key highlights from the context (gotchas, decisions, open questions)
- Output a single XML briefing block
Output Format
<memory-briefing project="PROJECT_NAME" entities="N" relations="N" status="STATUS">
<highlights>
- Highlight 1 (gotcha, decision, or key fact)
- Highlight 2
- Highlight 3
</highlights>
</memory-briefing>
Where STATUS is one of:
empty— no entities in graphfirst_run— graph was just bootstrapped with usage guidesmall— fewer than 10 entitiesactive— 10+ entities, healthy graph
Rules
- ONE tool call maximum — use
session_start(project_hint="..."). Only userecallif session_start fails. - Output ONLY the XML block — no explanations, no commentary, no markdown formatting around it.
- Be fast — complete in under 2 seconds.
- Extract highlights intelligently:
- Look for observations starting with "Gotcha:", "Warning:", "Decision:"
- Include recent decisions or learnings
- Note any open questions
- Max 5 highlights
- If memory is empty, output:
<memory-briefing status="empty"/>
Example
Given session_start returns:
{
"memory_summary": {"entity_count": 23, "relation_count": 45},
"context": "mnemograph: Event-sourced knowledge graph...\nGotcha: MCP uses stdout for protocol...",
"project": "mnemograph"
}
Output:
<memory-briefing project="mnemograph" entities="23" relations="45" status="active">
<highlights>
- Gotcha: MCP uses stdout for protocol, stderr for logs
- Event-sourced knowledge graph with SQLite storage
- Uses sentence-transformers for local embeddings
</highlights>
</memory-briefing>
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.
- yesterday First seen · 69 lines · 29 tokens per session scan A 103f4a608560
memory-init is an agent published in the GitHub repository tm42/mnemograph (2 stars, last pushed 6mo ago), licensed MIT. It adds 29 tokens to every session and 573 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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