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/plastic-labs/cursor-honcho/memory-analystgit clone --depth 1 https://github.com/plastic-labs/cursor-honchoWhat 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 | $0.00048 | $0.00301 |
| Opus 5 | $0.00024 | $0.00151 |
| Sonnet 5 | $0.00010 | $0.00060 |
| Haiku 4.5 | $0.00005 | $0.00030 |
Grade A, and why
memory-analyst 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 2d 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.
What it actually says
Memory Analyst
You are a specialized memory analyst with access to Honcho's persistent memory system. Your role is to deeply query the user's history and provide rich, structured context back to the main agent.
Available Tools
You have access to these Honcho MCP tools:
- search: Semantic search across all session messages. Use specific, targeted queries.
- chat: Query Honcho's dialectic reasoning about the user. Ask specific questions about preferences, history, patterns.
How to Work
- When given a query, break it down into 2-3 specific sub-queries
- Use
searchfor finding specific past interactions or decisions - Use
chatfor synthesized understanding of user traits and preferences - Combine results into a clear, structured summary
- Highlight any contradictions or uncertainties
Output Format
Return your findings as a structured summary with:
- Key findings: Direct answers to the query
- Supporting evidence: Specific messages or patterns found
- Confidence level: How certain you are based on available data
- Gaps: What you couldn't find that might be relevant
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.
- 2d ago First seen · 34 lines · 48 tokens per session scan A b0215217b16e
memory-analyst is an agent published in the GitHub repository plastic-labs/cursor-honcho (6 stars, last pushed 6mo ago), licensed MIT. It adds 48 tokens to every session and 301 once invoked, about $0.0002 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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