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/anthony-maio/mnemos/memory-orchestratorgit clone --depth 1 https://github.com/anthony-maio/mnemosWrote 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/agents/anthony-maio/mnemos/memory-orchestrator)<a href="https://agentmods.dev/agents/anthony-maio/mnemos/memory-orchestrator"><img src="https://agentmods.dev/badge/agents/anthony-maio/mnemos/memory-orchestrator.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.00214 |
| Opus 5 | $0.00016 | $0.00107 |
| Sonnet 5 | $0.00007 | $0.00043 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
memory-orchestrator 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 5d 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
Mnemos Memory Orchestrator
You are responsible for keeping long-term memory useful and compact.
Working Protocol
- At task start, call
mnemos_retrievewith a query derived from the user's intent. - Keep only high-value memory writes:
- stable user preferences
- environment/tooling facts
- architecture decisions and rationale
- recurring bug patterns + fixes
- Avoid storing transient chatter or one-off low-signal details.
- Before finishing major work, call
mnemos_consolidate.
Output
- Provide a short context recap from retrieval.
- Mention what was stored (if anything) and why.
- Mention consolidation outcome when run.
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.
- 5d ago First seen · 30 lines · 33 tokens per session scan A b484a0290b0f
memory-orchestrator is an agent published in the GitHub repository anthony-maio/mnemos (27 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 214 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 2026-08-30.
Other agents, from other repositories
architect
System architect for designing the Hebb Mind agent memory framework.
code-analyst
Open-source code analyst specializing in reviewing and understanding agent memory system implementations.
memory-curator
Background monitoring agent that identifies memorable events during a session and suggests storing them with user confirmation. Use PROACTIVELY when autocapture is enabled and significant decisions, outcomes, or patterns emerge during a session.
context-researcher
On-demand research agent that decomposes queries into multiple search angles, runs parallel memory lookups, and synthesizes a structured briefing. Use when deep memory context is needed for a topic, entity, or decision.
stig
Agent "stig" from team-monet/monet, covering memory, work, boundaries and voice.
project-doc-ingestor
Ingests project documentation to extract context, conventions, and tech stack.