Borrowing it
Nothing to install: this file belongs to AIOSAI/AIPass. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AIOSAI/AIPass/main/.agents/skills/memo/SKILL.mdgit clone --depth 1 https://github.com/AIOSAI/AIPassWrote 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/aiosai/aipass/memo)<a href="https://agentmods.dev/skills/aiosai/aipass/memo"><img src="https://agentmods.dev/badge/skills/aiosai/aipass/memo/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/aiosai/aipass/memo"><img src="https://agentmods.dev/badge/skills/aiosai/aipass/memo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.00284 |
| Opus 5.5 | $0.00011 | $0.00114 |
| Sonnet 5.5 | $0.00006 | $0.00057 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
memo 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
Memory Update
Purpose: Update branch memory files after completing work this session.
Execution
- Read
.trinity/passport.jsonfirst — re-absorb your identity, role, and principles before writing memories - Review what was done this session (context, recent changes, key decisions)
- Update each file below as needed
- Confirm completion — list files updated
Memory Roles
Each memory file plays a distinct role. Update based on what actually changed this session.
.trinity/passport.json— IDENTITY. Who you are: role, capabilities, principles. Only update if identity genuinely evolved this session. Don't touch it just to touch it..trinity/local.json— YOUR MEMORY. Session history and key_learnings. Add a session entry for significant work. Add key_learnings for facts you'd need next time. Trim oldest sessions if over 20..trinity/observations.json— YOUR MEMORY OF THE USER. Collaboration insights, preferences, friction points, flow states. Skip entirely if nothing new about the user this session.
If Relevant
- README.md — Does it reflect current state? Update if stale.
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 Changed · -6 lines a6b612774261
- 1mo ago First seen · 34 lines · 28 tokens per session scan A 3a5d2cc8d057
memo is a skill published in the GitHub repository AIOSAI/AIPass (306 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 284 once invoked, about $0.0001 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.
Other skills, from other repositories
learning-capture
Log corrections, errors, and discoveries to orbital/LESSONS.md so future sessions avoid repeating mistakes.
aura
Give this agent a real email address, a webhook URL, durable memory across runs, and the ability to wait for an event without burning tokens. Use when a task needs a verification code sent by email, needs to wait for a webhook or an approval, needs to remember something after the session ends, or needs to survive a…
squad-bootstrap
Skill de inicialização da squad. Faz a varredura do projeto e popula a memória técnica e de negócios em memories/. ATENÇÃO - SÓ DEVE ser executada se houver solicitação explícita do usuário ("instalar a squad", "fazer setup inicial", "bootstrap do projeto") ou logo após o instalador (install.sh) ter configurado a…
compound
Persistência de aprendizados nas memórias vivas ao final de cada ciclo. Use para "atualizar memória", "guardar aprendizados" ou "sincronizar contexto do projeto". Executada pelo Tech Lead após o PO definir Status entregue.
agentic-loop
Run long-lived autonomous agent loops with persistent memory, context-window compaction, self-healing retries, and resumable state. Use when an AI coding agent must retain progress across sessions, recover from failures, or avoid context exhaustion.
memory-system
A guide to giving an AI agent persistent, user-specific memory across conversations. It covers what to remember, how to store it, how to update or compress it, and when to use memory instead of a shared knowledge base.