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 skills/a5c-ai/babysitter/session-memorynpx skills add a5c-ai/babysitter --skill session-memorygit clone --depth 1 https://github.com/a5c-ai/babysitterWrote 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/a5c-ai/babysitter/session-memory)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/session-memory"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/session-memory.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 | $0.00037 | $0.00416 |
| Opus 5 | $0.00018 | $0.00208 |
| Sonnet 5 | $0.00007 | $0.00083 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
session-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 4d 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
Iron Law
EVERY WORKFLOW MUST:
- LOAD memory at START (and before key decisions)
- UPDATE memory at END (and after learnings/decisions)
Stable Edit Anchors
Safe section headers for Edit operations:
- activeContext:
## Recent Changes,## Learnings,## References - patterns:
## Common Gotchas,## Project SKILL_HINTS - progress:
## Completed,## Verification
Read-Edit-Verify Pattern
- Read file
- Verify anchor exists
- Edit with exact
old_string - Read back to confirm
Tool Rules
- Use
Write()for NEW files (permission-free) - Use
Edit()for EXISTING files (permission-free) - Never use
Write()to overwrite existing files - Never compound commands (
mkdir && cat)
When to Use
- At the start of every CC10X workflow (load)
- At the end of every CC10X workflow (update)
- Before making key decisions (check patterns)
- After discovering learnings or gotchas (persist)
Agents Used
All CC10X agents use this skill. The cc10x-router manages load/update lifecycle.
What ships with it
1 file 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.
- 4d ago First seen · 53 lines · 37 tokens per session scan A fd1e012eaffb
session-memory is a skill published in the GitHub repository a5c-ai/babysitter (1,765 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 416 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 skills, from other repositories
swarm-vault
The vault contract — how any agent reads, writes, and queries the SwarmVault. Use at the start of work in any vault-connected project, before exploring the repo, when deciding where to record memory/plans/decisions/sessions, when handing off between sessions or agents, or whenever unsure how the vault works.
swarm-init
Start a new project connected to the SwarmVault — register it, wire platform adapters, offer git init, set vault-as-default. Use when starting a new project, connecting a project to the vault, or when the user asks to set up SwarmVault in a directory.
swarm-migrate
Bring existing projects into the SwarmVault — register, mirror docs, optionally mine the repo into SDLC artifacts and resume the flow mid-phase (brownfield adoption). Use when the user wants existing projects migrated/connected to the vault, or an existing codebase placed into the SDLC flow.
swarm-eject
Disconnect a project from SwarmVault and choose what happens to its knowledge — keep it, export it into the repo, or delete it. Use when the user wants to stop using SwarmVault here, remove the vault wiring, uninstall the framework from a project, offboard or archive a project, or delete a project's vault data.
codex-mnemo
Codex CLI 과거 대화 검색과 장기기억 설정에 사용한다. notify 훅으로 대화 자동 저장, 키워드 태깅, 과거 검색을 제공한다. /mnemo, 므네모, 장기기억, 기억해, 이전에, handoff, 핸드오프, 세션 저장, codex 기억, codex memory 요청에 사용한다.
list-learned-actions
Explicit Codex workflow: List persisted reusable actions, UI skeletons, and legacy feedback memories before composing device primitives.