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 skills add fthsrbst/mnema --skill session-handoffgit clone --depth 1 https://github.com/fthsrbst/mnemaWrote 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/fthsrbst/mnema/session-handoff)<a href="https://agentmods.dev/skills/fthsrbst/mnema/session-handoff"><img src="https://agentmods.dev/badge/skills/fthsrbst/mnema/session-handoff/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/fthsrbst/mnema/session-handoff"><img src="https://agentmods.dev/badge/skills/fthsrbst/mnema/session-handoff.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00068 | $0.00359 |
| Opus 5.5 | $0.00027 | $0.00144 |
| Sonnet 5.5 | $0.00014 | $0.00072 |
| Haiku 4.5 | $0.00007 | $0.00036 |
Grade A, and why
session-handoff 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 1mo 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
Session Handoff
Amaç: bir sonraki oturum — hangi cihazda, hangi agent'la olursa olsun — kaldığı yerden devam edebilsin.
Adımlar
- Oturumu özetle (markdown, kısa ve bilgi yoğun):
## Yapılanlar - ... ## Yarım kalanlar / bilinen sorunlar - ... (dosya/satır referanslı) ## Sıradaki adım - ... (net, eyleme dönük tek cümleler) session_log(summary, project)çağır.- Bu oturumda karar alındıysa ve henüz kaydedilmediyse: her biri için
memory_save(type=decision, gerekçeli) veyaproject_add_decision. - Proje odağı değiştiyse
project_updateilecurrent_focus+next_stepsgüncelle.
Kurallar
- Özet, kodu görmemiş birinin anlayacağı dilde olsun; oturum içi kısaltmalar kullanma.
- Yarım kalan işte "neden yarım kaldı"yı yaz (bloker neydi).
- 10 dakikalık önemsiz oturum için log bırakma; sinyal/gürültü oranını koru.
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.
- 1mo ago First seen · 28 lines · 68 tokens per session scan A b9873b9c2f38
session-handoff is a skill published in the GitHub repository fthsrbst/mnema (2 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 359 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
reflect
Use Recall Reflect to review AI coding workflow history as a conversation-first timeline and discuss observed patterns before changing behavior. Trigger when the user asks to reflect on a project, review AI coding workflow, inspect workflow friction, discuss repeated corrections, review handoffs, or explore possible…
day-log
Quick timestamped log entry — no conversation, just capture.
period-summary
Period summary (w/m/q/y) — reflect on the period, score it, close it out.
day-start
Day briefing — deliver context, capture what's happened, get moving.
anyr
Use when reading, searching, creating, or updating Anytype documents (objects, spaces, types, properties, files, chats) from the command line with the configured anyr CLI, including JSON output patterns for scripting.
create-speech-recording-desktop
Create and embed a speech recording in ChatGPT Desktop (Codex), Antigravity App, OpenCode Desktop, or T3 Code.