Shared-memory instructions for coding agents. The hub is a persistent store where agents on different devices can save and retrieve project context, decisions, and session notes.

Use them at the start of coding tasks, when checking why a technical decision was made, when finding where previous work stopped, and when recording durable project knowledge.

They help an agent recover important context after a session ends and avoid repeating earlier investigation. They also describe when to search for project facts or save new information.

hub-memory — Skill for Claude Code and Codex by fthsrbst: Shared-memory instructions for coding agents.

Install

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.

agentmods

npx agentmods add skills/fthsrbst/mnema/hub-memory

Any agent

npx skills add fthsrbst/mnema --skill hub-memory

Clone the repo

git clone --depth 1 https://github.com/fthsrbst/mnema

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/fthsrbst/mnema/hub-memory.svg)](https://agentmods.dev/skills/fthsrbst/mnema/hub-memory)

Your own site

<a href="https://agentmods.dev/skills/fthsrbst/mnema/hub-memory"><img src="https://agentmods.dev/badge/skills/fthsrbst/mnema/hub-memory.svg" alt="Measured on agentmods" height="20"></a>

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,495 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00066	$0.01495
Opus 5	$0.00033	$0.00747
Sonnet 5	$0.00013	$0.00299
Haiku 4.5	$0.00007	$0.00150

Measured 5d ago against content hash 749a826a2160, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

hub-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 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.

skills/hub-memory/SKILL.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hub Hafıza Kullanımı — Katmanlı Bağlam

Hub, tüm cihazlardaki tüm agentların paylaştığı hafızadır. Sen kapanınca bağlamın silinir; hub silinmez. Bağlam üç katmandır: otomatik gelen (bridge/recall), görev başında çektiğin (project_get/memory_search), çalışırken yazdığın (memory_save/session_log). Doğru davranış katmanına göre değişir.

Katman 1 — Otomatik gelen (okuman yeter)

<hub-bridge> (oturum başı): aktif projenin map'i + son oturum özeti. Kaldığın yeri buradan al. Map'in gerçekle çeliştiğini görürsen görevin ortasında bile project_update ile düzelt.
<hub-recall> (mesaj başı): mesajla yüksek benzerlikli az sayıda kayıt. Sistem bilinçli olarak az ve isabetli enjekte eder; boş olması "hafızada yok" demek değildir — şüphen varsa Katman 2'ye in.

Katman 2 — Görev başında sen çek

Projede çalışıyorsan ve bridge gelmediyse project_get(name): özet, stack, kararlar, odak, sıradaki adımlar + kod haritası (architecture/modules/entry_points/commands).
"Neden X kullanıyoruz", "bunu daha önce nasıl çözmüştük" → memory_search(query).
Doküman/öğrenme notu/araştırma arşivi → rag_search(query).
"Nerede kalmıştım" → session_recent(project).

Katman 3 — Çalışırken yaz

Durum	Aksiyon
Teknik karar alındı (kütüphane, mimari, yaklaşım)	`memory_save` type=decision — gerekçeyi mutlaka yaz
Zor bir bug çözüldü	`memory_save` type=howto — belirti, kök neden, çözüm
Kullanıcı tercih belirtti (stil, araç, workflow)	`memory_save` type=preference
Tekrar lazım olacak komut/kurulum/config	`memory_save` type=howto
Uzun araştırma/öğrenme çıktısı, doküman, talimat/prompt metni	`rag_add` — memory DEĞİL (öğrenme notu: project='learning', uri='learning/')

Kayıt kalite kuralları

Ölçüt: "Başka bir cihazdaki agent 2 hafta sonra bundan faydalanır mı?" Hayırsa kaydetme (oturuma özel detay, koddan/git'ten okunabilen şey, geçici durum).
Boyut: memory "bir bakışta okunur tek bilgi"dir. Gövde ~1500 karakteri aşıyorsa büyük ihtimalle doküman yazıyorsun → rag_add.
project alanı: project_list'teki kanonik ad. Makine/cihaz adı (fatih-pc gibi) proje DEĞİLDİR — cihaza özgü bilgiye tags ekle. Yeni gerçek proje açılıyorsa önce project_update ile map oluştur.
importance: varsayılan 1 çoğu kayıt için doğrudur. 2 = aylar sonra bile öne geçmesi gereken kritik karar/tercih (nadir!). 0.5 = önemsiz detay. Enflasyon skorlamayı bozar.
Dedup: memory_save benzer kayıt uyarısı dönerse ciddiye al — mevcut kaydı memory_update ile zenginleştir, yeni açtığını memory_delete ile geri al.
Yanlışlanan bilgiyi gördüğün an düzelt (memory_update) veya sil (memory_delete). Çelişkili hafıza, hafızasızlıktan kötüdür.

Read the full file on GitHub · 45 lines

Changes

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 · 45 lines · 66 tokens per session scan A 749a826a2160

Subscribe to this mod's changes

hub-memory is a skill published in the GitHub repository fthsrbst/mnema (2 stars, last pushed 6d ago), licensed MIT. It adds 66 tokens to every session and 1,495 once invoked, about $0.0003 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.

Memory and context ai-agents claude cli codex local-first mcp

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