memorize.skeleton

A command that reviews the current coding session and saves useful lessons to memory for future work. It focuses on information likely to help an agent when the same situation appears again.

In plain words
What is it for?
Use it to record solutions, hidden codebase rules, common error traps, architecture choices, and user preferences.
Why use it?
It reduces repeated investigation of project conventions, known fixes, recurring mistakes, and important design decisions.

Command

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 commands/varienos/agentic-workflow/memorize.skeleton
Clone the repo
git clone --depth 1 https://github.com/varienos/agentic-workflow
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,713 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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01713
Opus 5 $0.00000 $0.00856
Sonnet 5 $0.00000 $0.00343
Haiku 4.5 $0.00000 $0.00171

Measured 2d ago against content hash 728ae697b937, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memorize.skeleton 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 2d 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.

Agentbase/templates/core/commands/memorize.skeleton.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Memorize — Oturum Ogrenme Kaydedici

Mevcut oturumdaki onemli ogrenimleri analiz eder ve hafizaya kaydeder. Kullanim: /memorize, /memorize "auth modulu icin ogrenilenler"


Felsefe

Her sey kaydetmeye deger degildir. Hafiza, gelecekte TEKRAR KARSILASILDACAK bilgileri saklar. "Bunu bilseydim daha hizli yapardim" testini gec: ileride ayni durumla karsilasan ajan bu bilgiden faydalanir mi?


Step 1 — Oturum Analizi

Mevcut konusmadaki tum etkilesimleri analiz et:

  1. Hangi dosyalar uzerinde calisildi?
  2. Hangi sorunlarla karsilasildi?
  3. Nasil cozulduler?
  4. Beklenmedik durumlar oldu mu?
  5. Kullanici ozel tercihler belirtti mi?

Step 2 — Ogrenimleri Siniflandir

Kaydetmeye Deger Kategoriler

Kategori Aciklama Ornek
Cozum Deseni Belirli bir sorun icin bulunan cozum "Prisma N+1 sorunu include ile cozuldu"
Proje Konvansiyonu Kod tabanindaki kesfedilen gizli kural "Service'ler hep Result<T> donuyor"
Hata Tuzagi Kolay dusulen, zor bulunan hata "useEffect cleanup'i eksik olunca memory leak"
Mimari Karar Neden boyle yapilandirilmis "Auth, gateway'de degil her service'de ayri"
Kullanici Tercihi Kullanicinin belirttigi calisma tercihi "PR aciklamalari Turkce olsun"
Arac Kullanimi Belirli bir aracin kullanim detayi "backlog CLI'da --set flag'i tirnak ister"

Kaydetmeye Deger OLMAYAN Seyler

  • Genel programlama bilgisi (herkes bilir)
  • Tek seferlik islemler (tekrarlanmayacak)
  • Kisisel bilgiler (kullanici hakkinda spesifik olmayan)
  • Cok spesifik debug adimlari (baglamsiz anlamsiz)
  • Zaten dokumantasyonda olan bilgiler

Step 3 — Hafiza Dosyalari Olustur

3.1 — Dosya Formati

Her ogrenme icin ayri bir hafiza dosyasi olustur:

Kutsal Yol Kurali:

  • Agentbase .claude/memory/ dizini icine yaz
  • Codebase icine hafiza dosyasi YAZMA

Read the full file on GitHub · 156 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.

  1. 2d ago First seen · 156 lines · 0 tokens per session scan A 728ae697b937

Subscribe to this mod's changes

memorize.skeleton is a command published in the GitHub repository varienos/agentic-workflow (58 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,713 tokens. 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.