memory

memory is a skill for Claude Code from angad-kandhari/deliberate. It costs 87 tokens per session (1,536 once invoked), scanned A, original, Apache-2.0.

Guidance for managing notes that an AI coding agent carries between sessions, such as AGENTS.md files, memory banks, or automatic memory. It explains what to remember, how to organize it, and when to remove outdated information.

In plain words
What is it for?
Use it when creating, reviewing, pruning, or structuring agent memory and other notes that future coding sessions will read.
Why use it?
Persistent notes can become bloated, stale, or contradictory and cause future agents to make poor decisions. This keeps only information that changes future work and cannot easily be rediscovered.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; mentions AGENTS.md.

Part of the deliberate plugin — 13 skills, 1 hook shipped together

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/angad-kandhari/deliberate/memory
Any agent
npx skills add angad-kandhari/deliberate --skill memory
Clone the repo
git clone --depth 1 https://github.com/angad-kandhari/deliberate

Made for: Claude Code.

Or install deliberate, the plugin that ships this one along with the rest of its 13 skills, 1 hook.

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.

agentmods badge for memory

README.md
[![agentmods](https://agentmods.dev/badge/skills/angad-kandhari/deliberate/memory.svg)](https://agentmods.dev/skills/angad-kandhari/deliberate/memory)
Your own site
<a href="https://agentmods.dev/skills/angad-kandhari/deliberate/memory"><img src="https://agentmods.dev/badge/skills/angad-kandhari/deliberate/memory.svg" alt="Measured on agentmods" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,536 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 5.1 $0.00087 $0.01536
Opus 5 $0.00044 $0.00768
Sonnet 5 $0.00017 $0.00307
Haiku 4.5 $0.00009 $0.00154

Measured 6d ago against content hash a8fd13ee771b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

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 6d 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/memory/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Memory

Memory skill for LLM coding agents. Load this when the agent keeps persistent memory across sessions — CLAUDE.md, AGENTS.md, auto-memory, a memory-bank directory, or any notes file a future session will read.

Where deliberate keeps code honest, this skill keeps what the agent remembers honest. Counters the failure modes of agent memory: bloat that buries the signal, stale entries acted on confidently, contradictory duplicates, and notes that restate what the repo already records.

How memory is stored and loaded is the harness's job. What gets written, kept, believed, and deleted is judgment — this skill governs that. The evidence is blunt: agents that record everything perform far worse than agents that record little and prune. Curation beats architecture.


1. Write Selectively

A memory earns its place by changing future behavior. Most things don't.

Before writing, both must hold:

  • It will change what a future session does. A preference, a constraint, a correction, a decision with a why. Not narration of what happened.
  • It can't be re-derived. If the next session could learn it from the repo, the docs, or one obvious command, writing it down is duplication, not memory.

The strongest write signal is repetition: the same mistake twice, the same correction twice, the same question twice. Once is an event; twice is a pattern worth a note.

Test: Will a future session act differently because this entry exists?


2. Never Record What the Repo Already Knows

The repo is the source of truth. A memory that copies it is guaranteed to drift from it.

Don't store:

  • Code structure, file locations, function signatures — the file tree and search answer these fresh and correctly every time.
  • Dependency lists, versions, scripts — the manifest already says.
  • What changed and when — git history says, with proof.
  • Anything a README, CLAUDE.md, or doc already states.

Store instead what the repo can't say: why a decision went this way, which approach was tried and rejected, what the user corrected, constraints that live outside the code.

Read the full file on GitHub · 133 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. 6d ago First seen · 133 lines · 87 tokens per session scan A a8fd13ee771b

Subscribe to this mod's changes

memory is a skill published in the GitHub repository angad-kandhari/deliberate (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 87 tokens to every session and 1,536 once invoked, about $0.0004 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.

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