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lore: Instructions file for Claude Code

CLAUDE.md

lore CLAUDE.md is an instructions file for Claude Code from agentkitai/lore. It costs 535 tokens per session, scanned A, original, MIT.

Instructions for using Lore, a persistent memory system that stores and retrieves information across coding sessions.

In plain words
What is it for?
Use it at session start, while debugging, after solving unusual problems, and before major context changes.
Why use it?
It helps an agent remember earlier decisions, lessons, and preferences instead of starting from scratch each session.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md.

This is agentkitai/lore's own configuration. It tells Claude Code how to work on lore itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything lore configures →

not rated 10repo 5d ago A scan 535 tokens original MIT
View source ↗ agentkitai/lore
Reuse

Borrowing it

Nothing to install: this file belongs to agentkitai/lore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/agentkitai/lore/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/agentkitai/lore

Made for: Claude Code.

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Per session 535 This file is loaded in full into every session.
When invoked 535 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00535 $0.00535
Opus 5.5 $0.00214 $0.00214
Sonnet 5.5 $0.00107 $0.00107
Haiku 4.5 $0.00053 $0.00053

Measured 2mo ago against content hash 39f4ed6b4069, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lore CLAUDE.md 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 2mo 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.

CLAUDE.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lore — Universal AI Memory

You have access to Lore, a persistent memory system via MCP tools. Use it to remember context across sessions and recall relevant knowledge.

When to Use Lore

Session Start

Call recent_activity(hours=24) to load what happened recently. This gives you grouped context from the last day — decisions, lessons, work done.

During Work

  • Before debugging: recall("describe the problem") — check if this was solved before
  • After solving something non-obvious: remember("what you learned", type="lesson")
  • Key decisions: remember("decision and reasoning", type="note")
  • Preferences discovered: remember("user prefers X", type="preference")

Pre-Compaction (Automatic)

Lore's session accumulator auto-saves snapshots when your context grows large. You don't need to manually call save_snapshot — but you can if you want to preserve specific state before a complex transition:

save_snapshot(content="Current state: ...", title="mid-refactor checkpoint")

Key Tools

Tool When
recall(query) Search memories semantically
remember(content, type) Save a memory (types: note, lesson, fact, preference, pattern, convention)
recent_activity(hours) Load recent session context
save_snapshot(content) Manually checkpoint current state
suggest(context) Get proactive memory recommendations based on session context
topics() Browse auto-generated topic summaries
graph_query(query) Explore knowledge graph connections
entity_map(name) Find everything related to an entity
review_digest() Review pending graph connections (with risk scores)
on_this_day() Memories from this date in prior years
export(format) Export all data (json/markdown)

Types for remember

  • lesson — Bug fixes, gotchas, things learned the hard way
  • fact — Objective information (API endpoints, config values, specs)
  • preference — User preferences, style choices
  • pattern — Recurring patterns or anti-patterns
  • convention — Project conventions, naming rules
  • note — General notes, decisions, context

Read the full file on GitHub · 55 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. 2mo ago First seen · 55 lines · 535 tokens per session scan A 39f4ed6b4069

Subscribe to this mod's changes

lore CLAUDE.md is an instructions file published in the GitHub repository agentkitai/lore (10 stars, last pushed 5d ago), licensed MIT. It adds 535 tokens to every session, about $0.0021 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.

Memory and contextPythonai-agentscross-agentknowledge-graphmcp
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