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 agentmods add instructions/emson/elfmem/claude-mdgit clone --depth 1 https://github.com/emson/elfmemWhat 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 | $0.03404 | $0.03404 |
| Opus 5 | $0.01702 | $0.01702 |
| Sonnet 5 | $0.00681 | $0.00681 |
| Haiku 4.5 | $0.00340 | $0.00340 |
Grade A, and why
elfmem 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 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.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
elf — Adaptive Memory for LLM Agents
elf (elfmem package) is a self-aware adaptive memory system. Agents learn, reinforce, and forget knowledge the way biological memory works — fast ingestion, deep consolidation at pauses, decay-based archival at rest. SQLite-backed. Zero infrastructure.
Core Mental Model
Four rhythms (every design decision maps to one of these):
- Heartbeat —
learn(): milliseconds, no LLM, pure inbox insert - Breathing —
dream()/consolidate(): seconds, LLM-powered dedup + contradiction detection - Sleep —
curate(): minutes, decay archival + graph pruning + top-K reinforcement - Deep Sleep —
dream(rescore=True)/rescore(): re-evaluates aged active blocks against the current SELF; keeps alignment / summary / tags fresh as the agent's identity drifts (v0.13.3)
Four frames — always select before retrieving context:
self · attention · task · simulate
(simulate is the Theory-of-Mind frame: blends self constitution with mind/* blocks to reason about modelled minds.)
Knowledge lifecycle: BIRTH → GROWTH → MATURITY → DECAY → ARCHIVE Decay is session-aware (holidays don't kill knowledge). Reinforcement resets the clock.
Code Style
SIMPLE · ELEGANT · FLEXIBLE · ROBUST — full patterns in docs/coding_principles.md
- Functional Python — pure functions, input → output, compose pipelines from ≤50-line functions
- Fail fast — exceptions bubble up; catch only at CLI/MCP system boundaries
- No defensive code — no broad
except, notry/exceptin business logic - Complete type hints — every function, public and private
- Docstrings follow this template on every public method:
USE WHEN: … DON'T USE WHEN: … COST: … RETURNS: … NEXT: … - AgentGuide required: every new public
MemorySystemmethod must have a correspondingAgentGuideentry insrc/elfmem/guide.pyGUIDESdict before the PR merges. This is what makeselfmem guideauthoritative and keeps user project CLAUDE.mds permanently correct.
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.
- 2d ago First seen · 265 lines · 3,404 tokens per session scan A e369d529574e
elfmem CLAUDE.md is an instructions file published in the GitHub repository emson/elfmem (58 stars, last pushed 4d ago), licensed MIT. It adds 3,404 tokens to every session, about $0.0170 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 2026-08-30.
Other instructions, from other repositories
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.