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/bcharleson/crystallized-intelligence/agents-mdgit clone --depth 1 https://github.com/bcharleson/crystallized-intelligenceWhat 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 | $0.00746 | $0.00746 |
| Opus 5 | $0.00373 | $0.00373 |
| Sonnet 5 | $0.00149 | $0.00149 |
| Haiku 4.5 | $0.00075 | $0.00075 |
Grade A, and why
crystallized-intelligence AGENTS.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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Guide — Crystallized Intelligence for Agents
Open-source framework for pre-compiling domain expertise into agent-readable layers. This repo ships tooling and a demo brain; your proprietary content lives in a separate brain repo.
Repo roles
| Artifact | Location | Purpose |
|---|---|---|
| Framework | This repo (tools/, spec/, schemas) |
classify, crystallize, verify, retrieve |
| Brain | Your fork's brain dir or sibling repo | brain.yaml + corpus/{domain}/ |
| Skill | skills/use-crystallized-brain/SKILL.md | How agents retrieve without token burn |
Quick start for agents
export BRAIN_ROOT=examples/demo-brain # replace with your brain path
python tools/bin/brain.py bootstrap specialty-coffee
Prefer MCP when configured: tools brain_bootstrap, brain_expand, brain_search, brain_get_document. See docs/AGENT-INTEGRATION.md.
Operating rules
- Layer-first — bootstrap (
seed+principles) before readingknowledge/orsources/ - Trust-weighted — lower
source_tierwins on conflict (0 = first-party) - Budgeted expand — use
--max-tokensand--max-tier 3by default - No corpus dumps — never load all of
sources/into context - Framework only here — no hardcoded company domains or client content in this repo
Copy skills/use-crystallized-brain/SKILL.md into .cursor/skills/ (or your agent's skill path) when working against a real brain.
Fork → initialize → use
# Initialize a new brain (separate directory)
python tools/bin/brain.py init --path ~/my-brain --name "My Brain" --domains "ops"
export BRAIN_ROOT=~/my-brain
# Add corpus files with frontmatter → crystallize → verify
python tools/bin/brain.py crystallize --domain ops --local
python tools/bin/brain.py verify --domain ops
Tools reference
| Command | Agent use? | Notes |
|---|---|---|
brain bootstrap |
Yes | Always first |
brain expand |
Yes | Query + token budget |
brain search |
Yes | Paths + snippets |
brain get |
Yes | Single document |
brain domains |
Yes | Discovery |
classify |
Maintainer | Validate tiers |
crystallize |
Maintainer | Rebuild _crystal/ |
verify |
Maintainer | Schema + structure |
freshness-audit |
Maintainer | Staleness report |
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 · 71 lines · 746 tokens per session scan A 43dae471a193
crystallized-intelligence AGENTS.md is an instructions file published in the GitHub repository bcharleson/crystallized-intelligence (5 stars, last pushed 3mo ago), licensed MIT. It adds 746 tokens to every session, about $0.0037 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.
Other instructions, from other repositories
spellbook AGENTS.md
Instructions for majiayu000/spellbook, covering spellbook agent contract, routing, scope rules, threads long-run guardrails and validation.
open-supermarkets AGENTS.md
Instructions for abracadabra50/open-supermarkets, covering agent integration guide, supported frameworks, quick integration, 1. add as skill and 2. agent calls commands.
helm copilot-instructions.md
Instructions for PetePeter/helm, covering gamepad-cli-hub — copilot instructions, project purpose, system overview, data flow pipeline and key controls.
fusion-skills AGENTS.md
AGENTS.md instructions for CrowdStrike/fusion-skills, covering agents.md, what this is, prerequisites, repository structure and skills ecosystem.
aeon CLAUDE.md
Instructions for aeonfun/aeon, covering aeon, how aeon works, strategy, voice and soul file hierarchy (read in this order).
ESAA-Core AGENTS.md
Instructions for elzobrito/ESAA-Core, covering agents.md — contrato operacional codex/esaa, 1. autoridade e termos, 2. cli e runner, ou configure o runner uma vez por sessão and 3. concorrência.