Borrowing it
Nothing to install: this file belongs to bcharleson/crystallized-intelligence. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/bcharleson/crystallized-intelligence/main/AGENTS.mdgit clone --depth 1 https://github.com/bcharleson/crystallized-intelligenceWrote 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.
[](https://agentmods.dev/instructions/bcharleson/crystallized-intelligence/agents-md)<a href="https://agentmods.dev/instructions/bcharleson/crystallized-intelligence/agents-md"><img src="https://agentmods.dev/badge/instructions/bcharleson/crystallized-intelligence/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/bcharleson/crystallized-intelligence/agents-md"><img src="https://agentmods.dev/badge/instructions/bcharleson/crystallized-intelligence/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00746 | $0.00746 |
| Opus 5.5 | $0.00298 | $0.00298 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 5mo ago), licensed MIT. It adds 746 tokens to every session, about $0.0030 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.
Other instructions, from other repositories
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).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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 copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.