ShellBrain
Long-term Memory for AI Agents.
ShellBrain carries useful lessons from one agent task to the next. It preserves decision reasons, failed approaches, product direction, and preferences that the resulting code does not explain.
Install
curl -L shellbrain.ai/install | bash
Works for Codex, Claude Code, and Cursor. The installer runs shellbrain init for you. Repos register themselves on first use.
Requirements.
- macOS or Linux, Python 3.11+, Docker for the managed local Postgres+pgvector runtime.
Upgrade for latest capabilities
shellbrain upgrade
You can also run curl -L shellbrain.ai/upgrade | bash. Manual alternative: pipx upgrade shellbrain && shellbrain init.
Recall in one command
Architecture
ShellBrain stores evidence and two forms of reusable knowledge:
- Episodic knowledge records evidence. It stores prompts, agent steps, tool calls, and outputs from each session.
- Empirical knowledge extracts concrete memories. It organizes problems, solutions, failed tactics, facts, preferences, and changes in a semantic graph for case-based reasoning.
- Conceptual knowledge abstracts reusable ideas. Its concept graph connects claims, relations, and implementations to empirical knowledge.
Memories and concept claims link to supporting evidence. A concept can express a product principle without a duplicate memory. Current code remains the source of truth for implementation details.
How Agents Use ShellBrain
Recall
Working agents run shellbrain recall to get one compact brief for the current task.
Recall, automatic learning, and teaching use the same evidence selector. It combines BM25, vector similarity, and graph links. Learning agents receive the selected records. The recall agent can summarize them.
Recall receives only the quoted query. Include the relevant task, failure, subsystem, or decision in the question.
shellbrain recall "What is ShellBrain, and how does it help a working coding agent?"
Response format:
{
"status": "ok",
"data": {
"brief": {
"summary": "...",
"constraints": ["..."],
"known_traps": ["..."],
"prior_cases": ["..."],
"concept_orientation": ["..."],
"anchors": ["`README.md`"],
"conflicts": ["..."],
"gaps": ["..."],
"next_checks": ["..."]
},
"fallback_reason": null
},
"errors": []
}
Recall selects an evidence pack in code, then asks an inner agent to summarize it. Source attribution comes from the selected records. Fast mode and provider failures return a brief directly from that same pack.
Teach
Run shellbrain teach only when you explicitly want ShellBrain to remember something important.
Memory Discipline
ShellBrain keeps memory grounded in evidence and narrow in scope. Agents request memory when they need it.
Memory that cannot justify itself should not persist.
Use ShellBrain
Use Shellbrain with your preferred agent. Then work as usual.
- Claude Code: Use
/shellbrainto recall context at task boundaries. - Codex: Use $shellbrain to recall context at task boundaries.
- Cursor: Use
/shellbrainto recall context at task boundaries.
Repair
Run shellbrain admin doctor to inspect the installation. If it reports a problem, run shellbrain init. Do not run init every session.
Docs
- For Humans: installation, upgrades, and first steps
- For Agents: agent workflow and memory rules
- Technical Docs: detailed documentation and code map
1 maintainer
Metadata
1 maintainer
Release files for shellbrain 0.1.59
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| File | Size | Uploaded | Provenance | |
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|---|---|---|---|---|
| shellbrain-0.1.59-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
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