A persistent learning system for an AI agent that stores rules and lessons from past sessions in a searchable local database.

It helps load relevant rules, record errors as anti-patterns, review sessions, group rules into principles, search stored knowledge, and inspect system statistics.

It helps the agent remember corrections, preferences, recurring mistakes, and useful principles instead of starting from scratch each session.

capy-cortex — Skill for Claude Code by happycapy-ai

Install

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.

Any agent

npx skills add happycapy-ai/Happycapy-skills --skill capy-cortex

Clone the repo

git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/happycapy-ai/happycapy-skills/capy-cortex/github.svg)](https://agentmods.dev/skills/happycapy-ai/happycapy-skills/capy-cortex)

Your own site

<a href="https://agentmods.dev/skills/happycapy-ai/happycapy-skills/capy-cortex"><img src="https://agentmods.dev/badge/skills/happycapy-ai/happycapy-skills/capy-cortex/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/happycapy-ai/happycapy-skills/capy-cortex"><img src="https://agentmods.dev/badge/skills/happycapy-ai/happycapy-skills/capy-cortex.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 585 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00028	$0.00585
Opus 5	$0.00014	$0.00293
Sonnet 5	$0.00006	$0.00117
Haiku 4.5	$0.00003	$0.00059

Measured 11d ago against content hash 16f8f18e0b7e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

capy-cortex 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 11d ago.

The scan reads SKILL.md. This mod also ships 24 executable files (dashboard.py, dashboard/eslint.config.js, dashboard/src/hooks/useAnimatedValue.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/capy-cortex/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Capy Cortex - Autonomous Learning System

You have a persistent learning brain powered by SQLite + FTS5 + sklearn TF-IDF. Knowledge is automatically loaded via hooks. This file describes manual operations.

Architecture

Database: ~/.claude/skills/capy-cortex/cortex.db (SQLite + FTS5 + WAL)
Hooks (automatic, never call manually):
- SessionStart: Loads anti-patterns, preferences, principles
- UserPromptSubmit: Retrieves task-relevant rules via FTS5
- PreToolUse(Bash): Blocks known dangerous commands
- PostToolUseFailure: Records errors as anti-patterns
- Stop: Extracts corrections and preferences from conversation
Scripts (for manual/scheduled use):
- cortex.py: Core engine (retrieve, add rules, stats)
- reflect.py: Deep session analysis
- consolidate.py: Cluster rules into principles (sklearn)
- bootstrap.py: Mine historical sessions

Manual Commands

# Check system health
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py stats

# Retrieve rules for a topic
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py retrieve "react typescript"

# Add a rule manually
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-rule "Always use TypeScript strict mode" "best_practice"

# Add an anti-pattern
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-ap "Never force push to main" "critical"

# Add a preference
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-pref "User prefers functional components over class components"

# Run consolidation (clusters rules into principles)
python3 ~/.claude/skills/capy-cortex/scripts/consolidate.py

# Retrain TF-IDF model
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py retrain

# Apply confidence decay
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py decay

How It Learns

Automatic (via hooks): Errors are captured, corrections noted, preferences extracted
Reflection: Deep analysis of session transcripts extracts patterns
Consolidation: sklearn clustering groups similar rules into principles
Decay: Old, unreinforced rules fade; validated rules strengthen
Retrieval: Two-stage FTS5 + TF-IDF returns only relevant knowledge (O(1) context)

Read the full file on GitHub · 61 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

11d ago First seen · 61 lines · 28 tokens per session scan A 16f8f18e0b7e

Subscribe to this mod's changes

capy-cortex is a skill published in the GitHub repository happycapy-ai/Happycapy-skills (139 stars, last pushed 7d ago), licensed MIT. It adds 28 tokens to every session and 585 once invoked, about $0.0001 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.

Memory and context

media-ingest

Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.

garrytan/gbrain · 52 tokens

mem0-oss-to-platform

Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…

mem0ai/mem0 · 273 tokens

Cortex

Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…

danielmiessler/LifeOS · 196 tokens

memory

Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.

opensquilla/opensquilla · 44 tokens

ha-data-stores

Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…

shiwenwen/hope-agent · 115 tokens

establishing-project-context

Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.

GanyuanRan/Aegis · 45 tokens