AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.
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 skills/ufy2024/auc/continuous-learningnpx skills add ufy2024/AuC --skill continuous-learninggit clone --depth 1 https://github.com/ufy2024/AuCWrote 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/skills/ufy2024/auc/continuous-learning)<a href="https://agentmods.dev/skills/ufy2024/auc/continuous-learning"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/continuous-learning.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.01166 |
| Opus 5 | $0.00032 | $0.00583 |
| Sonnet 5 | $0.00013 | $0.00233 |
| Haiku 4.5 | $0.00006 | $0.00117 |
Grade B, and why
continuous-learning scanned grade B with 1 finding 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 yesterday.
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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Add to your `~/.claude/settings.json`: Copies of this mod
6 near-identical copies found in the catalogue:
- continuous-learning — 88% identical, 32 lines differ
- continuous-learning — 84% identical, 44 lines differ
- continuous-learning — 84% identical, 40 lines differ
- continuous-learning — 83% identical, 42 lines differ
- continuous-learning — 83% identical, 42 lines differ
- continuous-learning — 81% identical, 29 lines differ
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Continuous Learning Skill - DEPRECATED
DEPRECATED 2026-04-28. Use
continuous-learning-v2instead. v2 is a strict superset: stop-hook observation becomes PreToolUse/PostToolUse observation, full skills become atomic instincts with confidence scoring, and global-only storage becomes project-scoped plus global promotion.This file is kept for archival reference and backward compatibility with existing installs.
Original v1 Documentation (archival)
Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills.
When to Activate
- Setting up automatic pattern extraction from Claude Code sessions
- Configuring the Stop hook for session evaluation
- Reviewing or curating learned skills in
~/.claude/skills/learned/ - Adjusting extraction thresholds or pattern categories
- Comparing v1 (this) vs v2 (instinct-based) approaches
Status
This v1 skill is still supported, but continuous-learning-v2 is the preferred path for new installs. Keep v1 when you explicitly want the simpler Stop-hook extraction flow or need compatibility with older learned-skill workflows.
How It Works
This skill runs as a Stop hook at the end of each session:
- Session Evaluation: Checks if session has enough messages (default: 10+)
- Pattern Detection: Identifies extractable patterns from the session
- Skill Extraction: Saves useful patterns to
~/.claude/skills/learned/
Configuration
Edit config.json to customize:
{
"min_session_length": 10,
"extraction_threshold": "medium",
"auto_approve": false,
"learned_skills_path": "~/.claude/skills/learned/",
"patterns_to_detect": [
"error_resolution",
"user_corrections",
"workarounds",
"debugging_techniques",
"project_specific"
],
"ignore_patterns": [
"simple_typos",
"one_time_fixes",
"external_api_issues"
]
}
Pattern Types
| Pattern | Description |
|---|---|
error_resolution |
How specific errors were resolved |
user_corrections |
Patterns from user corrections |
workarounds |
Solutions to framework/library quirks |
debugging_techniques |
Effective debugging approaches |
project_specific |
Project-specific conventions |
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.
- yesterday First seen · 154 lines · 64 tokens per session scan B 1e32ad45b516
continuous-learning is a skill published in the GitHub repository ufy2024/AuC (1,091 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,166 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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