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/jxoesneon/ciel/continuous-learning-v2npx skills add jxoesneon/Ciel --skill continuous-learning-v2git clone --depth 1 https://github.com/jxoesneon/CielWrote 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/jxoesneon/ciel/continuous-learning-v2)<a href="https://agentmods.dev/skills/jxoesneon/ciel/continuous-learning-v2"><img src="https://agentmods.dev/badge/skills/jxoesneon/ciel/continuous-learning-v2.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 5.1 | $0.00031 | $0.00713 |
| Opus 5 | $0.00015 | $0.00357 |
| Sonnet 5 | $0.00006 | $0.00143 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
continuous-learning-v2 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CIEL ADAPTATION: Continuous Learning V2 (The Instinct Engine)
This is CIEL's core engine for autonomous evolution. It turns every session into structured knowledge by capturing atomic "instincts"—small, confidence-weighted behaviors learned from direct observation.
The Instinct Model
An instinct is a discrete, evidence-backed behavior:
- Trigger: The specific context that activates the behavior.
- Action: The learned "Do X" or "Don't do Y" instruction.
- Confidence: 0.3 (Tentative) to 0.9 (Core behavior).
- Scope:
project(scoped to a specific repo) orglobal.
The Learning Loop
- Observe (Hooks): Every tool call is captured via Pre/Post-ToolUse hooks, ensuring 100% reliable data collection.
- Analyze (Background): A background agent (e.g., Haiku) identifies patterns in user corrections, error resolutions, and repetitive workflows.
- Persist (MemPalace): Learned instincts are stored in the MemPalace Knowledge Graph (
mempalace_kg_add) or project-specific registries. - Evolve: Related instincts are clustered and promoted into full Skills, Commands, or Agent Definitions.
Project Scoping & Promotion
- Isolation: React patterns stay in React projects; Python conventions stay in Python projects.
- Promotion: When an instinct appears in 2+ projects with high confidence (>= 0.8), it is promoted to the Global Scope.
Legacy Session Evaluation (Stop-Hook)
CIEL retains the legacy probabilistic session-end analysis from V1 as a lightweight fallback:
- Evaluates: Checks if the session length meets the minimum threshold (default: 10 messages).
- Detects: Identifies recurring patterns in error resolutions, workarounds, and project-specific conventions.
- Extracts: Proposes new skills or updates to existing ones based on the session's "best practices."
Commands
/instinct-status: Show all learned instincts and their confidence levels./evolve: Cluster instincts into new skills or commands./promote: Manually move project-scoped instincts to global scope.
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 · 67 lines · 31 tokens per session scan A 1f482db8ae1d
continuous-learning-v2 is a skill published in the GitHub repository jxoesneon/Ciel (1 stars, last pushed 6d ago), licensed Apache-2.0. It adds 31 tokens to every session and 713 once invoked, about $0.0002 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 2026-09-03.
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