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 skills add amitvijapur/cortex --skill cortex-learngit clone --depth 1 https://github.com/amitvijapur/cortexWrote 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/amitvijapur/cortex/cortex-learn)<a href="https://agentmods.dev/skills/amitvijapur/cortex/cortex-learn"><img src="https://agentmods.dev/badge/skills/amitvijapur/cortex/cortex-learn/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/skills/amitvijapur/cortex/cortex-learn"><img src="https://agentmods.dev/badge/skills/amitvijapur/cortex/cortex-learn.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 | $0.00045 | $0.00684 |
| Opus 5.5 | $0.00018 | $0.00274 |
| Sonnet 5.5 | $0.00009 | $0.00137 |
| Haiku 4.5 | $0.00005 | $0.00068 |
Grade A, and why
cortex-learn 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 6d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cortex-learn
Run pattern detection on the active state's cortex-log.jsonl. Surface groups of routing decisions that repeated ≥3 times as candidate Decision Shortcuts for cortex.md.
When to invoke
- User types
/cortex-learnexplicitly - User asks "what patterns is cortex seeing"
- User asks "are there routes I should codify"
- User says "tune cortex based on usage"
- Session-start check (via
cortex learn --check) surfaced a pending pattern
What to do
Step 1 — Run pattern detection
Resolve the state directory from CORTEX_HOME, then CLAUDE_DIR, then
$HOME/.claude, matching the CLI and installer. Keep a custom override exported
in the agent's environment. Use that directory's cortex.md for registry edits.
cortex_state_dir="${CORTEX_HOME:-${CLAUDE_DIR:-$HOME/.claude}}"
python3 "$cortex_state_dir/bin/cortex" learn
Optional:
--threshold N— change minimum count (default 3)--check— terse one-liner for session-start use (no review flow)--no-proposals— skip writing markdown proposal files
Step 2 — Review the proposals
For each detected pattern, the tool writes a markdown proposal file with frontmatter status pending. The user should:
- Read each proposal
- Decide: approve, modify, or reject
- If rejected: persist
status: rejectedin that exact proposal's YAML frontmatter and write a one-line reason in Notes. A checkbox or a chat acknowledgement alone does not persist the decision. - If approved (including an approved modification): add the agreed shortcut to
cortex.md→ Decision Shortcuts table, then persiststatus: approvedin the proposal. Keepclass,system, andpatternas the original detection identity; put approved changes in the candidate row and Notes. - Read back the edited file before confirming the decision. If the write fails, report that it was not saved. Do not claim suppression based only on the user's reply.
Approved, rejected and superseded tuples are excluded from ordinary future suggestions, even if their counts grow. cortex learn --include-actioned explicitly includes them again. Do not promise automatic reconsideration on growth. With --no-proposals, report only; there is no proposal decision to persist unless the user requests one.
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.
- 6d ago Changed · +7 lines 47c4338cc1d2
- 1mo ago First seen · 51 lines · 45 tokens per session scan A 7a20b56cd527
cortex-learn is a skill published in the GitHub repository amitvijapur/cortex (5 stars, last pushed 3d ago), licensed MIT. It adds 45 tokens to every session and 684 once invoked, about $0.0002 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.
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