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/okminlee/everything-claude-code-ios/continuous-learningnpx skills add OkminLee/everything-claude-code-ios --skill continuous-learninggit clone --depth 1 https://github.com/OkminLee/everything-claude-code-iosWhat 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 | $0.00026 | $0.00423 |
| Opus 5 | $0.00013 | $0.00211 |
| Sonnet 5 | $0.00005 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00042 |
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.
What it actually says
Continuous Learning v2
Automatically detect repeated patterns across sessions and promote them to learned skills.
When to Activate
- Automatically on session end (via evaluate.js Stop hook)
- When reviewing draft skills at session start
How It Works
Detection (evaluate.js)
At session end, the evaluate hook:
- Loads
config.jsonfor pattern detection settings - Reads today's session file (
~/.claude/sessions/) - Analyzes git log and session data for patterns:
error_resolution— same error type fixed 3+ timesuser_corrections— approach changed after user feedbackworkarounds— non-standard solutions applieddebugging_techniques— repeated debugging patternsproject_specific— project-unique conventions
- Creates draft skills in
~/.claude/skills/learned/draft-<name>.md
Approval Flow
At next session start, session-start.js reports draft skills:
[SessionStart] 2 draft skill(s) awaiting approval
[SessionStart] Draft: draft-error-resolution-2026-03-31.md
User decides:
- Approve: rename to remove
draft-prefix, becomes active learned skill - Reject: delete the draft file
Configuration (config.json)
{
"min_session_length": 10,
"extraction_threshold": "medium",
"auto_approve": false,
"patterns_to_detect": ["error_resolution", "user_corrections", ...]
}
extraction_threshold:low(2+),medium(3+),high(5+) occurrencesauto_approve: alwaysfalse— human gate for quality
What ships with it
1 file 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.
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 · 58 lines · 26 tokens per session scan A a77d0c937e9f
continuous-learning-v2 is a skill published in the GitHub repository OkminLee/everything-claude-code-ios (58 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 423 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.
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