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/ilang-ai/autocode/learn-patternnpx skills add ilang-ai/autocode --skill learn-patterngit clone --depth 1 https://github.com/ilang-ai/autocodeWhat 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 | $0.00015 | $0.00097 |
| Opus 5 | $0.00008 | $0.00048 |
| Sonnet 5 | $0.00003 | $0.00019 |
| Haiku 4.5 | $0.00002 | $0.00010 |
Grade A, and why
learn-pattern 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 3d 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
::GENE{learn-pattern|conf:confirmed|scope:global} -e T:detect_recurring_patterns T:apply_automatically A:apply_wrong_pattern⇒verify_context
::ACTIVATE{learn-pattern} ON:auto
Powered by I-Lang v5.0 | ilang.ai
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.
- 3d ago First seen · 16 lines · 15 tokens per session scan A 4a19f5dba279
learn-pattern is a skill published in the GitHub repository ilang-ai/autocode (86 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 97 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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