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 instructions/malwarebo/nyrve/learningsgit clone --depth 1 https://github.com/malwarebo/nyrveWhat 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 | $0.00225 | $0.00225 |
| Opus 5 | $0.00112 | $0.00112 |
| Sonnet 5 | $0.00045 | $0.00045 |
| Haiku 4.5 | $0.00022 | $0.00022 |
Grade A, and why
nyrve learnings.instructions.md 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 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.
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.
This is a copy
100% identical to vscode learnings.instructions.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
This document describes how to deal with learnings that you make. It is a meta-instruction file.
Structure of learnings:
- Each instruction file has a "Learnings" section.
- Each learning has a 1-4 sentences description of the learning.
Example:
## Learnings
* Prefer `const` over `let` whenever possible
* Avoid `any` type
When the user tells you "learn!", you should:
- extract a learning from the recent conversation
- identify the problem that you created
- identify why it was a problem
- identify how you were told to fix it/how the user fixed it
- reflect over it, maybe it can be generalized? Avoid too specific learnings.
- create a learning (1-4 sentences) from that
- Write this out to the user and reflect over these sentences
- then, add the reflected learning to the "Learnings" section of the most appropriate instruction file
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 · 28 lines · 225 tokens per session scan A 9c9af2e42865
nyrve learnings.instructions.md is an instructions file published in the GitHub repository malwarebo/nyrve (5 stars, last pushed 2mo ago), licensed MIT. It adds 225 tokens to every session, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to vscode learnings.instructions.md, differing in 0 lines, and is treated as a copy.
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