Borrowing it
Nothing to install: this file belongs to ourobx/agent-ebpf. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ourobx/agent-ebpf/main/v2/.github/instructions/self-learning.instructions.mdgit clone --depth 1 https://github.com/ourobx/agent-ebpfWrote 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/instructions/ourobx/agent-ebpf/self-learning)<a href="https://agentmods.dev/instructions/ourobx/agent-ebpf/self-learning"><img src="https://agentmods.dev/badge/instructions/ourobx/agent-ebpf/self-learning/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/instructions/ourobx/agent-ebpf/self-learning"><img src="https://agentmods.dev/badge/instructions/ourobx/agent-ebpf/self-learning.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 | $0.02381 | $0.02381 |
| Opus 5.5 | $0.00952 | $0.00952 |
| Sonnet 5.5 | $0.00476 | $0.00476 |
| Haiku 4.5 | $0.00238 | $0.00238 |
Grade C, and why
self-learning scanned grade C with 1 finding 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 1mo 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- Copilot Instruction Telemetry: This file was auto-generated by Claude Skills Manager --> How it starts
The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
self-learning
Self-Learning
A small, project-agnostic accumulated-experience store. The goal: the second time something fails, fixing it is instant because the fix is already written down — and reliable commands don't need re-verifying every session.
Storage layout
All state lives under .claude/learning/ in the target project (create it on
first use):
.claude/learning/
runs.jsonl append-only log of recorded outcomes (gitignore this)
patterns.md auto-generated report (gitignore this)
session-learnings.md human/agent-curated decisions and fixes (commit this)
knowledge-cache.md cached answers to repeated questions (commit this)
skill-feedback.jsonl user negative reactions to agent/skill behavior (gitignore)
task-skill-proposals.json proposed skills for the current task (gitignore)
Add .claude/learning/runs.jsonl, .claude/learning/patterns.md,
.claude/learning/skill-feedback.jsonl, and .claude/learning/task-skill-proposals.json to
.gitignore if not already ignored — they're machine-local history.
session-learnings.md and knowledge-cache.md should be committed: they're
durable, reviewable output.
Run record schema (one JSON object per line in runs.jsonl)
{"ts": "2026-06-11T14:32:00", "skill": "terraform-plan-review", "action": "plan",
"rc": 0, "duration": 4.2, "error": "", "hint": "", "note": "", "tokens": 12345,
"metadata": {"invoked": true}}
skill/action: a short identifier for what was run (e.g. skill name + subcommand, or"task"+ a short task name).metadata.invoked: set totruewhen this skill was actually invoked in the session (not merely listed in context). Cost attribution uses this to distinguish active skills from enabled-but-unused skills.rc: 0 for success, non-zero for failure.error: first meaningful error line (truncate to ~200 chars), empty on success.hint: a short fix description if one is known (see "Deriving hints" below); empty if none.note: optional free-text context.tokens: optional total token count (input + output + cache write + cache read) attributable to this run — see "Recording token usage" below. Omit if it can't be determined.
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.
- 1mo ago Changed 80e00fb8810a
- 1mo ago Changed d632e1817a67
- 1mo ago Changed 9d22bc499047
- 1mo ago First seen · 212 lines · 2,381 tokens per session scan C 5e6981aee098
self-learning is an instructions file published in the GitHub repository ourobx/agent-ebpf (1 stars, last pushed 9d ago), licensed MIT. It adds 2,381 tokens to every session, about $0.0095 per session on Opus 5.5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
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Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.