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/harzva/learn-likecc/agents-mdgit clone --depth 1 https://github.com/Harzva/learn-likeccWhat 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 | $0.00146 | $0.00146 |
| Opus 5 | $0.00073 | $0.00073 |
| Sonnet 5 | $0.00029 | $0.00029 |
| Haiku 4.5 | $0.00015 | $0.00015 |
Grade A, and why
learn-likecc AGENTS.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 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 7 lines · 146 tokens per session scan A 33e3f335228b
learn-likecc AGENTS.md is an instructions file published in the GitHub repository Harzva/learn-likecc (57 stars, last pushed 3d ago), with no licence file. It adds 146 tokens to every session, about $0.0007 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.
Other instructions, from other repositories
dev-3.0 AGENTS.md
Instructions for h0x91b/dev-3.0, covering agents.md, response style, what is this, ui/ux work — which skill, and when (mandatory) and where dev3 overrides the better-family skills.
opencode-swarm copilot-instructions.md
Instructions for ZaxbyHub/opencode-swarm, covering mandatory pr publication protocol, pr title requirements, pr body requirements, validation requirements and release fragment requirement.
meridian CLAUDE.md
Claude Code instructions for rynfar/meridian, covering claude.md, what this is, commands, code rules and module boundaries.
meridian AGENTS.md
AGENTS.md instructions for rynfar/meridian, covering agents.md, what this is, commands, code rules and module boundaries.
Atomic-Spec AGENTS.md
Instructions for Chappygo-OS/Atomic-Spec, covering agents.md — adding a new ai agent to atomic spec, about atomic spec and the atomicspec cli, general practices, adding new agent support and current supported agents.
Atomic-Spec CLAUDE.md
Instructions for Chappygo-OS/Atomic-Spec, covering claude.md, what this repository is, architecture — the phase pipeline, critical conventions and common commands.