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/euniai/awesome-code-agents/claude-mdgit clone --depth 1 https://github.com/EuniAI/awesome-code-agentsWrote 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/euniai/awesome-code-agents/claude-md)<a href="https://agentmods.dev/instructions/euniai/awesome-code-agents/claude-md"><img src="https://agentmods.dev/badge/instructions/euniai/awesome-code-agents/claude-md.svg" alt="Measured on agentmods" 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 | $0.01871 | $0.01871 |
| Opus 5 | $0.00936 | $0.00936 |
| Sonnet 5 | $0.00374 | $0.00374 |
| Haiku 4.5 | $0.00187 | $0.00187 |
Grade A, and why
awesome-code-agents CLAUDE.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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Awesome Code Agents — Project Context
Working Preferences (owner: Zhaoyang-Chu)
- Always work directly on
main, no worktrees. Commit and push after each logical change so nothing gets lost. - Do NOT add
Co-Authored-By: Claudeto commit messages. Commits show only the owner's account. - English-only repo. Every file (data, docs, commit messages, comments) is English. No Chinese anywhere in the repo.
- No em-dashes in anything we write (they read as AI-written). Use colons, commas, parentheses, or separate sentences. Never alter em-dashes inside a paper's own title or abstract (quoted source text).
- Keep the design philosophy current in automation/DESIGN.md: it states the repo's final design and the reasoning behind it, organized by theme (no dated log, no superseded alternatives). When a turn settles a non-trivial design point, fold it into the right section that same turn. Chat is ephemeral; the repo is the memory.
What This Is
A curated list of research papers on autonomous code agents, published at
euni.ai and github.com/EuniAI/awesome-code-agents. Rebuilt
from the ground up in 2026-07 (taxonomy, data, and pipeline); the old system
lives only in git history. Design rationale: automation/DESIGN.md; the rebuild-era
records (legacy audit, completeness warrant) live at the git tag rebuild/2026-07.
The Two Sources of Truth
- automation/data/taxonomy.json: the category system. Four top-level branches:
foundation_models(flagship general models),studies(surveys and empirical research about the agents),artifact(code as the deliverable; 8 domains, software expands into 10 lifecycle activities),agency(code as the language of action; 6 worlds). Machine-facing contract per node: definition / includes / boundary / examples; plus a repo-wide scope with a hardened relevance gate and an ordered master_test. The classifier prompt is COMPILED from this file; never hand-write category text elsewhere. - automation/data/calibration.json: owner-labeled real papers as positive and negative few-shot examples (each with a why). They guide the classifier by precedent; they never pin papers by id. Grows automatically from review feedback (see the learning loop) and by hand when the owner rules on a case.
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.
- 4d ago First seen · 130 lines · 1,871 tokens per session scan A c52112903d70
awesome-code-agents CLAUDE.md is an instructions file published in the GitHub repository EuniAI/awesome-code-agents (127 stars, last pushed 4d ago), licensed Apache-2.0. It adds 1,871 tokens to every session, about $0.0094 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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