agents-radar is an automated GitHub Actions workflow that gathers AI-related updates from sources such as GitHub, ArXiv, Hacker News, Hugging Face, and Product Hunt, then publishes bilingual daily digests. Developers and AI enthusiasts use its issues, Markdown reports, web interface, RSS feed, and messaging notifications to follow the ecosystem. The catalogue instructions relate to running or using this reporting workflow.
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/duanyytop/agents-radar/agents-mdgit clone --depth 1 https://github.com/duanyytop/agents-radarWrote 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/duanyytop/agents-radar/agents-md)<a href="https://agentmods.dev/instructions/duanyytop/agents-radar/agents-md"><img src="https://agentmods.dev/badge/instructions/duanyytop/agents-radar/agents-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 | $0.02780 | $0.02780 |
| Opus 5 | $0.01390 | $0.01390 |
| Sonnet 5 | $0.00556 | $0.00556 |
| Haiku 4.5 | $0.00278 | $0.00278 |
Grade A, and why
agents-radar 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 5d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project overview
agents-radar is a daily digest generator for the AI open-source ecosystem. A GitHub Actions cron job runs at 00:00 UTC (08:00 CST) and produces bilingual (Chinese + English) reports, published as GitHub Issues and committed Markdown files.
Commands
pnpm start # run the full digest locally
pnpm test # vitest (unit tests)
pnpm typecheck # tsc --noEmit
pnpm lint # ESLint
pnpm lint:fix # ESLint --fix
pnpm format # Prettier --write src
pnpm format:check # Prettier --check src
Required env vars for local runs:
export GITHUB_TOKEN=ghp_xxxxx
export DIGEST_REPO=owner/repo # omit to skip GitHub issue creation
# LLM provider (default: anthropic)
export LLM_PROVIDER=anthropic # anthropic | openai | github-copilot | openrouter | deepseek
# Anthropic (default)
export ANTHROPIC_API_KEY=sk-ant-xxxxx
# OpenAI
# export OPENAI_API_KEY=sk-xxxxx
# GitHub Copilot — uses GITHUB_TOKEN
# OpenRouter
# export OPENROUTER_API_KEY=sk-or-xxxxx
# DeepSeek
# export DEEPSEEK_API_KEY=sk-xxxxx
Architecture
The pipeline runs in four sequential phases, each implemented as a named async function in src/index.ts:
fetchAllData— all network I/O in parallel: GitHub API (issues/PRs/releases) for 17 repos, Claude Code Skills, Anthropic/OpenAI sitemaps, GitHub Trending HTML + Search API, Hacker News Algolia API.generateSummaries— per-repo LLM calls, all in parallel, rate-limited to 5 concurrent requests by a queue insrc/report.ts.- Comparisons — two LLM calls: cross-tool CLI comparison and OpenClaw cross-ecosystem comparison.
- Save phase —
buildCliReportContent/buildOpenclawReportContent/buildInfraReportContent(insrc/report-builders.ts) build Markdown strings;saveWebReport/saveTrendingReport/saveHnReport(insrc/report-savers.ts) call LLM + write file + create GitHub Issue.
Source files
| File | Responsibility |
|---|---|
src/index.ts |
Orchestration: repo config, phase functions, main() |
src/i18n.ts |
Centralized bilingual strings: Lang type, report titles, issue labels, footer text, REPORT_LABELS, NOTIFY_LABELS |
src/github.ts |
GitHub API helpers: fetchRecentItems, fetchRecentReleases, fetchRecentDiscussions (GraphQL), fetchSkillsData, createGitHubIssue; shared RepoFetch type |
src/config.ts |
Loads config.yml into RadarConfig (cliRepos, skillsRepo, openclaw, openclawPeers, infraRepos); built-in defaults when a section is missing |
src/prompts.ts |
LLM prompt builders for repo reports: buildCliPrompt, buildPeerPrompt, buildInfraPrompt, buildComparisonPrompt, buildInfraComparisonPrompt, buildPeersComparisonPrompt, buildSkillsPrompt |
src/prompts-data.ts |
LLM prompt builders for data-source reports: buildTrendingPrompt, buildWebReportPrompt, buildHnPrompt |
src/report.ts |
callLlm (with concurrency limiter), saveFile, autoGenFooter (uses i18n), LLM token budget constants |
src/report-builders.ts |
buildCliReportContent, buildOpenclawReportContent, buildInfraReportContent — assemble final Markdown strings for CLI, OpenClaw and infra reports |
src/report-savers.ts |
saveWebReport, saveTrendingReport, saveHnReport — LLM call + file save + optional GitHub issue |
src/date.ts |
Date and timing utilities: toCstDateStr, toUtcStr, sleep |
src/providers/types.ts |
LlmProvider interface, ProviderName type, VALID_PROVIDER_NAMES |
src/providers/openai-compatible.ts |
OpenAICompatibleProvider — shared base class for OpenAI-compatible providers |
src/providers/anthropic.ts |
AnthropicProvider — Anthropic SDK wrapper |
src/providers/openai.ts |
OpenAIProvider — extends OpenAICompatibleProvider |
src/providers/github-copilot.ts |
GitHubCopilotProvider — extends OpenAICompatibleProvider |
src/providers/openrouter.ts |
OpenRouterProvider — extends OpenAICompatibleProvider |
src/providers/deepseek.ts |
DeepSeekProvider — extends OpenAICompatibleProvider |
src/providers/index.ts |
createProvider factory + barrel re-exports |
src/web.ts |
Sitemap-based web content fetching; state persisted to digests/web-state.json |
src/trending.ts |
GitHub Trending HTML scraper + Search API topic queries |
src/hn.ts |
Hacker News top AI stories via Algolia HN Search API |
src/generate-manifest.ts |
Generates manifest.json (sidebar data for Web UI) and feed.xml (RSS 2.0 feed) |
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.
- 5d ago First seen · 137 lines · 2,780 tokens per session scan A 3a67e68ae7e8
agents-radar AGENTS.md is an instructions file published in the GitHub repository duanyytop/agents-radar (1,044 stars, last pushed today), licensed MIT. It adds 2,780 tokens to every session, about $0.0139 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
vscode buildNext.instructions.md
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).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
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.