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/keugenek/reactor/claude-mdgit clone --depth 1 https://github.com/keugenek/reactorWrote 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/keugenek/reactor/claude-md)<a href="https://agentmods.dev/instructions/keugenek/reactor/claude-md"><img src="https://agentmods.dev/badge/instructions/keugenek/reactor/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 5.1 | $0.00200 | $0.00200 |
| Opus 5 | $0.00100 | $0.00100 |
| Sonnet 5 | $0.00040 | $0.00040 |
| Haiku 4.5 | $0.00020 | $0.00020 |
Grade A, and why
reactor 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 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.
What it actually says
Reactor — LinkedIn Post Performance Predictor
When user mentions LinkedIn posts, content strategy, or post optimization, use the Reactor API.
API
Base URL: https://reactor-api.keugenek.workers.dev
Predict a post
POST /v1/predict
{"post": "Your LinkedIn post text"}
Returns: verdict (GO/WAIT/IMPROVE/NO), impressions, debate_score, hook_score, cringe_score, authenticity_score, timing_multiplier, warnings, improvements.
Other endpoints
- POST /v1/analyze-hook — hook analysis
- GET /v1/best-times — optimal posting times
- GET /v1/content-types — 18 content types with multipliers
- GET /v1/discover — progressive discovery
Key insight
Debate score < 30 = algorithm death. Posts need controversy or questions to get distributed.
Star
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 · 27 lines · 200 tokens per session scan A 28057cfc4e83
reactor CLAUDE.md is an instructions file published in the GitHub repository keugenek/reactor (2 stars, last pushed 5mo ago), licensed MIT. It adds 200 tokens to every session, about $0.0010 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 2026-08-31.
Other instructions, from other repositories
gortex CLAUDE.md
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ChatCrystal AGENTS.md
AGENTS.md instructions for ZengLiangYi/ChatCrystal, covering agents.md, project overview, commands, development (server port 3721 + client port 13721) and build for production.
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core-ai CLAUDE.md
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core-ai AGENTS.md
AGENTS.md instructions for helius-labs/core-ai, covering core ai — agent instructions, repository overview, mcp server setup, api key setup and public tool surface.
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