Borrowing it
Nothing to install: this file belongs to enchanter-ai/cyclops. 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/enchanter-ai/cyclops/main/CLAUDE.mdgit clone --depth 1 https://github.com/enchanter-ai/cyclopsWrote 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/enchanter-ai/cyclops/claude-md)<a href="https://agentmods.dev/instructions/enchanter-ai/cyclops/claude-md"><img src="https://agentmods.dev/badge/instructions/enchanter-ai/cyclops/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 | $0.00897 | $0.00897 |
| Opus 5 | $0.00449 | $0.00449 |
| Sonnet 5 | $0.00179 | $0.00179 |
| Haiku 4.5 | $0.00090 | $0.00090 |
Grade A, and why
cyclops 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 2d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cyclops — Agent Contract
Audience: Claude. Cyclops is a deterministic, model-free MCP proxy that detects and prevents typed toxic flows over a provenance graph — EXFILTRATION (untrusted-web → sensitive-read → external-egress) and EXCESSIVE_AGENCY (untrusted → privileged action, args derived from untrusted content, no sensitive read). Each class carries its OWASP LLM Top 10 (2025) code. It watches an autonomous MCP agent's tool calls from the outside and never trusts or modifies the agent.
Hard invariants
- Model-free decision path. No LLM, no network, no randomness decides a verdict. The detector is the thing watching an injectable agent — if it could be influenced by untrusted content, it would be the vulnerability. Never introduce a model call into
classify.py,overlap.py,graph.py,severity.py, ordetector.py. - Nothing hardcoded. Server and tool names are plain
strsourced frompatterns.toml— no string literal"filesystem","web","post"in logic. Taint, mode, flow-class, and transport names are enums incyclops/enums/. - Detection data is data. All patterns live in
cyclops/patterns.toml, loaded byconfig.pyinto typed constants. Adding a pattern edits the TOML, never a.py. - House style. No comments in any source file. No double blank lines. Both are enforced by
tests/test_style.py. - Honest credit. The toxic-flow concept is Invariant Labs'; the lethal-trifecta framing is Simon Willison's. The contribution is the combination (byte-provenance + encoding-unmask + leak-volume + choke-point + deterministic + endpoint-resident). Never present the concept as novel — see
docs/differentiation.md.
Layout
This is the production core — only the MCP proxy and the model-free enforcement engine. No demo CLI, harness, or mock servers ship.
cyclops/
enums/ FlowClass, Mode, Taint, Transport (server / tool names are plain str)
records/ ToolCall, Metrics, Flow (dataclasses)
patterns.toml detection data (untrusted / sensitive / egress / privileged / owasp)
config.py loads patterns.toml into typed constants
classify.py taint classification
overlap.py encoding-unmask + token matching
graph.py provenance graph + typed find_toxic_flows (exfil + excessive-agency)
severity.py leak-volume in bytes
detector.py detect / prevent orchestration + per-class metrics
downstream.py typed loader for the downstream-server map (stdio / Streamable HTTP)
proxy.py external MCP proxy (stdio + Streamable HTTP) + session.json verdict
downstream.example.toml operator template binding real MCP servers to logical roles
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.
- 2d ago Changed · +23 tokens per session cce7f25af753
- 5d ago First seen · 44 lines · 874 tokens per session scan A 5426d9941b33
cyclops CLAUDE.md is an instructions file published in the GitHub repository enchanter-ai/cyclops (1 stars, last pushed 5d ago), licensed MIT. It adds 897 tokens to every session, about $0.0045 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
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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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).
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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.
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.