Borrowing it
Nothing to install: this file belongs to Proxy2021/Enso. 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/Proxy2021/Enso/main/CLAUDE.mdgit clone --depth 1 https://github.com/Proxy2021/EnsoWrote 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/proxy2021/enso/claude-md)<a href="https://agentmods.dev/instructions/proxy2021/enso/claude-md"><img src="https://agentmods.dev/badge/instructions/proxy2021/enso/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/proxy2021/enso/claude-md"><img src="https://agentmods.dev/badge/instructions/proxy2021/enso/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.11646 | $0.11646 |
| Opus 5.5 | $0.04658 | $0.04658 |
| Sonnet 5.5 | $0.02329 | $0.02329 |
| Haiku 4.5 | $0.01165 | $0.01165 |
Grade A, and why
Enso CLAUDE.md scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Available methods in executor function bodies: `ctx.callTool(name, params)`, `ctx.listDir(path)`, `ctx.readFile(path)`, `ctx.searchFiles(root, name)`, `ctx.fetch(url, opts?)`, `ctx.search(query, opts?)`, `ctx.ask(prompt, How it starts
The opening of the file, as written. The whole thing — 589 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enso — CLAUDE.md
For detailed app building guides, API references, template rules, and code examples, see CLAUDE-REFERENCE.md.
Vision
Enso is a deeply personal AI assistant that understands who you are, discovers what you care about, and mobilizes a full team of AI agents to help you make real progress on the goals that matter most.
Every installation is self-hosted, open-source, and fully owned by the user — you own the factory, not just the product.
The Arc: Understand → Focus → Execute
Enso follows a three-phase arc that compounds over time:
1. Understand the user deeply — Enso scans the user's digital life across 12 data sources (Kindle library, YouTube subscriptions, browser history, email, projects, Steam games, movies/TV, photos, Twitter/X, QQ Music, system apps). Each scan ingests content into the Knowledge Cortex — an interlinked wiki of 2000+ pages that builds a semantic map of who the user is, what they know, and what they're drawn to. Cross-source synthesis connects a Kindle book on quantitative finance to an AlphaRank project to a YouTube channel on systematic investing. The system sees patterns the user might not.
2. Identify what matters — From the Cortex, Enso infers Focus Areas — concrete, outcome-oriented goals the user is working toward. Not category labels ("Quantitative Finance") but actionable goals ("Develop AlphaRank into a Market-Beating Quant Tool"). Each focus has clarity levels (emerging → developing → clear), a deeper personal WHY, adjacent pursuits, and evidence grounded in the user's actual data. Focus areas are first-class Cortex citizens — their wiki pages accumulate everything: evaluation briefings, conversation insights, sprint results, and cross-references.
3. Iterate: Evaluate → Discuss → Evolve — Each focus area has a three-step iterative workflow:
- Evaluate: An orchestration-powered deep study. Multiple AI agents (researcher, codebase analyst, synthesizer) work in parallel to gather web research, analyze project code and sprint history, cross-reference Cortex knowledge, and produce a comprehensive briefing. Progress is visible live in the Evolve tab.
- Discuss: A clean strategic dialogue with the AI (no tool calls, no app cards — just focused thinking). The AI arrives prepared with the evaluation briefing and all Cortex context, acting as a co-strategist to flesh out the problem space, define success criteria, and build a clear vision.
- Evolve: The full conversation context feeds into an
/Evolveorchestration — a multi-agent sprint where a team of AI agents (Project Leader, Architect, Engineer, QA, and domain specialists) execute on the agreed goals. Each agent is a Claude Code session with role-specific prompts, coordinated through a DAG execution engine. This cycle repeats — each sprint's results feed back into the Cortex, refining the focus and informing the next evaluation.
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.
- 2mo ago First seen · 589 lines · 11,646 tokens per session scan A 7519d00c1cc3
Enso CLAUDE.md is an instructions file published in the GitHub repository Proxy2021/Enso (6 stars, last pushed 5mo ago), licensed MIT. It adds 11,646 tokens to every session, about $0.0466 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.