ANOLISA is a server-side operating layer for AI agent workloads that provides terminal access, token-saving tool-output compression, runtime controls, security, observability, skills, memory, and sandbox management. It is for running and supervising agents from a Linux terminal while retaining an existing shell, agent framework, and sandbox. The catalogue add-ons are components of its agent operating environment and workflows.
Borrowing it
Nothing to install: this file belongs to alibaba/anolisa. 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/alibaba/anolisa/main/AGENTS.mdgit clone --depth 1 https://github.com/alibaba/anolisaWrote 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/alibaba/anolisa/agents-md)<a href="https://agentmods.dev/instructions/alibaba/anolisa/agents-md"><img src="https://agentmods.dev/badge/instructions/alibaba/anolisa/agents-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/alibaba/anolisa/agents-md"><img src="https://agentmods.dev/badge/instructions/alibaba/anolisa/agents-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 | $0.05082 | $0.05082 |
| Opus 5.5 | $0.02033 | $0.02033 |
| Sonnet 5.5 | $0.01016 | $0.01016 |
| Haiku 4.5 | $0.00508 | $0.00508 |
Grade A, and why
anolisa 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 1mo 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 — 437 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides context for AI coding assistants (Qoder, Claude, etc.) working in this repository.
1. Project Overview
ANOLISA is a monorepo for an Agentic OS — a server-side operating layer designed for AI agent workloads.
| Component | Path | Tech | Platform |
|---|---|---|---|
copilot-shell (cosh) |
src/copilot-shell/ |
TypeScript / Node.js | All |
| cosh-ng | src/cosh-ng/ |
Rust | Linux (full); macOS (limited functionality) |
| agent-sec-core | src/agent-sec-core/ |
Rust + Python | Linux only |
| agentsight | src/agentsight/ |
Rust (eBPF) | Linux (full); macOS (trajectory/serve only) |
| tokenless | src/tokenless/ |
Rust | Linux (full); macOS x64/arm64 (CLI binaries + adapters, via npm) |
agent-memory (memory) |
src/agent-memory/ |
Rust | Linux only |
| os-skills | src/os-skills/ |
Python / Shell | All |
| anolisa | src/anolisa/ |
Rust | Linux + macOS (arm64) |
SkillFS (skillfs) |
src/skillfs/ |
Rust / FUSE | Linux only |
| ws-ckpt | src/ws-ckpt/ |
Rust + TypeScript | Linux only |
| ktuner | src/ktuner/ |
Rust | Linux only |
| blaze | src/blaze/ |
Rust | Linux only |
agent-sec-core,agent-memory,skillfs,ktuner, andblazerequire Linux.agentsightprovides full eBPF tracing on Linux and limited trajectory collection plus the local viewer on macOS.cosh-ngis Linux-first and supports limited functionality on macOS. Do not attempt to build the Linux-only components on macOS or Windows. (tokenless ships macOS CLI binaries and framework adapters via npm, but the binaries are cross-compiled from Linux — building tokenless on macOS is still unsupported.)
2. Development Commands
# Unified build (recommended — handles deps, build, and user install)
./scripts/build-all.sh # integrated default components
./scripts/build-all.sh --no-install # build only, skip install
./scripts/build-all.sh --ignore-deps # skip dependency setup and runtime verification
./scripts/build-all.sh --component cosh --component sec-core # selected components
# Partial convenience test runner (five components; may skip unavailable suites)
./tests/run-all-tests.sh
./tests/run-all-tests.sh --filter shell # copilot-shell only
./tests/run-all-tests.sh --filter sec # agent-sec-core only
./tests/run-all-tests.sh --filter sight # agentsight only
# copilot-shell (per-component)
cd src/copilot-shell
make deps # npm install + husky hooks (use make deps-ci in CI)
make build
make lint
make test
# cosh-ng (Linux full; macOS limited functionality, per-component)
cd src/cosh-ng
cargo build --workspace
cargo fmt --all -- --check
# Select the closest targeted test from src/cosh-ng/CONTRIBUTING.md.
# Full gates require a large/cross-cutting change and an explicit request.
# agent-sec-core (Linux only; Python 3.11.6 + uv, per-component)
cd src/agent-sec-core
make build-all
uv run --project agent-sec-cli python --version # must report 3.11.6
make test # Python + Rust sandbox + OpenClaw plugin tests
# agentsight (Linux full eBPF; macOS trajectory/serve only, per-component)
cd src/agentsight
# Linux
make build-all
make lint
make test
# macOS
make build-mac
# os-skills
cd src/os-skills # Skill definitions are static assets, no compilation needed
# tokenless (per-component)
cd src/tokenless
make build # tokenless + RTK + OpenClaw plugin
make lint
make test # Rust + hooks + integration + adapters
# agent-memory (Linux only, per-component)
cd src/agent-memory
make build # cargo build --release --locked
make fmt-check
make lint
make test # cargo test --locked
make smoke # end-to-end MCP stdio smoke test
# anolisa (per-component)
cd src/anolisa
cargo fmt --all --check
cargo clippy --all-targets --locked -- -D warnings
cargo test --locked
# ws-ckpt (Linux only, per-component)
cd src/ws-ckpt
make build # cargo build --release + openclaw plugin
make test # cargo test --workspace
# SkillFS (Linux only, per-component)
cd src/skillfs
cargo fmt --all --check
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace
scripts/test.sh # FUSE smoke test; skips itself if fuse3 or /dev/fuse is unavailable
# ktuner (Linux only, per-component)
cd src/ktuner
cargo fmt --all --check
cargo clippy --all-targets -- -D warnings
cargo test
# blaze (Linux only, per-component)
cd src/blaze
cargo fmt --all --check
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace
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.
- 1mo ago First seen · 437 lines · 5,082 tokens per session scan A 89e5fce47205
anolisa AGENTS.md is an instructions file published in the GitHub repository alibaba/anolisa (603 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 5,082 tokens to every session, about $0.0203 per session on Opus 5.5. 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).
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.