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/katanemo/plano/claude-mdgit clone --depth 1 https://github.com/katanemo/planoWrote 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/katanemo/plano/claude-md)<a href="https://agentmods.dev/instructions/katanemo/plano/claude-md"><img src="https://agentmods.dev/badge/instructions/katanemo/plano/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 | $0.01270 | $0.01270 |
| Opus 5 | $0.00635 | $0.00635 |
| Sonnet 5 | $0.00254 | $0.00254 |
| Haiku 4.5 | $0.00127 | $0.00127 |
Grade A, and why
plano 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 4d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Plano is an AI-native proxy server and data plane for agentic applications, built on Envoy proxy. It centralizes agent orchestration, LLM routing, observability, and safety guardrails as an out-of-process dataplane.
Build & Test Commands
# Rust — WASM plugins (must target wasm32-wasip1)
cd crates && cargo build --release --target=wasm32-wasip1 -p llm_gateway -p prompt_gateway
# Rust — brightstaff binary (native target)
cd crates && cargo build --release -p brightstaff
# Rust — tests, format, lint
cd crates && cargo test --lib
cd crates && cargo fmt --all -- --check
cd crates && cargo clippy --locked --all-targets --all-features -- -D warnings
# Python CLI
cd cli && uv sync && uv run pytest -v
# JS/TS (Turbo monorepo)
npm run build && npm run lint && npm run typecheck
# Pre-commit (fmt, clippy, cargo test, black, yaml)
pre-commit run --all-files
# Docker
docker build -t katanemo/plano:latest .
E2E tests require a Docker image and API keys: tests/e2e/run_e2e_tests.sh
Architecture
Client → Envoy (prompt_gateway.wasm → llm_gateway.wasm) → Agents/LLM Providers
↕
brightstaff (native binary: state, routing, signals, tracing)
Crates (crates/)
- prompt_gateway (WASM) — Proxy-WASM filter for prompt processing, guardrails, filter chains
- llm_gateway (WASM) — Proxy-WASM filter for LLM request/response handling and routing
- brightstaff (native) — Core server: handlers, router, signals, state, tracing
- common (lib) — Shared: config, HTTP, routing, rate limiting, tokenizer, PII, tracing
- hermesllm (lib) — LLM API translation between providers. Key types:
ProviderId,ProviderRequest,ProviderResponse,ProviderStreamResponse
Python CLI (cli/planoai/)
Entry point: main.py. Built with rich-click. Commands: up, down, build, logs, trace, init, cli_agent.
Config (config/)
plano_config_schema.yaml— JSON Schema for validating user configsenvoy.template.yaml— Jinja2 template → Envoy configsupervisord.conf— Process supervisor for Envoy + brightstaff
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.
- 4d ago First seen · 107 lines · 1,270 tokens per session scan A 2138ac5aa390
plano CLAUDE.md is an instructions file published in the GitHub repository katanemo/plano (7,033 stars, last pushed 14d ago), licensed Apache-2.0. It adds 1,270 tokens to every session, about $0.0064 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
gateway CLAUDE.md
Instructions for Portkey-AI/gateway, covering claude.md, project overview, development commands, core development and testing.
prompty copilot-instructions.md
Instructions for microsoft/prompty, covering prompty v2 — complete rebuild plan, what prompty uses from the typra-generated model, key design decisions, python coding rules and environment & tooling.
neuron-ai AGENTS.md
AGENTS.md instructions for neuron-core/neuron-ai, covering neuron ai - project overview, the mental model: neuron is a composable workflow, development commands, architecture and modules.
neuron-ai CLAUDE.md
Claude Code instructions for neuron-core/neuron-ai, covering project overview, code standards, think before coding, simplicity first and surgical changes.
zentinel AGENTS.md
Instructions for zentinelproxy/zentinel, covering zentinel, philosophy (north star), architecture, crates and core crates.
Guardrails AGENTS.md
AGENTS.md instructions for NVIDIA-NeMo/Guardrails, covering agents.md, agent skills, quick rules, repository map and setup.