Borrowing it
Nothing to install: this file belongs to valory-xyz/trader. 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/valory-xyz/trader/main/CLAUDE.mdgit clone --depth 1 https://github.com/valory-xyz/traderWrote 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/valory-xyz/trader/claude-md)<a href="https://agentmods.dev/instructions/valory-xyz/trader/claude-md"><img src="https://agentmods.dev/badge/instructions/valory-xyz/trader/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 | $0.03071 | $0.03071 |
| Opus 5 | $0.01536 | $0.01536 |
| Sonnet 5 | $0.00614 | $0.00614 |
| Haiku 4.5 | $0.00307 | $0.00307 |
Grade A, and why
trader 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 6d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
The Trader repo hosts the Olas prediction-market agents. A single agent package (valory/trader) is shipped as two services:
| Service | Stack name | Chain | Venue |
|---|---|---|---|
valory/trader_pearl |
Omenstrat | Gnosis | Omen |
valory/polymarket_trader |
Polystrat | Polygon | Polymarket (CLOB v2) |
Both run as single-agent (sovereign) deployments distributed via Pearl. The agent queries an AI Mech for probability estimates, evaluates profitability, and executes on-chain via a Safe multisig. Built on Open Autonomy (ABCI skills, FSMs, content-addressed packages); Tendermint is framework plumbing, not the deployment shape.
When working locally with make run-agent / aea-helpers run-agent, the agent-level aea-config.yaml defaults are Omen-flavored — service-level polymarket_trader/service.yaml overrides only apply under autonomy deploy. Local Polystrat dev requires explicit overrides (IS_RUNNING_ON_POLYMARKET=true, MECH_CHAIN_ID=polygon, DEFAULT_CHAIN_ID=polygon, pUSD-scaled STRATEGIES_KWARGS, the Polymarket TOOLS_ACCURACY_HASH, and the chain-specific market-filter flags). See README.md for the full set.
Tech Stack
- Framework: Open Autonomy
- Package management:
uv(versions pinned inpyproject.toml— check there for the current Python range and dependencies; do not duplicate them here) - Task running:
Makefile+tox - Lint / format:
tomte(wraps black, isort, flake8, mypy, pylint, darglint, bandit) - Tests:
pytest+hypothesis
Common Commands
Testing
# Run all skill tests (pick the env that matches your interpreter; 3.10–3.14 supported)
uv run tox -e py3.10-linux # or py3.11/3.12/3.13/3.14-linux, *-darwin, etc.
# Run a single skill's tests
uv run pytest packages/valory/skills/<skill_name>/tests/ -v
# Run a specific test
uv run pytest packages/valory/skills/<skill_name>/tests/test_behaviours.py::TestClassName::test_method -v
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.
- 6d ago First seen · 224 lines · 3,071 tokens per session scan A aa0399c10178
trader CLAUDE.md is an instructions file published in the GitHub repository valory-xyz/trader (77 stars, last pushed yesterday), licensed Apache-2.0. It adds 3,071 tokens to every session, about $0.0154 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
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).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
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).
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.
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.
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.