agentmods.dev

bluebox CLAUDE.md

Development instructions for the VectorlyApp/bluebox codebase. They document how to set up the Python environment, run tests and benchmarks, and use the project's browser-monitoring and discovery commands.

In plain words
What is it for?
Use them when working on bluebox: create or activate its Python environment, install it for development, run the test suite or benchmarks, and start browser monitoring or routine discovery.
Why use it?
They give agents a consistent way to prepare the project, verify changes, and run its development tools. The supplied excerpt is specific to this codebase and does not describe a general add-on.

Instructions file

201 5mo ago A scan 3,431 tokens original Apache-2.0
View the source file VectorlyApp/bluebox
Install

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.

agentmods
npx agentmods add instructions/vectorlyapp/bluebox/claude-md
Clone the repo
git clone --depth 1 https://github.com/VectorlyApp/bluebox
Per session 3,431 This file is loaded in full into every session.
When invoked 3,431 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.03431 $0.03431
Opus 5 $0.01716 $0.01716
Sonnet 5 $0.00686 $0.00686
Haiku 4.5 $0.00343 $0.00343

Measured 2d ago against content hash 877105bf2efb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bluebox 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 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Verify: `curl http://127.0.0.1:9222/json/version`
CLAUDE.md · 295 lines

How it starts

The opening of the file, as written. The whole thing — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.

bluebox Development Guide

This file provides context and guidelines for working with the bluebox codebase.

Bash Commands

Development Setup

  • uv venv bluebox-env && source bluebox-env/bin/activate - Create and activate virtual environment (recommended)
  • python3 -m venv bluebox-env && source bluebox-env/bin/activate - Alternative venv creation
  • uv pip install -e . - Install package in editable mode (faster with uv)
  • pip install -e . - Install package in editable mode (standard)

Testing

  • pytest tests/ -v - Run all tests with verbose output
  • pytest tests/unit/test_js_utils.py -v - Run specific test file
  • pytest tests/unit/test_js_utils.py::test_function_name -v - Run specific test
  • python scripts/dev/run_benchmarks.py - Run routine discovery benchmarks
  • python scripts/dev/run_benchmarks.py -v - Run benchmarks with verbose output

CLI Tools

  • bluebox-monitor --host 127.0.0.1 --port 9222 --output-dir ./cdp_captures --url about:blank --incognito - Start browser monitoring
  • bluebox-discover --task "your task description" --cdp-captures-dir ./cdp_captures --output-dir ./routine_discovery_output --llm-model gpt-5.2 - Discover routines from captures
  • bluebox-execute --routine-path example_data/example_routines/amtrak_one_way_train_search_routine.json --parameters-path example_data/example_routines/amtrak_one_way_train_search_input.json - Execute a routine
  • bluebox-api-index --cdp-captures-dir ./cdp_captures --task "your task" --output-dir ./api_indexing_output --model gpt-5.2 --post-run-analysis - Run the API indexing pipeline (exploration + routine construction)
  • bluebox-agent-adapter --agent NetworkSpecialist --cdp-captures-dir ./cdp_captures - Start HTTP adapter for programmatic agent interaction (see Agent HTTP Adapter section below)
  • bluebox-agent-adapter --list-agents - List all available agents and their required data

Chrome Debug Mode

  • macOS: /Applications/Google Chrome.app/Contents/MacOS/Google Chrome --remote-debugging-address=127.0.0.1 --remote-debugging-port=9222 --user-data-dir="$HOME/tmp/chrome" --remote-allow-origins='*' --no-first-run --no-default-browser-check
  • Verify: curl http://127.0.0.1:9222/json/version

Read the full file on GitHub · 295 lines

Changes

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.

  1. 2d ago First seen · 295 lines · 3,431 tokens per session scan A 877105bf2efb

Subscribe to this mod's changes

bluebox CLAUDE.md is an instructions file published in the GitHub repository VectorlyApp/bluebox (201 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 3,431 tokens to every session, about $0.0172 per session on Opus 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 2026-08-30.

Backend and APIsData and AITestingai-agentsai-web-appai-websiteapibrowser-automationcdp
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