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/googlecloudplatform/cxas-scrapi/agents-mdgit clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapiWhat 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 | $0.00805 | $0.00805 |
| Opus 5 | $0.00402 | $0.00402 |
| Sonnet 5 | $0.00161 | $0.00161 |
| Haiku 4.5 | $0.00081 | $0.00081 |
Grade A, and why
cxas-scrapi 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 3d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cxas-scrapi
This repository is a workspace and SDK for building and managing GECX (Google Customer Engagement Suite) conversational agents.
Repository Structure
cxas-scrapi/ # SDK source code
.agents/skills/ # Collection of reusable agent skills
├── cxas-agent-foundry/ # Composite skill for end-to-end agent lifecycle
├── cxas-sim-eval/ # Skill for converting evals
└── ...
<project_name>/ # (Optional) App-specific agent workspaces managed by skills (e.g., cymbal/)
.venv/ # Shared virtual environment
AGENTS.md # Workspace overview (this file)
.active-project # (Optional) Points to the currently active project folder
Setup
Run the setup script to create a virtual environment and install the cxas-scrapi SDK from the local source:
.agents/skills/cxas-agent-foundry/scripts/setup.sh # Full setup (install + configure)
.agents/skills/cxas-agent-foundry/scripts/setup.sh --configure # Reconfigure only
Requires Python 3.10+ and astral-uv.
- Always execute
cxascommands usinguv run cxasinstead of using .venv/.
Available Skills
This workspace provides several specialized AI skills to assist with development.
cxas-agent-foundry: The primary skill for the end-to-end GECX agent lifecycle. Use this for building agents from PRDs, generating and running evals, debugging failures, and syncing code.cxas-autolabel-rules: Author, validate, and manage Contact Center AI (CCAI) Insights Autolabeling Rules declaratively via YAML and CEL.cxas-configurable-dashboards: Author, validate, and manage CCAI Insights Configurable Dashboards declaratively via YAML, Vega-Lite specs, and SQL metrics queries.cxas-sim-eval: A utility skill for converting CXAS golden evaluations to SCRAPI SimulationEvals test cases.
CLI Features
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.
- 3d ago First seen · 49 lines · 805 tokens per session scan A ec5a463bc489
cxas-scrapi AGENTS.md is an instructions file published in the GitHub repository GoogleCloudPlatform/cxas-scrapi (94 stars, last pushed 6d ago), licensed Apache-2.0. It adds 805 tokens to every session, about $0.0040 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).
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.
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.
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 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).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.