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/snowflake-labs/snowflake-ai-kit/agents-mdgit clone --depth 1 https://github.com/Snowflake-Labs/snowflake-ai-kitWrote 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/snowflake-labs/snowflake-ai-kit/agents-md)<a href="https://agentmods.dev/instructions/snowflake-labs/snowflake-ai-kit/agents-md"><img src="https://agentmods.dev/badge/instructions/snowflake-labs/snowflake-ai-kit/agents-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 | $0.00929 | $0.00929 |
| Opus 5 | $0.00464 | $0.00464 |
| Sonnet 5 | $0.00186 | $0.00186 |
| Haiku 4.5 | $0.00093 | $0.00093 |
Grade A, and why
snowflake-ai-kit AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Guidelines — snowflake-ai-kit
What This Repo Is
Developer tools for building on Snowflake with AI coding agents. Includes a Claude Code plugin (auto-routes Snowflake prompts to Cortex Code) and installers (shell + PowerShell + npx).
Architecture
plugins/
cortex-code/ ← Claude Code plugin (v3.0.1)
.claude-plugin/plugin.json ← plugin manifest
hooks/hooks.json ← UserPromptSubmit hook (prompt_filter.py)
scripts/router/
prompt_filter.py ← keyword detection, fires additionalContext
discover_cortex.py ← finds Cortex CLI + discovers skills
execute_cortex.py ← spawns cortex CLI, credential blocking
route_request.py ← indicator scoring + skill trigger matching
skills/
cortex-router/ ← auto-routing skill
cortex-run/ ← explicit invocation ($cortex-run)
cortex-setup/ ← CLI install + connection setup
install.sh / install.ps1 / bin/install.mjs ← one-command installers
tests/
run-tests.sh ← bash test runner (Mac/Linux)
run-tests.ps1 ← PowerShell test runner (Windows)
validate-install.ps1 ← install validation
.github/workflows/
test.yml ← CI: runs tests on macOS + Windows
Critical Rules
- Never commit credentials. Use environment variables or Snowflake built-in auth.
- License: Root LICENSE is Apache 2.0.
- Branch protection: PRs required on main.
- README uses HTTPS clone URLs (not SSH) — keep it that way for external users.
Plugin Scripts
prompt_filter.py— readsmessagefield from stdin JSON. ReturnsadditionalContextfor Snowflake-related prompts,{}otherwise.discover_cortex.py— finds Cortex CLI binary and parses skill output. Has Windows/macOS/Linux path handling.execute_cortex.py— spawnscortexCLI subprocess. Key behaviors: credential path blocking (CREDENTIAL_PATTERNS), break-on-result,process.terminate()cleanup. Thestdin=DEVNULLfix prevents the subprocess from stealing terminal input — do not remove it.route_request.py— scores prompts via keyword indicators and skill trigger matching. Known issue: single-word trigger matching at line 88 can produce false positives.
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.
- 5d ago First seen · 78 lines · 929 tokens per session scan A c580bd8c95a2
snowflake-ai-kit AGENTS.md is an instructions file published in the GitHub repository Snowflake-Labs/snowflake-ai-kit (37 stars, last pushed 22d ago), licensed Apache-2.0. It adds 929 tokens to every session, about $0.0046 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
GPT-RAG release.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.
apex-accelerator vendor-prompting.instructions.md
Vendor prompting best-practice rules for Anthropic Claude and OpenAI GPT-5.6-Terra agents and prompts. Each rule cites a rule ID in the vendor-prompting skill rules.json registry. Validator: npm run lint:vendor-prompting.
ken CLAUDE.md
Claude Code instructions for townsendmerino/ken, covering claude.md, what this is, repository ownership (read this first), commands and embedding parity & golden fixtures (now in aikit).
rag-code-mcp copilot-instructions.md
Instructions for doITmagic/rag-code-mcp, covering copilot instructions - ragcode mcp, ⚖️ the golden rule, project overview, architecture & patterns and developer workflows.
ZipAI CLAUDE.md
Claude Code instructions for nickdesi/ZipAI, covering claude.md — zipai: ultra-dense token optimizer, rules, 1. zero filler, 2. ambiguity and 3. prompt caching.
TreeSkill CLAUDE.md
Instructions for JimmyMa99/TreeSkill, covering claude.md, project overview, commands, install and run tests.