A project-discipline command that helps choose how much Cortex-related checking to apply before building. Cortex is Snowflake’s set of AI features for working with data.

Use it to select lite, full, or ultra mode and run the associated pre-build decision checks.

It makes the project’s checking intensity explicit, so the same level of review can be applied consistently.

cocolean — Skill for Claude Code by Snowflake-Labs

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.

Any agent

npx skills add Snowflake-Labs/cocoplus --skill lean

Clone the repo

git clone --depth 1 https://github.com/Snowflake-Labs/cocoplus

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/lean.svg)](https://agentmods.dev/skills/snowflake-labs/cocoplus/lean)

Your own site

<a href="https://agentmods.dev/skills/snowflake-labs/cocoplus/lean"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/lean.svg" alt="Measured on agentmods" height="20"></a>

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,253 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00041	$0.01253
Opus 5	$0.00020	$0.00626
Sonnet 5	$0.00008	$0.00251
Haiku 4.5	$0.00004	$0.00125

Measured 3d ago against content hash 0f4540257ab8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

cocolean 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.

.cortex/skills/cocolean/lean.skill.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Objective

You are executing CocoLean — the minimum viable Cortex surface discipline. Your task depends on how this skill was invoked:

$lean / $lean full — activate full mode (all three CocoLean modes), run the pre-build decision ladder
$lean lite — switch to lite mode (ladder only), run the pre-build decision ladder
$lean ultra — switch to ultra mode (full + enforcement), run the pre-build decision ladder
$lean with no prior context — treat as $lean full

Before proceeding, verify that .cocoplus/ exists. If not, output: "CocoPlus is not initialized. Run $pod init first." Then stop.

Step 1 — Set Intensity Level

Parse the invocation:

Command	Mode	Write to `.cocoplus/modes/lean.mode`
`$lean lite`	`lite`	`lite`
`$lean full`	`full`	`full`
`$lean ultra`	`ultra`	`ultra`
`$lean`	`full` (default)	`full`

Write the mode string to .cocoplus/modes/lean.mode. Confirm: "CocoLean mode set to [mode]."

If .cocoplus/modes/lean.mode already exists, read its current value and note the change: "CocoLean mode changed from [previous] to [new]."

Step 2 — Run the Pre-Build Decision Ladder

Surface the six-rung Cortex-adapted decision ladder. Present it as a checklist the developer must work through before writing any new Cortex AI function, pipeline stage, or subagent:

CocoLean Decision Ladder — work top to bottom, stop at the first YES:

[ ] Rung 1: Can a deterministic rule, SQL expression, lookup table, or threshold accomplish this without AI inference?
[ ] Rung 2: Does a Snowflake native built-in handle it? (FLATTEN, MATCH_RECOGNIZE, window functions, conditional expressions, SEARCH, OBJECT_CONSTRUCT…)
[ ] Rung 3: Does an existing UDF, stored procedure, or Cortex function in this project already solve this?
[ ] Rung 4: Would a single AI_COMPLETE call with a well-scoped prompt be sufficient?
[ ] Rung 5: Can the minimum working function be written in under ten lines? (Write the minimum version first — complexity is earned, not assumed.)
[ ] Rung 6: A full Cortex function or multi-stage pipeline is justified. Proceed to build.

Read the full file on GitHub · 102 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.

3d ago First seen · 102 lines · 41 tokens per session scan A 0f4540257ab8

Subscribe to this mod's changes

cocolean is a skill published in the GitHub repository Snowflake-Labs/cocoplus (720 stars, last pushed 4d ago), licensed MIT. It adds 41 tokens to every session and 1,253 once invoked, about $0.0002 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 2026-09-03.

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