What is learn-workspace-intent?

A command that learns the operational purpose of a workspace from its contents and saves the result for later use.

Use it to analyze a workspace and create an intent file that other Contorium views and exports can use.

It gives the add-on a structured understanding of the project, which can improve generated context and exports when configured AI access is available.

learn-workspace-intent — Command for Claude Code by ContoriumLabs

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.

Clone the repo

git clone --depth 1 https://github.com/ContoriumLabs/contorium

Made for: Claude Code.

Or install contorium, the plugin that ships this one along with the rest of its 1 skill, 5 commands, 1 MCP server.

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/commands/contoriumlabs/contorium/learn-workspace-intent.svg)](https://agentmods.dev/commands/contoriumlabs/contorium/learn-workspace-intent)

Your own site

<a href="https://agentmods.dev/commands/contoriumlabs/contorium/learn-workspace-intent"><img src="https://agentmods.dev/badge/commands/contoriumlabs/contorium/learn-workspace-intent.svg" alt="Measured on agentmods" height="20"></a>

Per session 20 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 129 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	$0.00020	$0.00129
Opus 5	$0.00010	$0.00064
Sonnet 5	$0.00004	$0.00026
Haiku 4.5	$0.00002	$0.00013

Measured 8d ago against content hash 686a00ca30a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

learn-workspace-intent 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 8d 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.

commands/learn-workspace-intent.md · 13 lines

What it actually says