finage-automation

Overview of finage-automation skill

What finage-automation is for

finage-automation is a Claude skill for automating Finage tasks through Composio’s Rube MCP server. Instead of assuming fixed tool names or stale parameters, the skill is built around a required discovery-first pattern: search Rube tools, verify the Finage connection, then execute the current Finage operation with the schema returned by Rube.

This makes the finage-automation skill most useful when you want an AI agent to work with live Finage tooling for market-data, financial-data, or account-connected operations without hardcoding a workflow that may break as the toolkit changes.

Best-fit users and workflows

Use finage-automation if you already use Claude with MCP tools and want a repeatable way to ask for Finage actions through Composio. It fits users who need Workflow Automation around Finage data access, reporting, lookup, enrichment, or recurring operational tasks, but still want the agent to validate available tools before acting.

It is especially relevant for:

• Claude Desktop or MCP-compatible client users
• Teams standardizing Composio/Rube-based financial data workflows
• Operators who need connection-aware Finage actions
• Developers who want prompts that respect live tool schemas instead of guessing inputs

What makes this skill different

The main differentiator is not a large helper library; the repository contains a focused SKILL.md. Its value is the operating pattern: always call RUBE_SEARCH_TOOLS first, use the returned schemas, check the Finage connection with RUBE_MANAGE_CONNECTIONS, and only then run the selected Finage tool.

That matters because financial-data automation often fails from schema drift, missing authentication, or vague tool selection. The skill tries to reduce those failures by making discovery and connection status part of the workflow, not an afterthought.

How to Use finage-automation skill

finage-automation install and MCP setup

Install the skill from the Composio skill collection with:

npx skills add ComposioHQ/awesome-claude-skills --skill finage-automation

The skill requires Rube MCP. In your MCP-compatible client, add the Rube endpoint:

https://rube.app/mcp

Then verify that RUBE_SEARCH_TOOLS is available. The Finage toolkit must also be connected through Rube. Use RUBE_MANAGE_CONNECTIONS with toolkit finage; if the connection is not active, follow the returned authorization link and confirm the status is ACTIVE before asking the agent to perform a Finage operation.

Inputs the skill needs from you

For best finage-automation usage, do not just say “get Finage data.” Give the agent the business goal, target entity, required fields, time range, output format, and any constraints.

Weak prompt:

Use Finage to get stock data.

Stronger prompt:

Use finage-automation via Rube MCP to retrieve the latest available Finage data for AAPL and MSFT. First search tools for the current Finage schema, verify the finage connection is active, then choose the correct tool. Return symbol, latest price, timestamp, and any source metadata in a compact table. If a required field is unavailable, explain what the tool supports instead of guessing.

This gives the skill enough context to search the right tools, avoid unsupported fields, and produce an auditable result.

Practical workflow for reliable execution

A good finage-automation guide workflow is:

1. Ask the agent to call RUBE_SEARCH_TOOLS for your specific Finage use case.
2. Have it inspect returned tool slugs, schemas, execution plans, and pitfalls.
3. Confirm the finage connection using RUBE_MANAGE_CONNECTIONS.
4. Execute the chosen tool with only schema-supported inputs.
5. Ask the agent to summarize what was called, what parameters were used, and what assumptions remain.

This is slower than a one-shot prompt, but it is safer for live tool automation because the agent is forced to align with the current Composio Finage toolkit.

Repository files to read first

The upstream skill is compact. Start with:

• SKILL.md — contains the prerequisites, setup steps, discovery pattern, and core workflow.

There are no visible support folders such as scripts/, rules/, resources/, or references/ in the previewed repository path, so your install decision should be based mainly on whether the SKILL.md workflow matches your MCP environment and Finage use case.

finage-automation skill FAQ

Is finage-automation useful without Rube MCP?

No. The skill explicitly depends on Rube MCP and the availability of RUBE_SEARCH_TOOLS. If your client cannot use MCP tools, or if Rube is not configured, this skill will not provide meaningful automation beyond a prompt template.

Is this better than an ordinary Claude prompt?

Yes, when the task involves real Finage tooling. A normal prompt may invent tool names or rely on outdated parameters. finage-automation instructs the agent to discover current tool schemas first and check the Finage connection before execution. For purely conceptual finance questions, however, a normal prompt may be enough.

Can beginners use this skill?

Beginners can use the finage-automation skill if they are comfortable adding an MCP server and following an authorization flow. The skill does not require writing code, but it does assume you can verify tool availability, complete a Finage connection, and understand whether the returned data matches your request.

When should I not install it?

Do not install it if you do not use Finage, do not want Composio/Rube in your workflow, need offline-only processing, or require a prebuilt application with dashboards and scheduled jobs. This skill is an agent workflow layer, not a standalone Finage client.

How to Improve finage-automation skill

Give finage-automation sharper task definitions

The most important improvement is input quality. Define the exact Finage operation in terms the tool search can match: asset type, symbols, market, date range, granularity, fields, and desired output.

Better request pattern:

Search Finage tools for historical daily OHLCV data for TSLA from 2024-01-01 to 2024-03-31. Verify the connection first. Use only fields present in the returned schema. Return CSV-style output and include any rate-limit or availability warning from the tool result.

This reduces schema mismatch and makes the agent’s tool choice easier to audit.

Watch for common failure modes

The most common blockers are inactive Finage connection, skipped tool discovery, vague use cases, and unsupported fields. If the first output fails, ask the agent:

• Which RUBE_SEARCH_TOOLS query did you run?
• Which Finage tool slug did you select?
• What schema fields were required?
• Was the finage connection active?
• Did any returned pitfall or limitation affect the result?

These questions turn a failed run into a debuggable workflow instead of another vague retry.

Iterate after the first result

After the first successful call, refine the output rather than rerunning blindly. Ask for narrower fields, a different format, validation against timestamps, or a second tool search if the initial result does not cover the target operation.

For recurring Workflow Automation, save the working prompt structure: discovery query, connection check, chosen output format, and validation notes. Reusing that structure gives you consistency while still preserving the skill’s discovery-first behavior.

Improve the upstream skill over time

If you maintain or fork finage-automation, consider adding examples for common Finage tasks, sample prompts, expected tool-discovery outputs, and troubleshooting notes for inactive connections. Because the current repository path is centered on a single SKILL.md, even a small set of practical examples would materially improve adoption and reduce guesswork for new users.