chatfai-automation
by ComposioHQchatfai-automation skill for automating Chatfai workflows through Composio Rube MCP. Learn setup requirements, connection checks, tool discovery, and safe usage patterns that search current schemas before execution.
This skill scores 66/100, meaning it is acceptable for directory listing but should be presented as a lightweight MCP workflow guide rather than a complete Chatfai automation package. Directory users get enough information to know it requires Rube MCP and an active Chatfai connection, and agents get a repeatable discovery-first pattern, but the repository evidence is thin on concrete Chatfai-specific workflows and installation support.
- Valid frontmatter clearly names the skill and declares the required MCP dependency: `rube`.
- Prerequisites and setup are explicit: Rube MCP must expose `RUBE_SEARCH_TOOLS`, the Chatfai toolkit connection must be active via `RUBE_MANAGE_CONNECTIONS`, and users are told how to add `https://rube.app/mcp`.
- The skill gives agents a concrete execution pattern to search current tool schemas before acting, reducing schema guesswork for dynamic Composio tools.
- No support files, scripts, README, or install command are provided beyond the single SKILL.md, so adoption depends on already knowing how to add the Rube MCP endpoint.
- The workflow guidance is mostly a generic Rube discovery/check/execute pattern and does not document specific Chatfai operations or example end-to-end tasks.
Overview of chatfai-automation skill
What chatfai-automation does
chatfai-automation is a Claude skill for automating Chatfai operations through Composio’s Rube MCP toolkit. Its main value is not a fixed list of Chatfai commands; it teaches the agent to discover the current Chatfai tool schemas first, verify the connection, then execute the right Rube MCP tool with less guesswork.
Use this skill when you want an agent to help perform Chatfai-related actions from a Claude-compatible environment that supports MCP tools, especially when the available Chatfai API actions may change over time.
Best-fit users and workflows
The chatfai-automation skill is best for users who already use Chatfai and want workflow automation through an AI assistant rather than manual dashboard work. It fits tasks such as checking available Chatfai actions, preparing character or conversation operations, validating connection state, and running repeatable Chatfai workflows through Composio.
It is most useful for operators, builders, and automation-focused users who can describe the desired Chatfai outcome clearly and are comfortable approving tool calls.
What makes this skill different
The important design choice is the “search tools first” pattern. Instead of assuming a hard-coded schema, chatfai-automation instructs the agent to call RUBE_SEARCH_TOOLS before execution. That matters because MCP tool names, required fields, and allowed parameters can differ from memory or older examples.
This makes the skill safer for live workflow automation: discover capabilities, check the Chatfai connection, inspect the returned schema, then run the selected tool.
Main adoption requirements
To use the chatfai-automation skill, you need Rube MCP available in your client and an active Chatfai connection managed through Composio. The source skill specifically depends on the rube MCP server and expects RUBE_SEARCH_TOOLS and RUBE_MANAGE_CONNECTIONS to be available.
If your AI client cannot connect to MCP servers, or if you do not have a Chatfai account/connection to authorize, this skill will not be useful yet.
How to Use chatfai-automation skill
Install chatfai-automation and connect Rube MCP
Install the skill from the Composio skills repository:
npx skills add ComposioHQ/awesome-claude-skills --skill chatfai-automation
Then add Rube MCP to your client configuration using:
https://rube.app/mcp
After MCP is connected, verify that RUBE_SEARCH_TOOLS is visible. Next, use RUBE_MANAGE_CONNECTIONS with toolkit chatfai to check whether your Chatfai connection is active. If it returns an authorization link, complete that flow before asking the skill to run Chatfai workflows.
Start with tool discovery, not execution
A good chatfai-automation usage pattern is:
- Ask the assistant to use
RUBE_SEARCH_TOOLSfor your specific Chatfai task. - Review the returned tool slugs, schemas, required fields, and warnings.
- Ask the assistant to confirm the Chatfai connection with
RUBE_MANAGE_CONNECTIONS. - Provide any missing IDs, names, content, or options required by the discovered schema.
- Approve execution only after the assistant summarizes the intended tool call.
This prevents failed calls caused by guessed field names or outdated examples.
Turn a rough goal into a strong prompt
Weak prompt:
“Use Chatfai to update my bot.”
Stronger prompt:
“Use chatfai-automation for Workflow Automation. First search Rube tools for the current Chatfai schema. I want to update the Chatfai character named Support Ava so its greeting is shorter and more helpful. Check the Chatfai connection first, tell me which tool and fields are required, then wait for my confirmation before executing.”
This prompt gives the skill a target object, desired change, safety instruction, and discovery requirement. If you know Chatfai IDs, connection names, character names, conversation IDs, or content constraints, include them up front.
Files to read before relying on it
The repository path is composio-skills/chatfai-automation, and the main file to inspect is SKILL.md. There are no extra scripts, references, rules, or metadata files in the current file tree, so the operational behavior is concentrated in that one skill document.
Read SKILL.md for the required MCP dependency, setup flow, discovery-first workflow, and example Rube calls. Also review Composio’s Chatfai toolkit documentation at composio.dev/toolkits/chatfai when you need the broader platform context.
chatfai-automation skill FAQ
Is chatfai-automation beginner-friendly?
It is beginner-friendly if your AI client already supports MCP and you are comfortable following an authorization link. It is not a one-click Chatfai app. The skill assumes you can connect Rube MCP, approve tool calls, and provide task-specific Chatfai details when the discovered schema asks for them.
Can I use ordinary prompts instead?
You can ask a general AI assistant for Chatfai advice, but ordinary prompts may invent tool names or use stale parameters. The chatfai-automation skill is better when you want the assistant to operate through live Composio/Rube tools because it requires discovery of the current schema before execution.
What does this skill not do?
It does not include custom scripts, offline Chatfai clients, bundled examples, or a complete list of every Chatfai action. It also does not bypass authentication. If the Chatfai connection is inactive, the correct workflow is to use RUBE_MANAGE_CONNECTIONS, complete auth, and only then continue.
When should I avoid this skill?
Avoid it if you only need conceptual Chatfai writing help, if your environment cannot use MCP, or if you cannot authorize a Chatfai connection. Also avoid using it for high-impact bulk changes without adding your own review step, dry-run plan, or confirmation checkpoint.
How to Improve chatfai-automation skill
Improve chatfai-automation results with better inputs
The skill performs best when you provide the business goal and the operational identifiers. Include the Chatfai object type, name or ID, desired action, content to create or update, constraints, and whether the assistant should execute immediately or wait.
Example:
“Find current Chatfai tools, confirm the chatfai connection is active, then prepare a tool call to create a character named Museum Guide. Tone: warm, concise, historically accurate. Do not execute until you show me the required fields and final payload.”
Handle common failure modes early
The most common blockers are missing MCP access, inactive Chatfai authorization, unclear target objects, and guessed schemas. Fix them by explicitly asking the assistant to verify RUBE_SEARCH_TOOLS, run RUBE_MANAGE_CONNECTIONS, and report missing required fields before execution.
If a call fails, do not retry blindly. Ask the assistant to compare the attempted payload with the latest returned schema and identify which field, type, permission, or connection status caused the error.
Add confirmation checkpoints for safer automation
For workflow automation, add a two-step approval pattern: “discover and draft” first, “execute after confirmation” second. This is especially important for edits, deletions, or bulk operations inside Chatfai.
A practical checkpoint summary should include the selected Rube tool slug, target Chatfai object, required fields, optional fields being omitted, expected result, and known pitfalls returned by tool discovery.
Iterate after the first output
After the first run, ask for a reusable prompt template based on the successful schema. Store the required fields, connection assumptions, and review steps in your own project notes. That turns chatfai-automation from a single-use helper into a repeatable Chatfai workflow pattern while still preserving the skill’s key rule: search tools first for current schemas.