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jongall45

Frontrun MCP Server

by jongall45

frontrun_untrack

Stop tracking a Twitter/X account to discontinue monitoring its venture capital activities and signals on the Frontrun MCP Server.

Instructions

Stop monitoring a Twitter/X account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesTwitter/X username to stop tracking (without @)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states the action ('stop monitoring') but doesn't disclose behavioral traits like whether this requires authentication, what happens if the account isn't being tracked (error vs. no-op), whether it's reversible, or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place, and there's no redundancy or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a mutation operation to stop tracking), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what happens after stopping monitoring (e.g., does it return a confirmation?), potential errors, or prerequisites. For a tool that modifies state, more context is needed to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description doesn't mention parameters, but the input schema has 100% description coverage (the 'username' parameter is fully documented in the schema). With high schema coverage, the baseline is 3 even without param info in the description. The description doesn't add meaning beyond the schema, but it doesn't need to compensate for gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Stop monitoring') and the target resource ('a Twitter/X account'), distinguishing it from sibling tools like 'frontrun_track' (which likely starts monitoring) and 'frontrun_list_tracked' (which lists monitored accounts). The verb 'stop monitoring' is precise and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: it should be used when you want to cease tracking an account you're currently monitoring. However, it doesn't explicitly state when NOT to use it (e.g., if the account isn't being tracked) or name specific alternatives like 'frontrun_track' for the opposite action. The context is clear but lacks explicit exclusions or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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