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RyanKramer

ShipPost MCP

by RyanKramer

analyze_account

Analyze a Twitter account to identify the user's profile, posting topics, and engagement patterns, helping you decide whether to engage with them and understand their audience.

Instructions

Analyze a Twitter account — who they are, what they post about, engagement patterns.

Useful for deciding whether to engage with someone or understanding their audience.

Requires a ShipPost API key (SHIPPOST_API_KEY). Get one at https://shippost.ai

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesTwitter username without @ (e.g. "elonmusk")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are present, so the description carries the burden of behavioral disclosure. It appropriately reveals the API key requirement (SHIPPOST_API_KEY) and the nature of the output, but it does not explicitly state that the operation is read-only, mention rate limits, or describe error behavior for invalid usernames. The output schema covers return structure, so the gap is moderate.

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?

Three sentences: purpose, use case, and auth requirement. No filler, front-loaded main action, every sentence earns its place.

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

Completeness4/5

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

For a single-parameter tool with an output schema, the description covers purpose, usage context, and auth prerequisite. It lacks explicit differentiation from sibling profile tools (e.g., get_user_profile), which would improve completeness, but overall it's adequately self-contained.

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

Parameters4/5

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

The single parameter is fully described in the schema with format examples, so baseline is 3. The description adds value beyond the schema by mentioning the required SHIPPOST_API_KEY configuration, giving context about the environment needed to run the tool.

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

Purpose4/5

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

The description clearly identifies the action ('Analyze a Twitter account') and specifies the scope of analysis: 'who they are, what they post about, engagement patterns.' This distinguishes it from raw-data tools like get_user_profile or get_timeline, though it doesn't explicitly name alternatives, so it stops short of a full 5.

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?

Provides explicit context: 'Useful for deciding whether to engage with someone or understanding their audience.' This gives a clear reason to invoke the tool but does not mention exclusions or alternatives, so it's a solid 4 rather than a 5.

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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