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sheepit-ai

sheepit-mcp

Official
by sheepit-ai

Sheepit help — what can I do?

sheepit_help

Get a curated overview of Sheepit MCP features or detailed help on specific areas like campaigns, dashboards, insights, and credentials.

Instructions

Returns a curated overview of what this MCP server can do, or a deep-dive on a specific area. Call this WITHOUT a topic when the user asks 'what can I do?' / 'how do I get started?' / 'what is Sheepit?' (or the Spanish equivalents — '¿qué es sheepit?' / '¿qué puedo hacer?' / '¿qué herramientas tiene sheepit?'). Call WITH a topic when the user asks about a specific area (campaigns, destinations, dashboards, insights, feedback, credentials). Pass language: 'es' when the user is writing in Spanish so the returned content matches their language.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional area to deep-dive on. Omit for a top-level overview that names every tool surface.
languageNoUser's conversation language. 'en' (default) or 'es' (neutral Latin American Spanish). Match the language the user is writing in.
Behavior4/5

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

No annotations exist, so description carries full burden. It discloses that the tool returns a curated overview and respects language preferences. Could mention that it is a read-only help tool, but the tone implies no side effects.

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

Conciseness4/5

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

Two sentences efficiently cover purpose and usage guidelines. Some detail could be trimmed (e.g., repeating 'the user is writing in') but overall no waste.

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?

No output schema, but description hints at content ('curated overview', 'deep-dive'). It doesn't specify format (e.g., list of tools), which would help agents, but for a help tool it is sufficient.

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?

Schema coverage is 100% with enum descriptions. The description adds value by explaining when to omit vs specify 'topic' and how to match 'language' to the user's conversation language, going beyond schema definitions.

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 tool returns a curated overview or deep-dive on a specific area, with explicit verb ('Returns') and resource ('overview of what this MCP server can do'). It distinguishes from siblings by focusing on generic 'what can I do?' queries.

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

Usage Guidelines5/5

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

The description explicitly says when to call without a topic (user asks about general capabilities) and with a topic (specific area). It also provides language matching instructions for Spanish, leaving no ambiguity.

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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