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Search Byteland

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Find people, projects and stacks across every resident of the city (people, projects, stacks), plus buildings on the street by username, name, project or technology (results). Private projects never appear.

Input Schema

NameRequiredDescriptionDefault
langNoLanguage of text fields (recipe, badges, topic names). Default: en.
modeNokume (default): the founder’s real building with vacant buildings; bos: topic city, everyone vacant; ornek: demo street full of sample profiles.
seedNoStreet seed. Default: gece-sehri.
queryYes
radiusNoStreet chunks to scan on both sides (1 chunk = 80 m). Default 4.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Since there are no annotations, the description carries the full burden. It successfully discloses the scope (city-wide) and a key behavioral rule (privacy filtering), which is valuable context.

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?

The description is highly efficient. It is a single paragraph that uses strong, specific verbs and immediately communicates the scope and one major functional constraint, without unnecessary filler.

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

Completeness3/5

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

Given the complexity of the inputs (including language, mode, and radius), the description is a 'minimum viable' explanation. It covers the 'what' and 'where,' but the specific meanings of complex parameters like 'mode' are deferred to the schema.

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 schema coverage is high (80%), meaning the schema provides most of the semantic meaning. The description focuses on the general search function rather than providing deep meaning beyond what the structured schema already covers.

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?

Clearly states the tool's purpose is to 'find people, projects and stacks' plus 'buildings on the street.' It specifies the scope as 'across every resident of the city,' which distinguishes it from granular tools like get_profile.

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

Usage Guidelines3/5

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

It provides a critical limitation ('Private projects never appear'), which serves as a usage guideline for when to expect certain data. It implies when not to use it (if private data is needed), but does not explicitly recommend it over siblings.

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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