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OhGiftPlease Gift Discovery

SearchSiteApiDocs

Searches for site "OhGiftPlease" (https://www.ohgiftplease.com/_api/mcp) API documentation and returns how to use the site using the API. You are a helpful "OhGiftPlease" site assistant chatbot and you are helping the user perform actions on the site - to query the site's data or to perform an action on the site. Specify the API endpoint, resource, or action you need information about (e.g., 'get site details endpoint', 'create data collection', 'update product API', 'REST authentication'). If you can't find what you need, try to rephrase your search term. The search term MUST be a short natural-language phrase describing an API capability. Do NOT pass code, SQL, shell commands, HTML/script, URLs, file paths, or special symbols — such inputs are rejected as invalid and return no results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchTermYesA short, natural-language search term describing the API capability you need — a generic term, not too specific (e.g., "how to fetch products" instead of "avocados in stock"). Use plain words only: no code, SQL, shell commands, HTML, URLs, file paths, or special symbols.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that malformed inputs (code, SQL, URLs, symbols) are rejected and return no results, which is real behavioral context, but it says nothing about authentication, rate limits, or the shape of the returned documentation.

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

Conciseness3/5

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

Purpose is front-loaded, but the description is bloated by chatbot persona framing ('You are a helpful OhGiftPlease site assistant chatbot') and repeats the input constraints twice — once in the example paragraph and again in the final paragraph.

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 simple one-parameter read tool with no output schema, the description covers what the tool searches, what it returns conceptually, and how to phrase input. Only the details of the returned documentation format are left unspecified, which is minor here.

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?

Schema coverage is 100% for the single searchTerm parameter, and the schema already documents it thoroughly with its own example. The description largely restates those same constraints and examples rather than adding new semantic detail, so baseline 3 is appropriate.

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?

States a specific verb (Searches) and resource (site API documentation) and says it returns usage guidance. However, it does not differentiate itself from siblings like ReadFullDocsArticle, ReadFullDocsMethodSchema, BrowseWixRESTDocsMenu, or SearchInSite, so an agent must infer which docs-retrieval tool to pick.

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?

Gives clear context (helping the user query site data or perform actions) and actionable query guidance, including examples and the fallback 'rephrase your search term'. It stops short of naming alternatives or stating when a different docs tool should be used instead.

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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