Get the full QueryQuarry reference (how it works, all tools and filters, search tips, rate limits, privacy). Call this when you need detail beyond these tool descriptions, when guiding a new user, or before composing a complex search.
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Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds useful context about the document's scope (rate limits, privacy, etc.). It does not describe return format or size, but given annotations cover safety, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded with the action and resource, then lists contents and usage scenarios. Every clause adds value; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a documentation tool with no parameters and no output schema, the description covers what it returns, why it exists, and when to call it. It is fully sufficient for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter info, which is fine because there are none to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the full QueryQuarry reference and lists its contents (how it works, tools, filters, tips, rate limits, privacy). It uses a specific verb ('Get') and resource, and is easily distinguished from sibling tools that perform specific data operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use scenarios: needing detail beyond tool descriptions, guiding new users, or before composing complex searches. However, it does not name specific alternative tools or state when not to use it, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: subscription, candidate search, detailed view, contact management, stats, docs, new candidates, watchlist, outcome reporting, and saving. No two tools overlap in purpose; the descriptions clearly differentiate them.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_subscription, get_candidate, search_candidates). The verbs vary as needed for different actions, maintaining a predictable structure.
With 11 tools, the set is well-scoped for a candidate sourcing platform. It covers search, detailed viewing, contact, watchlist management, subscription, and documentation without being excessive or too sparse.
Core workflows are covered: search, view, request contact, report outcome, save to watchlist. Minor gaps exist, such as lacking a remove-from-watchlist tool or a way to cancel a contact request, but these do not severely hinder the main use case.