ask_library
Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Plain-language question to answer from your report library |
Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Plain-language question to answer from your report library |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, establishing that this is a safe read operation. The description adds behavioral context by mentioning it synthesizes an answer and includes citations, which is useful. It does not contradict annotations and provides sufficient transparency for a query tool.
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 description is a single, concise sentence that front-loads the primary action and scope. It includes the key output detail (synthesized answer with citations) without any fluff, making it exceptionally efficient.
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 tool with one parameter, no output schema, and comprehensive annotations, the description is complete. It explains the purpose, scope, and expected return form. Nothing an agent needs to decide whether to call this tool is missing, especially given the read-only and idempotent hints.
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 schema description coverage is 100%, so the 'question' parameter is fully documented. The tool description does not add extra semantics about the parameter beyond restating that it is a plain-language question. This meets the baseline of 3 but does not elevate it.
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 states a specific verb ('ask'), a precise resource ('all your delivered analyses'), and the expected output ('synthesized answer with citations back to specific reports'). This clearly distinguishes it from report listing or viewing tools and conveys its Q&A nature.
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?
The description gives a clear context: it is for asking a question across the entire report library. It implies when to use it but does not explicitly state when not to use it or name alternatives such as 'answer_now' or 'find_precedent'. Since there are many siblings, the lack of explicit exclusions is a minor gap, but the context is sufficiently scoped.
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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