get_reference_answers
Get reviewed evergreen examples and fixed editorial tiers, not today’s answers. Use topic IDs from list_reference_topics.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| topic | Yes | ||
| locale | No | en | |
| offset | No |
Get reviewed evergreen examples and fixed editorial tiers, not today’s answers. Use topic IDs from list_reference_topics.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| topic | Yes | ||
| locale | No | en | |
| offset | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that content is pre-reviewed, evergreen and tier-assigned, implying a stable, non-live snapshot, but says nothing about pagination limits, result ordering, or behavior when a topic has no reviewed examples.
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?
Two short sentences, front-loaded with the resource definition followed by the prerequisite pointer. No filler or redundant restatement of the tool name.
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 read-only lookup with rich annotations and no output schema, the essentials are present: what the data is, that it is not live, and where topic IDs come from. The remaining gaps around pagination, locale behavior, and return shape are moderate but not blocking.
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?
Schema description coverage is 0% for four parameters, so the description carries the burden and only partly delivers: it clarifies that `topic` takes IDs from list_reference_topics. It says nothing about `limit`, `offset`, or `locale`, leaving three parameters completely undocumented across both schema and description.
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?
States a specific verb (Get) and resource (reviewed evergreen examples and fixed editorial tiers), and explicitly contrasts it with 'today's answers', which separates it from a live-answer tool. The phrase 'fixed editorial tiers' is somewhat jargon-y, but the agent can still tell what it retrieves.
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?
Gives a concrete prerequisite work flow by naming list_reference_topics as the source of topic IDs, and implies a when-not ('not today's answers'). It does not, however, say when to prefer this over get_game_rules or describe a fallback if a topic is unknown.
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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