Finance Tools MCP

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

With no annotations provided, the description carries full burden. It discloses that results show 'most popular' series and data may not be latest, adding useful behavioral context. However, it misses critical details like response format, pagination, error handling, or authentication needs, which are essential for a search tool with no structured annotations.

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 brief and front-loaded with the core purpose. Each sentence adds value: first states the action, second clarifies utility, third gives examples, fourth notes a limitation. There is no wasted text, though it could be more structured for clarity.

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?

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers basic purpose and a limitation but lacks details on parameters, return values, error cases, or integration with siblings. For a search tool with minimal structured data, this leaves significant gaps for an AI agent.

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%, so the description must compensate. It mentions 'keyword' which aligns with the 'query' parameter, but provides no additional semantics (e.g., format, examples beyond GDP/CPI, or search scope). With one undocumented parameter and minimal elaboration, it fails to adequately supplement the schema.

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 searches for FRED series by keyword, specifying the resource (FRED series) and verb (search). It distinguishes from siblings like 'get_fred_series' by focusing on keyword-based search rather than direct retrieval. However, it doesn't explicitly contrast with all siblings, keeping it at 4 instead of 5.

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 implies usage by mentioning 'useful for finding key data by name' and provides examples like GDP and CPI. It hints at limitations ('data is not always the latest'), but lacks explicit when-to-use vs. alternatives (e.g., 'get_fred_series' for specific series) or clear exclusions, leaving usage context somewhat vague.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.