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

Descriptions add substantial behavioral detail beyond the annotations: it names SwogeAgentic (a Claude agent) as the executor, explains it reads numbers and answers in Markdown with sources and sample sizes, discloses the API-key-only requirement, real-cost billing, optional quote behavior, and expected latency. All consistent with readOnlyHint=true and openWorldHint=true, no contradiction.

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 compact yet information-dense. It front-loads the purpose, then covers the agent behavior, costing, and timing. No filler sentences; every clause adds operational or decision-relevant information. Length is appropriate for the tool's complexity.

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 that chains multiple other tools and produces a written answer, the description covers all critical aspects: when to use, how it operates, cost model, timeout expectations, and output format (Markdown with sources and sample sizes). With no output schema, the description compensates fully. An agent has enough to decide whether and how to invoke it.

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 coverage is 100%, so each parameter is already documented. The description adds semantic value by explaining the 'quote' parameter in context (returns price without running) and framing the overall task as research. It goes beyond schema repetition by linking parameters to real-world usage and cost implications.

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 a specific purpose: chaining several tools together to produce a written answer, with concrete examples (comparing tokens, researching a launcher). It distinguishes itself from sibling tools by emphasizing the multi-tool orchestration and written response, leaving no ambiguity about its role.

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?

Explicitly states when to use it: when a question needs several tools chained and a written answer. Provides examples and practical constraints (API key required, 10-60 seconds latency, cost model). The description effectively implies that simple queries should use individual tools, and gives enough context to route the agent correctly.

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