raw_query

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 the tool runs arbitrary queries and suggests introspection for field discovery. However, it does not mention potential risks, rate limits, authentication, or that queries may fail. The behavioral traits are moderately transparent but could be more explicit.

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 concise at three sentences. The first sentence immediately clarifies purpose, the second adds version-specific details, and the third provides a practical tip. No extraneous words; every sentence adds value. Well-structured and front-loaded.

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 the tool's complexity (arbitrary GraphQL, multiple versions, optional parameters) and lack of output schema, the description covers the core idea and key hints. However, it omits details about the return format (raw GraphQL response), error handling, or any constraints. It is adequate for basic use but leaves gaps for an agent needing full context.

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 description adds meaningful context beyond the schema, such as which entities are exposed per Uniswap version (V2: pairs, swaps, tokens; V3/V4: pools, swaps, tokens) and that omitting version uses the highest-volume one. It also recommends running introspection queries, which helps the agent understand how to use the parameters effectively.

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's purpose: 'run an arbitrary GraphQL query against the resolved Uniswap subgraph for a (chain, version).' It uses specific verbs and resources, and clearly distinguishes itself from sibling tools which cover specific queries. The 'Escape hatch' label further indicates it is a fallback for custom needs.

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 implicitly indicates when to use this tool (when other tools do not cover the desired query) by calling it an 'Escape hatch'. It provides hints like running introspection queries first. However, it does not explicitly state exclusions or directly compare to siblings, leaving some ambiguity.

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