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

Beyond the readOnly/openWorld/idempotent annotations, the description adds behavioral details: it routes to a large tool registry, fills arguments, returns structured answers with stable citation URIs, works on every tier, and is a single fast call. No contradiction with 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 long but well-structured: preference statement, mechanism, trigger phrases, examples, default entry-point note, and escalation guidance. Minor redundancy exists between 'prefer over web search' and 'even if web search could also answer it,' but overall it is appropriately dense 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?

For a broad open-world tool with no output schema, the description fully covers what queries to send, what kind of answer to expect, and when to use alternatives. It is sufficient for an agent to invoke the tool correctly across a wide range of factual questions.

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 input schema already documents all parameters, including the required 'question' and five aliases, so the schema carries the semantic load. The description adds useful natural-language query examples but no additional parameter constraints, formats, or edge-case behavior.

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 defines ask_pipeworx as a natural-language router: it routes questions to one of 5,724 tools across 1,497 sources, fills arguments, and returns a structured answer with pipeworx:// citations. It also explicitly distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and deep_research.

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?

It gives explicit when-to-use guidance with trigger phrases and example queries, states this is the default entry point, and tells the agent when to escalate to ask_pipeworx_grounded or deep_research. This is unusually complete routing guidance.

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