lookup_pipelines

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it returns pipelines (id and name), requires user confirmation even for single results, and outlines a multi-step workflow. However, it doesn't mention potential errors, rate limits, or authentication needs, leaving some gaps in behavioral context.

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 well-structured and front-loaded with purpose and usage guidelines. It uses bullet points for clarity but includes some redundancy (e.g., repeating parameter details in a list). Every sentence adds value, though it could be slightly more concise by integrating the parameter explanations more seamlessly.

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 complexity (multi-step workflow, 4 parameters with 0% schema coverage) and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage, behavioral workflow, and parameter semantics thoroughly, leaving no critical gaps for agent operation.

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 schema description coverage is 0%, so the description must compensate. It provides detailed semantics for all four parameters: 'query' (search string with syntax examples), 'entity_type' (default and purpose), 'page' (0-based), and 'size' (max and default). This adds significant value beyond the bare schema, fully documenting parameter usage.

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: 'Look up pipelines by name (for leads).' It specifies the verb ('look up'), resource ('pipelines'), and context ('for leads'), distinguishing it from sibling tools like get_pipeline_stages or search_leads. The purpose is specific and actionable.

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 provides explicit guidance on when to use this tool: 'Use when the user asks for leads by stage (e.g. open/closed/won/lost) but does not specify which pipeline.' It also specifies sequencing ('Call this first; do NOT call get_pipeline_stages until after the user confirms the pipeline') and alternatives, making it highly actionable for an agent.

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