List Pipeline Leads

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying the return format ('JSON: { "leads": StoredLead[], "count": number }') and the fields of StoredLead, which helps the agent understand what the tool produces. It does not contradict 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 well-structured with a one-sentence summary, an Args section, a Returns section, and Examples. Every element adds value and there is no unnecessary verbosity. The use of code blocks and examples makes it easy to parse.

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?

Despite having no output schema, the description fully documents the return structure. It covers the optional parameters, provides usage examples, and given the simple nature of the tool (list with filters) and the rich annotations, the description is complete enough for an agent to use it correctly. Sibling tools are also distinguishable.

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?

With schema description coverage at 0%, the description compensates by explaining that category, tier, and status are optional filters, and provides examples showing how each filter can be used. It also describes the StoredLead fields, which clarifies what the filters operate on. This goes beyond the raw schema enums, though it could be more explicit about the meaning of each parameter.

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 'Lists saved leads from the pipeline, optionally filtered by category, tier, or status.' This uses a specific verb ('lists') and resource ('saved leads from the pipeline'), and distinguishes from sibling tools like discover, enrich, score, save, update, which perform different actions.

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 concrete usage examples: 'Use when: "Show me all hot e-mobility leads" -> category="e_mobility", tier="hot"' and 'Use when: "What's still uncontacted?" -> status="new"'. This gives clear context for when to use the tool and how to map natural language queries to parameters, though it does not explicitly mention alternatives or when not to use it.

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