Seed Demo Leads

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

Annotations provide limited behavioral detail (readOnlyHint=false, destructiveHint=false). The description adds valuable context: each call appends a fresh batch with new UUIDs, returns counts by status and sample IDs. No contradictions.

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?

Concise paragraph front-loading the core action. Every sentence adds value: counts, archetypes, enrichment state, downstream tools, use case, safety, return info. No waste.

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 no output schema, the description fully explains return values (counts by status plus sample_lead_ids) and mentions use with other tools. Complete for a demo seeding tool.

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?

No parameters exist in the input schema, so the description cannot add meaning beyond schema. With 100% coverage, baseline is 4. No additional parameter info needed.

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: 'Populate the pipeline with a realistic demo dataset: 14 leads across 5 archetypes'. It uses specific verbs and resources, distinguishing it from sibling tools like lead_ingest and lead_batch_ingest.

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: 'Use this to evaluate LeadPipe via MCP Inspector without Hunter, HubSpot, or Pipedrive API keys'. Also notes it is safe to call multiple times. Could improve by suggesting alternatives for real data, but current guidance is clear.

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