list_projectsList REACH projects for the authenticated user.
Use this tool to find the right project before calling `show_project`.| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of returned projects | |
| search | No | Optional prefix search on project name |
| Name | Required | Description | Default |
|---|---|---|---|
| projects | Yes | Project summaries. created_at is an ISO-8601 timestamp. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds limited behavioral context beyond the annotations, such as the 'REACH' qualifier and the fact that it's for the authenticated user, but it doesn't elaborate on pagination, rate limits, or other behaviors. It's not contradictory and adequately supports the 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 remarkably concise, consisting of just two sentences. The first states the core action, and the second offers actionable guidance. No unnecessary words, perfectly front-loaded information.
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 simple read-only tool with two well-documented optional parameters, an output schema, and rich annotations, the description is complete. It explains the tool's purpose and provides a usage hint, covering all necessary aspects for an agent to use it correctly.
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 provides complete descriptions for both parameters ('Maximum number of returned projects' and 'Optional prefix search on project name'), giving 100% schema coverage. The description adds no additional parameter-level detail, which is acceptable as the schema already does the heavy lifting.
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 verb ('List'), the resource ('REACH projects'), and the scope ('for the authenticated user'). It also differentiates from siblings by indicating its role in preparation for `show_project`, making its purpose unambiguous.
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 a clear use case: 'Use this tool to find the right project before calling show_project.' This gives contextual guidance for when to use it, though it does not explicitly exclude alternatives or mention contrast with other list-type tools (e.g., list_lists), keeping it from a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct resource and action: list generation (B2B vs B2C), enrichment (contact, demographic, firmographic, C2B, IP-to-domain), project/list management, job lifecycle, and validation. No two tools appear to do the same thing, so an agent can reliably select the correct one.
All tool names follow the verb_noun pattern consistently, using verbs like list, show, create, preview, search, validate, append, and estimate. Even the segmented append tools (c2b_append, contact_append, demographic_append, firmographic_append, ip_to_domain_append) follow the same pattern with clear noun modifiers. No mixed conventions or vague verbs.
With 19 tools, this is on the higher side but still well-scoped for a data enrichment and list-building platform. The count covers distinct functional areas (audience estimation, enrichment, job/project management, list inspection, documentation) without unnecessary bloat. It feels slightly heavy but each tool earns its place.
The tool surface covers the core workflows: estimating audiences, creating and monitoring jobs, managing projects and lists, and enriching records with various data types. Minor gaps exist, such as no explicit delete/update operations for projects or lists, and no direct file download for list contents (though preview_list and show_list provide partial coverage). These are non-blocking gaps that agents can work around.