Page through contacts stored in a saved list without making a new Sales Navigator request.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of contacts to return (1–100, default 25) | |
| listId | Yes | The unique identifier of the contact list | |
| offset | No | Number of contacts to skip for pagination (default 0) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses a significant behavioral trait: it does not make a new Sales Navigator request, implying cached data and potential staleness. This is useful context not covered by 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 a single sentence, front-loaded with the action ('Page through contacts'), and contains no redundant information. Every word contributes value.
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 pagination tool with strong annotations and full schema coverage, the description is sufficient. It explains the core use case and the key limitation (no new request). It does not detail return format, but the absence of an output schema makes that less critical given the simplicity.
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 fully documents all three parameters (limit, listId, offset) with descriptions and ranges. The description adds no additional parameter-specific meaning, so the baseline of 3 is appropriate.
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: 'Page through contacts stored in a saved list' with a specific verb and resource. It also adds scope ('without making a new Sales Navigator request') that distinguishes it from sibling tools like contact_lists-get or contacts-search.
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 clear context for when to use the tool—when you want to iterate over contacts that already exist in a saved list, avoiding a new API request. It implies a prerequisite (the list is already saved) and suggests it for pagination scenarios, but does not explicitly name alternatives or state 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.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as signals-firmographics vs companies-enrich_firmographics, findEmail vs contacts-enrich_work_email, and monitors vs signal_subscriptions vs market_signals. While descriptions add some context, an agent could easily select the wrong tool due to the high similarity in function.
Most tools use a resource_subresource-action pattern, but there are inconsistent separators: underscores within some names, hyphens in others (e.g., scoring-assignment-bulk-create), and several camelCase exceptions (findEmail, findEmailBatchGet, getContactResearchByExternalID). This mixed convention makes the tool set feel unpredictable.
With 119 tools, this server vastly exceeds the typical well-scoped range. Even for a comprehensive B2B data platform, the sheer number creates cognitive overload and increases the risk of incorrect tool selection.
The server covers an extensive range of operations: enrichment, lists, contacts, signals, subscriptions, monitors, and scoring. Nearly every resource has create, read, update, and delete or lifecycle equivalents, leaving very few practical gaps for the intended use case.
