Set the suggested prompts shown as clickable chips in the website chatbot, e.g. ['See pricing', 'Book a demo']. Replaces the existing list.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Which chatbot, when there is more than one | |
| suggestions | Yes | Prompts to show as chips |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as a write operation (readOnlyHint=false), and the description adds the key behavioral detail that the existing suggestion list is replaced. This is meaningful transparency beyond the structured annotation. It doesn't discuss side effects like persistence or UI updates, but the replacement disclosure is valuable.
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?
A single sentence communicates the action, the target, the expected input format with example, and the replacement semantics. It is front-loaded and contains no filler, making it easy for an agent 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?
For a simple two-parameter tool with full schema coverage, the description plus schema covers the essential calling information, including the domain disambiguation and suggestions array. The only minor gap is that the description doesn't explicitly mention how to handle multiple chatbots, but the schema already addresses that.
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?
Schema coverage is 100%, so the baseline is 3. The description adds a concrete example of valid suggestion values and clarifies that the array fully replaces the existing list, reinforcing the semantic of the 'suggestions' parameter. This exceeds the schema's basic description.
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 names a specific action—setting suggested prompts—and a precise resource: the website chatbot's clickable chips. It gives a concrete example and states the overwrite behavior, making the tool's purpose unmistakable and distinct from sibling tools like show_suggestions.
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 implies usage when you want to set chatbot suggestion chips, but it offers no explicit guidance on when to use this tool instead of alternatives like show_suggestions or update_chatbot_links. There are no conditions, exclusions, or sibling comparisons.
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.
Several tools occupy nearly identical roles (create_contact/add_contacts/save_contacts_to_crm/upload_contacts; add_companies/create_company; search_contacts/search_crm_contacts/find_contacts_at_companies), and the names don't clearly reveal whether they operate on saved or prospected data. Although the descriptions clarify some boundaries, an agent would frequently need to read many descriptions carefully to avoid mis-selection.
Most tools follow a snake_case verb_noun pattern such as list_campaigns, create_deal, and update_contact. Minor deviations like company_intelligence, get_icp, load_more_contacts, and the inconsistent use of add_/create_/upload_/save_ for similar creation actions keep it from being fully consistent.
51 tools is far beyond the well-scoped range and exceeds the 50+ extreme threshold. Even for a broad CRM/prospecting/marketing platform, exposing this many tools at once makes agent selection costly and unwieldy.
Contact and company creation/read/update are covered, but delete is absent across the board, and campaigns can be drafted, listed, and measured but not edited, activated, paused, or deleted. Deals, forms, and landing pages also lack update/delete lifecycle actions, creating meaningful dead ends for common CRM workflows.
