Add a custom field to CRM leads (e.g. 'Budget' of type number). type: text | number | date | url (default text). A key is generated from the label.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Field type. Default 'text'. | |
| label | Yes | Display name of the field. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-destructive behavior. The description adds value by revealing that a key is automatically generated from the label and that 'type' defaults to 'text'. This provides behavioral context beyond what annotations cover.
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?
Two sentences pack all essential information: purpose with example, type enumeration with default, and key generation. No extraneous words, highly efficient.
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?
Given only two parameters, no output schema, and annotations present, the description covers the tool's purpose, parameter types, defaults, and automatic key generation. It is sufficient for an agent to use the tool correctly, though it could mention success/error behavior.
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 both parameters are documented. The description adds meaning by explaining the purpose ('Add a custom field'), providing an example, and clarifying the default for 'type' and the key generation from 'label'. This enhances understanding beyond the schema alone.
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 action ('Add a custom field to CRM leads') with a specific example ('Budget' of type number). It distinctly differentiates from sibling tools like 'set_lead_fields' (which sets values) and 'add_crm_stage' (which adds stages), making the 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 implies usage for creating new custom fields but does not explicitly state when to use this tool versus alternatives (e.g., 'set_lead_fields' for setting field values, 'list_crm_fields' for viewing). No guidance on 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.
Most tools have distinct purposes, but there is some overlap among search tools (search_job_postings, search_google_xray, search_linkedin_people, search_web) and messaging tools (send_connection_request, send_linkedin_message, reply_to_chat). However, detailed descriptions clarify the differences.
All tools follow a consistent verb_noun snake_case pattern (e.g., add_contacts_to_campaign, list_campaigns). No mixing of conventions.
48 tools is high but justifiable given the broad domain (LinkedIn outreach, CRM, campaigns, job postings, etc.). However, some tools could be consolidated (e.g., multiple search tools).
The tool set covers the entire workflow: searching, connecting, messaging, campaign management, CRM operations (fields, stages, tasks, notes), job postings, and posting. No obvious gaps.
