Reject the current drafts on a campaign_contact with textual feedback (e.g. 'too formal, shorten to 2 sentences'). Resets generation_status to 'pending' so a new version is generated based on your feedback, which again waits for approval.
| Name | Required | Description | Default |
|---|---|---|---|
| reason | Yes | Why the drafts were rejected (used as regeneration feedback) | |
| campaign_contact_id | Yes | UUID of the campaign_contact |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint and readOnlyHint false, but description adds the behavioral trait of resetting generation_status to 'pending', which provides context beyond the annotations. 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?
Two tightly written sentences with no extraneous information. The key action and effect are front-loaded.
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 the tool's purpose, parameters, and side effects. Given low complexity (2 params), it is complete.
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 covers 100% of parameters with descriptions. The description adds the meaning of 'reason' as regeneration feedback, providing beyond-schema value.
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 (reject), the resource (current drafts on a campaign_contact), and the effect (resets generation_status to 'pending'). It distinguishes from siblings like 'approve_message'.
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 when to use (to reject drafts with feedback for regeneration) and when not to use (when wanting to approve, as 'approve_message' is a sibling). However, it lacks explicit 'when not to use' statements.
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.
