HeyLead

Overview Schema Source Related Servers Discussions Admin

engage_prospect

Destructive

Comment, react, follow, or endorse LinkedIn prospects to build trust and warm them up before outreach. Automates engagement so you can start conversations naturally.

Instructions

Comment on, react to, follow, or endorse a prospect on LinkedIn to build trust.

Finds a prospect's recent posts, generates a voice-matched comment
(or reacts with a Like), and sends it. Use action="follow" to follow
a prospect's profile — this triggers a "X started following you"
notification and warms them up before connecting. Use action="endorse"
to endorse their skills — triggers a high-visibility notification.
Great for social selling, warm-up engagement, and building familiarity
before cold outreach.

Args:
    campaign_id: Which campaign to engage from. Uses active campaign if empty.
    outreach_id: Specific outreach to engage with. Auto-picks next if empty.
    action: "auto" (comment if post has text, react otherwise),
        "comment" (always comment), "react" or "like" (just like the post),
        "view" (view their LinkedIn profile — lightest warm-up signal),
        "follow" (follow their LinkedIn profile as a warm-up signal),
        "endorse" (endorse their skills — highest visibility warm-up),
        "reply_comment" (reply to prospect's response on your comment thread).

Input Schema

TableJSON Schema

Name	Required	Default
`action`	No	auto
`campaign_id`	No
`outreach_id`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.375Sep 18, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is not read-only and has destructive potential. The description adds valuable behavioral detail beyond that: it generates a voice-matched comment, sends reactions, and explains that follow/endorse trigger LinkedIn notifications. This gives an agent a realistic sense of external side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a one-line summary, a behavior overview, usage context, and a clear Args section. It is somewhat long, but nearly every sentence adds necessary information since the schema itself provides no parameter documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with three optional parameters, the description covers all parameter semantics, core behavior, action variants, and the intended social-selling context. An output schema exists, so return-value documentation is not required from the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden for parameters. It clearly explains campaign_id, outreach_id, and every action value including edge behavior like 'auto' choosing comment vs reaction and 'Uses active campaign if empty.' This fully compensates for the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description leads with concrete verbs tied to a clear resource: 'Comment on, react to, follow, or endorse a prospect on LinkedIn to build trust.' This clearly distinguishes engage_prospect from sibling tools like send_message or send_email, which are about direct messaging rather than public LinkedIn engagement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use the tool: 'Great for social selling, warm-up engagement, and building familiarity before cold outreach.' It also explains different action modes and their purposes, but it does not explicitly name alternative tools or state when not to use this tool, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.