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Outreach Path to Target

get_outreach_path

Given a target person, find the shortest warm-intro path through your engager network. Walks coworker (shared current company) + alumni (shared past company / school) edges. Up to 3 hops. Pure DB read — no LinkedIn pull, no credits charged.

Input Schema

NameRequiredDescriptionDefault
limitNoMax paths to return (default 10)
max_hopsNoMax path length (1=direct, 2=one intermediate, 3=two intermediates). Default 2.
target_person_idNoTarget — people.id UUID
target_linkedin_urlNoTarget — LinkedIn URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description proactively supplies the key behavioral facts an agent cares about: it is a pure DB read, performs no LinkedIn pull, and charges no credits, plus the hard 3-hop ceiling. It does not cover failure modes (no path found, missing identifier), which keeps it from a 5.

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

Conciseness5/5

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

Four short clauses, front-loaded with the purpose, and each adds distinct information: mechanism, edge types, hop limit, and cost/safety. Zero filler and nothing repeated from the schema.

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

Completeness4/5

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

No output schema and no annotations, so the description must carry the load; it covers mechanism, safety, cost, and scope well. Remaining gaps are what a returned path looks like and the requirement to supply one of the two target identifiers, which the agent is left to infer.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents limit, max_hops, and both target identifiers; the description only reinforces the hop cap ('up to 3 hops'). It adds nothing about the important ambiguity that target_person_id and target_linkedin_url are both optional yet at least one is presumably needed.

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

Purpose4/5

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

States a specific verb and resource — 'find the shortest warm-intro path through your engager network' — plus the edge types traversed (coworker, alumni) and the hop cap. This is enough to tell it apart from graph-ish siblings such as traverse_graph or map_constellation, though it never names an alternative explicitly.

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

Usage Guidelines3/5

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

Usage is implied: 'Given a target person' frames the scenario, and the network/mutual-connection premise makes the intent reasonably clear. But there is no explicit when-to-use versus when-not (e.g., LinkedIn pull vs. cached network, or when the target has no path), so the agent must infer the boundary.

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

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