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Flux LinkedIn MCP

Engager Position History

get_engager_position_history

Return a person's full employment timeline from the position graph. Person must have engaged on at least one of your collected posts (engagement gate). Sorted current-first, then most-recent past by started_at desc. Pure DB read — no LinkedIn pull, no credits charged.

Input Schema

NameRequiredDescriptionDefault
person_idNopeople.id UUID
linkedin_urlNoPerson's LinkedIn profile URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden and handles the most expensive unknowns well: 'pure DB read — no LinkedIn pull, no credits charged' removes cost risk, and the framing as a position-graph read sets expectations. It does not say what happens when the engagement gate is unmet (empty result vs. error) or whether the timeline is truncated.

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?

Three short sentences, each load-bearing: what it returns, the eligibility gate, the sort order, and the cost profile. No filler and the core purpose is front-loaded.

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?

For a two-param read with no output schema, the description covers the essentials — source, eligibility, ordering, and cost. The remaining gap is error/empty-state behavior and the identifier-selection rule, minor but relevant given both params are optional.

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 coverage is 100%, so both parameters are documented in the schema and the baseline applies. The description adds nothing about the person_id/linkedin_url relationship — with zero required parameters, the agent gets no guidance on whether one identifier is mandatory or which takes precedence.

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?

The description names a specific verb and resource — 'return a person's full employment timeline from the position graph' — which is far more precise than the title 'Engager Position History'. It does not name a sibling it replaces or contrasts with (e.g., get_profile_summary, traverse_graph), so the agent must infer boundaries from the sibling list alone.

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?

It states a concrete eligibility condition: the person must have engaged on at least one collected post. That is a real gate an agent needs before calling. It stops short of 5 because it never says what to do when the gate fails or which alternative to use for non-engagers.

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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