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get_home_feed

Read-onlyIdempotent

Read the account's own LinkedIn home feed, as on linkedin.com/feed: recent posts from its connections and the people and pages it follows, plus posts LinkedIn shows because a connection reacted or commented (feed_reason). Returns up to 10 posts per page with the text, the engagement and the author (name, headline, member id, relationship degree). Ads and suggestion carousels are left out. First call with start=0; for the next page pass back next_start and pagination_token. Use to find posts to engage with among the people the account already knows or follows (connections, followed creators and pages); for a topic across all of LinkedIn use search_posts. Then like_post or comment_post with post_urn. The feed is ranked by LinkedIn and changes between calls, so read it page by page from start=0 rather than keeping offsets. One LinkedIn call per page; keep to a few pages per run. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startNo0 for the first page, then next_start from the previous page.
account_idYesReach id of the LinkedIn account to act on, from list_accounts.
pagination_tokenNopagination_token from the previous page. Omit on the first page.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
postsNo
startNo
next_startNoPass as start, with pagination_token, for the next page.
pagination_tokenNoPass back with next_start for the next page; null when LinkedIn has no more.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, idempotentHint=true), yet the description adds genuinely non-obvious behavior: the feed is ranked by LinkedIn and shifts between calls, so offsets must not be cached; pagination is cursor-driven via next_start/pagination_token; and there is a practical rate constraint ('one LinkedIn call per page; keep to a few pages per run').

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?

Dense but front-loaded: what the feed is, what it contains, what's excluded, then pagination, then when to use vs. the alternative. The trailing 'Read-only' is redundant against readOnlyHint, and a couple of clauses restate the same scoping idea, but almost every sentence carries information.

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?

With an output schema present, return values need no explanation, and the description still covers what the caller must know: items per page, pagination contract, feed volatility, exclusions, and downstream actions. Nothing needed to call this correctly appears to be missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds sequencing semantics beyond the schema: 'First call with start=0; for the next page pass back next_start and pagination_token,' plus the warning against reusing offsets. That explains how the three parameters relate rather than just what each is.

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?

States a specific verb+resource (read the account's LinkedIn home feed) and pins down scope precisely: recent posts from connections and followed people/pages, plus feed_reason items, excluding ads and suggestion carousels. It also distinguishes itself from siblings by naming search_posts for topic-wide search and list-oriented tools implicitly via the 'people the account already knows or follows' framing.

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

Usage Guidelines5/5

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

Explicitly says when to use it (finding posts to engage with among known connections/followed creators) and when not to (for a topic across all of LinkedIn, use search_posts). It also chains the workflow forward: 'Then like_post or comment_post with post_urn.'

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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