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Jrudani21
by Jrudani21

Search Conversations

search_conversations

Find LinkedIn messages by searching conversation keywords. Returns up to 50 conversation references, defaulting to 20.

Instructions

Search messages by keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of search-result rows to enumerate as conversation references (1-50, default 20). Each enumeration selects the row in LinkedIn's UI and may mark it as read, so a low cap is preferable for noisy queries.
keywordsYesSearch keywords to filter conversations

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

The description discloses no behavioral traits beyond the openWorldHint annotation. It does not mention that results may mark conversations as read (as noted in the limit parameter description) or any other side effects, so the description adds no relevant context.

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 a single, concise sentence that directly states the core function. It is front-loaded and free of fluff, though it could include more useful information without becoming verbose.

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

Completeness2/5

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

For a search tool with a limit parameter that can mark items as read and with several sibling tools, the description is incomplete. It lacks information about result format, usage context, and alternatives, making it minimally viable at best.

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%, with detailed descriptions for both 'keywords' and 'limit'. The tool description adds nothing beyond the schema, so the baseline of 3 applies.

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 'Search messages by keyword' clearly identifies the action (search) and resource (messages/conversations). It distinguishes from 'search_posts' by targeting messages, but doesn't explicitly differentiate from 'get_inbox' or 'get_conversation'.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus sibling tools like get_inbox, get_conversation, or search_posts. There are no exclusions or alternative recommendations.

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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