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Search Conversations

search_conversations

Search LinkedIn messages by keyword to locate relevant conversations. Filter with specific keywords to narrow results and limit message reads.

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 only annotation is openWorldHint, so the description carries most of the behavioral disclosure burden. It does not mention that enumerating results may mark conversations as read (noted only in the limit parameter description), nor does it disclose result-shaping behavior. 'Search' implies a read operation, but side effects are hidden.

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 compact, front-loaded sentence with no filler. It is easy to parse, but it is so terse that it contributes little beyond the tool name and parameter names, making it less effective than it could be.

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

Completeness3/5

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

For a two-parameter tool with an output schema and fully described parameters, the description is minimally adequate for invocation. However, it lacks usage guidance, scope clarification, and behavioral disclosures, so an agent cannot fully judge when to use it or what side effects may occur.

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 input schema already fully documents keywords and limit. The description adds no new parameter semantics beyond restating the keyword filter; it does not provide format details, examples, or constraints beyond what the schema offers.

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 states a specific action (search) and resource (messages), making the tool's core purpose clear. It is somewhat distinct from sibling search tools by focusing on messages, but it does not explicitly differentiate itself from related tools like get_inbox, get_conversation, or search_posts.

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 gives no guidance on when to use this tool versus alternatives such as get_inbox, get_conversation, or search_posts. There is no mention of scope, prerequisites, or situations where another tool should be preferred.

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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