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Dot-Fun

Fathom AI MCP Server

by Dot-Fun

get_summary

Retrieve the summary of any meeting recording. Optionally deliver it asynchronously to a destination URL.

Instructions

Get the summary for a specific meeting recording.

If destination_url is provided, the summary will be delivered asynchronously to that URL. Otherwise, the summary is returned directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recording_idYesThe ID of the meeting recording
destination_urlNoOptional URL for async summary delivery

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals a key behavior: if destination_url is provided, the summary is delivered asynchronously; otherwise it is returned directly. This adds meaningful context beyond the raw schema, though it omits further details like error handling or permissions.

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?

Two concise sentences with information front-loaded. Every phrase earns its place, explaining both the primary purpose and the key conditional behavior without redundancy.

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. The description covers the core purpose and the only behavioral nuance (async vs direct), making it complete for a tool of this simplicity.

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%, providing baseline 3. The description adds value by explaining the conditional effect of destination_url (async vs direct delivery), which is not fully explicit in the schema. This helps the agent understand the parameter's role in selecting behavior.

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?

The description clearly states the action ('Get') and the specific resource ('summary for a specific meeting recording'), distinguishing it from sibling tools like get_transcript. It also clarifies the scope (specific recording), leaving no ambiguity.

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?

The description provides clear context on when to use this tool (to retrieve a summary for a given recording) and explains behavior with destination_url. It does not explicitly mention alternatives or exclusions, but the context is sufficient for an agent to decide.

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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