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Onsa

Get lead research memo

get_lead_memo
Read-onlyIdempotent

Returns the research memo Onsa's agent wrote about one lead: role history, company size and stage, what they have said publicly, and the angle on them. It is usually far richer than scoreExplanation, and it is the source material for outreach built on a specific, checkable fact rather than a generic opener. Most leads have no memo - Onsa writes one only for prospects it has researched - so memo: null is the common case and not an error, and scoreExplanation is the remaining source in that case.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leadIdYesLead to read, from any tool that returns leads

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
memoYes
nameYes
leadIdYes
companyNameYes
memoWrittenAtYes
scoreExplanationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds critical behavioral context beyond annotations: most leads have no memo, so a null return is common and not an error, and it clarifies the source of the memo (Onsa's agent). This is valuable and does not contradict any annotation.

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?

The description is concise yet comprehensive, using three sentences that each add distinct value: content of the memo, comparison to scoreExplanation, and the null-return behavior. No fluff or redundant phrasing; the most critical information (memo content and null case) is front-loaded.

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?

An output schema exists, so return format is not needed. The description covers the tool's purpose, contents, typical null behavior, and relationship to the alternative source. Nothing an agent needs to invoke it correctly or interpret results is missing.

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% for the single parameter leadId, which already explains it is the lead to read. The description adds the hint 'from any tool that returns leads', which is mildly helpful but does not substantially alter parameter meaning. Baseline 3 is appropriate given full schema coverage.

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?

Description states a specific verb and resource: 'Returns the research memo' about one lead, and enumerates its contents (role history, company size/stage, public statements, angle). It clearly distinguishes itself from scoreExplanation by noting it is 'usually far richer' and serves as the basis for fact-based outreach. This differentiates it from sibling tools without opening any schema.

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 explains when to use it: for building outreach on a specific, checkable fact, and notes it is richer than scoreExplanation. It also states that when no memo exists (common case), scoreExplanation is the fallback. This gives clear context and implies alternatives, though it does not explicitly name a sibling tool or a hard 'when not to use' condition, so it loses one point.

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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