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Facts for an opening line

opening_line_facts
Idempotent

What to write an opening line to one company from: what just happened there (a trial, a hire, an FDA decision, funding, news), each with its source, and from the rep's own profile the service it calls for, their closest past project, a certification the company asked for, and the angle when the company already uses another firm or resembles their clients. Also says how the company fits the rep (territory, stage) and who they already know there. Returns the facts, not the lines. Looking a company up here also counts it toward what Whimbrel learns the rep is drawn to, shown and removable on their Memory page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior5/5

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

Annotations declare readOnlyHint=false on what looks like a read tool, and the description explains exactly why: 'Looking a company up here also counts it toward what Whimbrel learns the rep is drawn to,' with the fact that it is shown and removable on the Memory page. It discloses a non-obvious persistent side effect plus its reversibility, which the annotations alone could not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and every clause carries content, but the body is one sprawling run-on sentence that mixes return contents, rep-profile matching, and memory semantics without structural breaks. Dense with value yet hard to parse on first read.

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

Completeness4/5

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

With no output schema, the description enumerates the returned fact types and explicitly notes it returns facts rather than generated lines, and it covers the memory side-effect. The remaining gap is the input contract for 'company' and no guidance on result shape or volume.

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

Parameters2/5

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

There is a single required parameter at 0% schema description coverage, so the description must carry the format. It says 'one company' but never clarifies whether the value is a name, a domain, or an ID, nor what happens on ambiguity or no-match. It leaves the only parameter's contract under-specified.

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 names a specific resource (facts used to write an opening line for one company) and enumerates the categories of facts it composes — recent events with sources, rep-profile matches, certifications, competitive angle, fit, and known contacts. 'Returns the facts, not the lines' crisply states the deliverable. It stops short of naming which sibling (company, news, account) to use instead, so it lacks explicit differentiation.

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

Usage Guidelines3/5

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

Usage is implied by the phrase 'What to write an opening line to one company from,' which tells the agent this is the pre-outreach research call. There is no statement of when not to use it, no prerequisites, and no routing to alternative siblings. The memory side-effect is disclosed but framed behaviorally rather than as a usage caveat.

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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