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Kepler CRM

Get Record

get_record
Read-onlyIdempotent

Reads one record in full by exact id: all standard fields, custom fields by slug, version, and the few related rows needed next (a candidate's applications with stage and status, a job's company and open application counts, a list's member ids). Requires an id from a search or list result. Use this before any update so you have expected_version. Never guess an id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUUID
record_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark it read-only and idempotent, and the description adds meaningful behavioral context: the return includes standard fields, custom fields by slug, version, and selected related rows. It also discloses the version-related requirement for safe updates, which is valuable beyond the annotations.

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 information-dense but well organized: purpose first, then output details, then usage guidance. Every sentence earns its place, with no filler or repetition of schema data.

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?

For a two-parameter read tool with an output schema and read-only annotations, the description covers all necessary operational context: how to obtain a valid id, what data to expect, and how to use the result for updates. Nothing critical is missing for correct invocation.

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?

With 50% schema coverage, the description compensates by explaining the id must come from a search or list result and must not be guessed. It also illustrates record_type impact through examples like candidate applications and job company counts, though it does not explicitly define every enum value.

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 states a specific verb and resource ('Reads one record in full by exact id') and enumerates what 'full' includes, distinguishing it from list/search tools. It also gives concrete record-type examples, so an agent can immediately understand the tool's scope.

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?

It provides clear usage context: requires an id from a search or list result, use before updates to get expected_version, and never guess an id. It does not explicitly name sibling alternatives, but the prerequisite flow is implied through 'Requires an id from a search or list result.'

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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