GoodLeads

Look up one lead by ID

find_lead_by_glid

Read-onlyIdempotent

One record in full, by its Lead ID (e.g. GL-CO-00042).

Use this when you already hold a Lead ID — from a file, a CRM, a receipt —
and want everything we know about that business and its owner: the
business, the primary contact, both scores, every attribute, and where
each field came from.

Args:
    glid: The Lead ID, e.g. `GL-CO-00042` — the `lead_ref` field on every
        record. Case-insensitive.

Returns:
    The full lead detail dict, including a `_meta` provenance block
    (schema_version, freshness incl. this record's last update, source,
    score_versions, access_level). Raises ValueError if the id is not
    shaped like a Lead ID or no record matches.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`glid`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 10, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses return shape, the `_meta` provenance block, freshness/source behaviors, and raises ValueError for malformed or unmatched IDs. This gives complete behavioral expectations.

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 structured with a lead sentence, use-case context, Args, and Returns. Every sentence adds operational value, and there is no redundant repetition of the schema or annotations.

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 one-parameter lookup with rich annotations and an output schema, the description is complete: it covers when to use it, how to format the parameter, what the response contains, and what errors can occur. Nothing essential is missing.

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

Parameters5/5

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

The input schema only provides the property name, but the description fully compensates by explaining the format (`GL-CO-00042`), case-insensitivity, and that it maps to the `lead_ref` field. This is exactly what an agent needs to construct a valid call.

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 operation ('One record in full, by its Lead ID') and immediately gives an example ID format. It clearly distinguishes this from listing/browsing tools by framing it as a targeted lookup when you already hold a Lead ID.

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?

Explicitly says 'Use this when you already hold a Lead ID' and explains what data you get. It does not name sibling tools or exclusions, but the intended context is clear enough to route an agent appropriately.

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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