TalaLevel

Search leads

search_leads

Read-onlyIdempotent

Find merchants (leads) by business name, contact name, email, phone number, or by what was said on their file ("asked about equipment" also finds "needs a new truck": words first, then meaning). Narrow by status, a saved list, starred, or only this person's own. Use it to get a lead id for get_lead; use search_what_was_said instead when the question is who said something rather than who someone is. Statuses are the workspace's own words: a status that does not exist is refused with the ones that do.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_leads"
  }
}

Input Schema

Name	Required	Description	Default
`mine`	No	Only leads owned by this person.
`sort`	No	recent: starred first, then most recently updated.	recent
`limit`	No	How many to return, at most 50 (more is cut to 50).
`query`	No	Words to find: a name, an email, a phone number in any format, or what was said.
`cursor`	No	The cursor a previous page of this tool gave, to read the next page. Leave it out for the first.
`status`	No	A lead status exactly as the workspace calls it, or "__none__" for leads with none.
`list_id`	No	Only leads on this saved list (ids from list_lists).
`starred`	No	Only starred leads.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so safety is covered. The description adds genuinely new behavior: matching is words-first-then-meaning with the 'asked about equipment' -> 'needs a new truck' example, and invalid statuses are rejected with the valid list returned. It does not explain result shape or the limit clamp, which is a smaller gap given the annotation coverage.

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

Conciseness4/5

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

Front-loaded with purpose in the first clause, then narrowing, then alternatives, then a caveat about statuses — a sensible order with no filler. The sentences are dense and multi-clause, and the status-validation note sits at the end where it is slightly easy to miss.

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 8 optional params fully documented, annotations present, and no output schema needed, the description covers purpose, routing, matching semantics, and one failure mode. Remaining gaps (pagination expectations, the limit cap) are partly handled in the schema but the schema's 500 maximum conflicts with the param text saying results are cut to 50 — a wrinkle the description does not address.

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%, so baseline is 3; the description goes beyond it by explaining the query's fuzzy/meaning-based semantics and clarifying that status strings must be the workspace's own vocabulary (invalid values are refused). It does not add anything for cursor, sort, or mine beyond the schema text.

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?

Opens with a concrete verb and resource (find merchants/leads) plus the fields searched, and explicitly contrasts itself with get_lead (id lookup) and search_what_was_said (who said it). An agent can route between these three 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 Guidelines5/5

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

States the primary use case ('use it to get a lead id for get_lead') and names the alternative with the exact condition that selects it ('when the question is who said something rather than who someone is'). Narrowing options (status, list, starred, mine) are enumerated as part of usage.

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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