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Callvu

by com.callvu
OverviewDiscussionsAdmin

Find processes Callvu runs

find_processes
Read-onlyIdempotent

The process catalog for an industry (also at callvu.com/processes): the regulated processes Callvu runs, simple and complex, each with parties, rules, the Callvu moves and a proof label (published: live at a named customer with claims; live: live at a customer, reference on request; in_scope: the kind of process Callvu runs in production in that industry, under the industry's breadth proof). Search with query, filter by proof or complexity. Illustrative, not exhaustive.

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": "find_processes"
  }
}

Input Schema

NameRequiredDescriptionDefault
proofNo
queryNoThe process in the buyer's words, e.g. 'field technician dispatch'.
verticalNoA vertical slug, name or alias, for example "banking", "Home lending" or "mortgage". Case-insensitive.
complexityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare a safe, idempotent, closed-world read, so the description is free to add higher-value context — and it does, defining the three proof labels (published, live, in_scope) so the agent understands what confidence each result carries. It also discloses the catalog's limits ("Illustrative, not exhaustive") and an alternate access path, which annotations cannot convey. It stops short of saying how results are ordered or how large the catalog is.

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?

The purpose is front-loaded, but the opening sentence buries three nested proof-label definitions in a parenthetical, making it a dense run-on that is hard to parse on first read. All the content is relevant, yet the label glossary would serve better as separate sentences.

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 does the necessary work of enumerating what a returned process entry contains (parties, rules, Callvu moves, proof label) and warns that coverage is illustrative. Minor gaps remain around result ordering, count, and the vertical parameter's role, but nothing essential to calling the tool 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 coverage is 50%: query and vertical are documented, while proof and complexity carry only enum values. The description partially compensates by explaining what each proof label means, which is real value beyond the enum tokens, but it never mentions the vertical parameter at all despite listing it in the schema. That is roughly baseline for this coverage level.

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 the resource precisely: a catalog of regulated processes Callvu runs, with the fields each entry carries (parties, rules, Callvu moves, proof label). An agent can tell this is a process-search tool, though it does not explicitly contrast itself with the similarly-named find_use_cases sibling, leaving the boundary to inference.

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?

"Search with query, filter by proof or complexity" gives implied usage instructions for the parameters, and "Illustrative, not exhaustive" hints at when results are sufficient. There is no explicit statement of when to reach for this tool versus find_use_cases or assess_fit, so the agent must infer the routing.

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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