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Prompt List

prompt_list
Read-onlyIdempotent

List and search an organization's saved AI prompts for customer support replies. Filter by name or text to find prompts for AI classifications and responses.

Instructions

List or search the saved AI prompts of an organization. Classifications reference a prompt for their AI replies, and ai_prompt can apply one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, starting at 1.
limitNoMaximum items to return (default 10, max 50).
searchNoMatches the prompt name and text.
organizationIdYesThe organization id. Use organization_list to find it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and a closed world, so the safety profile is fully covered. The description adds domain context (classifications reference prompts; ai_prompt applies one) but says nothing about ordering, default pagination behavior, or result shape beyond what the schema states.

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?

Two tight sentences with the core action front-loaded in the first. The second sentence is useful domain context rather than filler, though it reads slightly tangential to the act of listing, keeping it just under a 5.

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?

For a read-only list tool with a fully described 4-parameter schema and complete annotations, the description covers the essentials; no output schema is needed since none exists. The only shortfall is the absence of ordering/result-shape context, which is minor.

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 description coverage is 100%, with page, limit, search, and organizationId all documented in the schema including the pointer to organization_list. The description adds no parameter-level meaning beyond the schema, so the baseline of 3 is appropriate.

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 gives a specific verb set ("List or search") and resource ("the saved AI prompts of an organization"), which cleanly separates it from prompt_get, prompt_create, prompt_update, and prompt_delete by verb. It does not, however, explicitly name a sibling or state how it differs from generic search, so it stops short of a 5.

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?

"List or search" implies the usage (browse prompts, optionally filter by name/text), and the note that classifications reference a prompt hints at why an agent would look prompts up. But there is no explicit when-to-use guidance, no exclusion against prompt_get for retrieval by id, and no mention of the `search` parameter as the routing mechanism.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.