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MappaIQ

by com.mappaiq
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List layers

get_layers
Read-only

Get all available layers with their names and comp counts. When the account has multiple maps, each layer also includes the map it belongs to — use that to disambiguate same-named layers and to target actions at the correct map. Per-layer pin-ID arrays are omitted by default (they make the response enormous on big accounts); pass includeCompIds:true only if you specifically need the raw ID lists — search_comps is the right tool for finding pins.

Input Schema

NameRequiredDescriptionDefault
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
includeCompIdsNoInclude each layer's full pin-ID array (large). Default false.
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely useful behavioral context beyond that: pin-ID arrays are omitted by default and why (response size on big accounts), and the `map` field only appears on multi-map accounts. It stops short of noting pagination, but that is a minor gap given the read-only annotation.

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?

Three sentences, purpose front-loaded, then the map-disambiguation detail, then the includeCompIds caveat with its alternative. No filler; each sentence carries actionable content.

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?

With no output schema, the description steps in to describe the return shape (names, comp counts, conditional `map`) and a deliberately omitted field. For a read-only list tool this covers everything an agent needs to call it correctly and interpret the result.

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 the baseline is 3, and the description adds real meaning: it explains the consequence of includeCompIds (enormous responses) and routes to search_comps, going beyond the schema's terse 'Include each layer's full pin-ID array (large)'. The context/llm_model/conversation_id analytics params are left to the schema, which documents them fully.

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?

States a specific verb+resource (get all available layers) and enumerates what comes back (names and comp counts), plus the conditional `map` field. An agent can immediately tell this is a layer-listing tool and distinguish it from pin-finding siblings.

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?

Explicitly tells the agent when to pass includeCompIds:true (only if raw ID lists are truly needed) and names the correct alternative for the adjacent task — 'search_comps is the right tool for finding pins'. Both the trigger and the alternative are stated, not inferred.

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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