ShowMeOnMap

Mutate a map

mutate_map

Apply a natural-language instruction to an existing workspace. Valid mutations: filter a layer, remove a layer, change camera, change basemap. For ambiguous instructions the tool emits a clarification field. For unrelated instructions it emits outOfScope — build a new map in that case. For the full Op catalog and predicate grammar, fetch the MCP resource showmeonmap://docs/workspace-ops-spec.

Input Schema

TableJSON Schema

Name	Required	Description
`map_id`	Yes	map_id from a prior build_map call
`rationale`	Yes	Short audit-log label (≤300 chars) stating the user-facing goal this call serves, e.g. "add wildfire layer for the user's California query". Required on every call. Stored in the operations log so map edits stay traceable — we never see your chat history.
`instruction`	Yes	e.g., "filter to where magnitude is greater than 5", "change basemap to dark"

TDQS

A4/5.0

Behavior3/5

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

Description adds context about ambiguous and out-of-scope instructions, and explains the rationale parameter is for audit-logging. No annotations contradiction, but more details on response format or side effects would improve transparency.

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?

Description is concise with three sentences, each adding new information: purpose, edge cases, and documentation reference. Front-loaded with main function.

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?

Description covers purpose, valid operations, edge cases, and points to external docs. With no output schema, the description is mostly sufficient, though response structure details would increase completeness.

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?

Parameter descriptions in the schema already cover all three parameters adequately. The description adds examples for the instruction parameter and context for valid mutations, but does not significantly extend schema knowledge.

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?

Description clearly states the tool applies a natural-language instruction to an existing workspace and lists four valid mutation types. This distinguishes it from sibling tools like filter_layer or remove_layer.

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?

Description explains when to use alternatives: for unrelated instructions it emits outOfScope, suggesting to build a new map. However, it does not explicitly say when to prefer this tool over specific sibling tools for the same mutations.

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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TDQS

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but a few pairs such as select_within/focus_area and correlate_layers/add_fusion_layer overlap in function, differing mainly by input type or output (read vs. write). The descriptions adequately explain these differences, so agents can distinguish them with careful reading.

Naming Consistency5/5

Tool names consistently follow a verb_noun snake_case pattern (add_layer, filter_layer, export_image, remove_annotation). Minor exceptions like undo/redo/tag are conventional single verbs and do not detract from the overall predictability.

Tool Count4/5

At 25 tools, the server is on the heavy side, but each tool serves a distinct operation in a comprehensive mapping workspace—covering creation, editing, analysis, export, and history. The number feels justified by the broad feature set rather than excessive.

Completeness4/5

The toolset covers the full lifecycle of layers and workspace state, including add/remove/rename/restyle/filter, build/get/mutate/undo/redo, export, and tagging. Minor gaps such as annotation editing, layer reordering, or direct data updates exist, but they are not critical blockers for typical workflows.

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