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ShowMeOnMap

by com.showmeonmap

Query features from a layer (read-only)

query_features
Read-onlyIdempotent

Evaluate a predicate against a layer's inline features and return the matching subset. No Op is emitted and the workspace is not mutated. Handy for introspection ("how many X match Y?") before deciding whether to filter, subset, or build a new layer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoDefault 100, max 1000. Response sets `truncated:true` when clipped.
map_idYes
layerIdYes
predicateYesPredicate in the Mongo-shape grammar. Examples: {op:"eq",field:"category",value:"cafe"}, {op:"gt",field:"magnitude",value:5}, {op:"within",geometry:{type:"Polygon",coordinates:[...]}}, {op:"and",children:[...]}. See docs/superpowers/specs/2026-04-17-workspace-ops-log-design.md §6.
rationaleYesShort 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.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. Description adds value by stating 'No Op is emitted and the workspace is not mutated', and notes the rationale parameter's audit-log purpose, reinforcing non-destructive behavior without contradicting annotations.

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?

Two sentences, front-loaded with the core action and complemented by a concise usage hint. Every sentence serves a purpose without waste.

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?

Given no output schema, the description explains the basic operation and use case well. It mentions the rationale for audit logs and implies return structure. Minor gaps: no error handling details or explicit output format, but sufficient given annotations.

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 60%, and the description does not add meaning beyond the schema's parameter descriptions (e.g., limit default/max, predicate examples, rationale purpose). While schema provides adequate detail, the description does not enhance understanding of parameters.

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 uses specific verb ('evaluate a predicate') and resource ('layer's inline features'), clearly stating the return of a matching subset. It distinguishes from sibling tools like filter_layer by noting it is for introspection before deciding to filter or subset.

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?

Explicitly states no mutation and no Op emission, indicating read-only use. Provides context for introspection before filtering or building new layers, but could be more explicit about when not to use compared to siblings.

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.

Resources