ShowMeOnMap

Set the time window (direct)

set_time

Idempotent

Override the current time-range filter. Latest set_time op wins during replay. Use for "filter to 2020-2024" or "show only the last 7 days" intents. Not yet consumed by the renderer — the UI drives the slider directly — but the value is captured in the ops log and queryable via get_state.

Input Schema

TableJSON Schema

Name	Required	Description
`field`	Yes	Feature property carrying the time value (e.g. "date", "year", "timestamp").
`format`	No	How rangeStart/rangeEnd encode time. Default: unix_ms at render time.
`map_id`	Yes
`rangeEnd`	Yes	Inclusive upper bound of the visible window.
`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.
`rangeStart`	Yes	Inclusive lower bound of the visible window.

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the annotations (idempotentHint=true, destructiveHint=false), the description explains replay behavior ('Latest set_time op wins'), current consumption status, and that the value is queryable via get_state, adding significant 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?

The description is extremely concise: three sentences that front-load the core action, then add key behavioral notes with zero wasted words.

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 tool with 6 parameters and no output schema, the description covers purpose, usage, replay behavior, and current limitations. It could mention edge cases or error handling, but is largely complete.

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 high (83%), so the schema already documents most parameters well. The tool description does not add new parameter-level details beyond implying the use of rangeStart and rangeEnd for time bounds.

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?

The description clearly states the tool overrides the time-range filter, provides concrete example intents ('filter to 2020-2024', 'show only the last 7 days'), and implicitly distinguishes it from sibling filter tools by focusing on time windows.

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?

The description explicitly lists appropriate use cases with examples, but does not mention when not to use it or compare to sibling tools like filter_layer. The caveat about not being consumed by the renderer provides helpful context.

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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