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by ai.mapmap

report_map_issue

Report that the live world disagrees with the map — a closed road, a wrong or missing restriction, a bad speed limit, a missing road, a wrong one-way, or changed access. Use it when you observe the mismatch mid-task. Provide location {lat, lon}, a category (road_closed, wrong_restriction, wrong_speed_limit, missing_road, wrong_oneway, access_changed, other) and optionally a description, the OSM way_id and an evidence_url. This is a first-party observation: it is QUEUED for human/agent review and NEVER changes routing immediately or edits any map. Returns the queued report_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
way_idNoThe OSM way id the observation concerns, when the caller knows it. Optional — the report stands on its own as a first-party observation and is never tied to OSM data beyond this hint.
categoryYesWhat kind of mismatch this is.
locationYesWhere the mismatch was observed (WGS84 decimal degrees).
descriptionNoFree-text detail of what was observed on the ground, e.g. "barrier across the lane, diversion signed via the B4009". Bounded length.
evidence_urlNoA URL backing the observation (photo, notice, news item), when one exists. Bounded length.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesAlways "queued": the report awaits human/agent review and changes nothing about routing immediately.
categoryYesThe category, echoed back as its snake_case wire tag.
report_idYesThe generated id of the queued report (cite it in follow-ups).

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden. It clearly states the report is QUEUED for human/agent review, NEVER changes routing immediately, and NEVER edits any map, plus it names the return value (report_id). This prevents the agent from assuming immediate side effects.

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 compact and front-loaded with purpose, then moves to usage trigger, parameter requirements, and side-effect caveat. Every sentence contributes needed information; there is no filler or repetition of title.

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?

For a 5-parameter tool with no annotations, the description covers purpose, when to use it, parameter requirements, behavioral consequences, and return value. The output schema exists and the description explicitly names the queued report_id, so nothing needed to invoke the tool correctly is missing.

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 coverage is 100% with per-parameter descriptions and category enum semantics, so the baseline is 3. The description usefully compresses required vs optional parameters and lists category values, but adds little meaning beyond what the schema already provides.

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 opens with a specific verb and resource: 'Report that the live world disagrees with the map' and enumerates seven concrete mismatch types. None of the 33 sibling tools covers map-issue reporting, so this is unambiguously distinct.

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?

It gives an explicit trigger: 'Use it when you observe the mismatch mid-task.' It doesn't name exclusions or alternatives, but there are no obvious sibling alternatives, and the queued-observation framing helps the agent understand the tool's role.

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

A4/5.0
Disambiguation4/5

Most tools target a distinct action and resource pair, and descriptions are explicit about which tool fits which scenario. The closest overlaps—plan_ev_route vs cheapest_charging_along_route, and route vs plan_day vs order_stops vs optimise_routes—are mitigated by clear guidance, so an agent can usually pick correctly.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (plan_ev_route, set_palette, list_style_layers) with a consistent geo_ prefix for geometry helpers. Minor deviations like elevation, route, and matrix are short and readable but break the strict verb_noun convention.

Tool Count2/5

At 39 tools, this surface is well past the 25+ threshold and feels heavy even for a broad mapping platform. The set spans routing, geocoding, places, styles, EV/fuel, telematics, usage, and feedback, which would be easier for an agent to navigate if split into smaller domain-focused servers.

Completeness4/5

For the stated breadth, coverage is strong: routing, multi-stop planning, VRP, EV/fuel detours, geocoding, places, geometry, style lifecycle, and telematics all have workable primary paths. Minor gaps like no style deletion, no route alternatives, and no batch geocoding are present but do not create dead ends for core workflows.

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