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DaedalMap Geography Tools (loc_id)

by com.daedalmap

Estimate loc_id Conversion Job

estimate_conversion_job
Read-only

Free dry-run quote for uploaded or pasted user data conversion. Estimates rows, sample resolvability, output bytes, errors, and charge units before execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iso3No
itemsNoSample or full rows; row-level fields may override top-level defaults.
limitNo
min_shareNo
row_countNoExpected total row count when only a sample or artifact pointer is provided.
to_systemNoOptional output reference system. Omit to normalize to loc_id.
request_idNoOptional caller-supplied request id for tracing.
from_systemNoInput reference system for rows.
output_nameNoOptional safe base filename.
output_formatNoEnriched-row output format. CSV is spreadsheet-friendly; Parquet is compact and typed; JSON Lines is stream-friendly.
geography_bindingNoKnown dataset-geography declaration. The estimate verifies it against distinct identifiers and avoids point containment.
target_admin_levelNo
relationship_vintageNo

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description reinforces this by stating 'dry-run' and 'before execution', indicating no side effects. It adds that the quote is 'free' and estimates charge units, which is useful context. However, it does not discuss authentication, rate limits, or what happens on error, but given the read-only nature, the description is adequate and consistent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with 'Free dry-run quote', and conveys the core value without extraneous words. It is concise and well-structured, though it could have added one clarifying sentence about input modes without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 13 parameters, nested anyOf schemas, and no output schema, the description is insufficient. It does not explain how to provide input (items vs row_count), the role of geography_binding, or how output_format affects the estimate. An agent would need to dig into the schema to understand request formation, which is a significant gap for this complexity.

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 62%, and some parameters already have descriptions (e.g., data reserved columns, to_system, output_format). The description mentions 'uploaded or pasted user data' which hints at the items or row_count modes but does not explain the anyOf structure or how to choose between them. It also does not clarify geography_binding semantics beyond what is in the schema. It provides partial value but does not fully compensate for unpresented 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?

The description clearly states it is a 'free dry-run quote' for 'user data conversion' and lists specific estimates (rows, sample resolvability, output bytes, errors, charge units). This distinguishes it from sibling tools like create_conversion_job, which actually performs conversions, and estimate_geometry_package, which focuses on geometry packages.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies it is for pre-execution estimation ('before execution') and is a dry-run, but it does not explicitly state when to use this instead of alternatives like create_conversion_job or how it differs from other estimate tools. No exclusions or alternative routing is mentioned; the intent is inferred from 'dry-run quote'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All DaedalMap Geography Tools (loc_id) toolsInspect
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TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: point resolution, reference conversion, hierarchy traversal, geometry retrieval, export creation, job estimation, catalog discovery, and relationship comparison are all separated. The descriptions explicitly state what each tool does and what it does not do, preventing misselection. Even closely related tools like get_geometry, get_geometry_export, and estimate_geometry_package are differentiated by their roles (single-shape retrieval vs. export artifact vs. dry-run estimate).

Naming Consistency5/5

All 20 tool names follow a consistent verb_noun snake_case pattern (e.g., get_geometry, create_conversion_job, resolve_point, list_reference_systems). The verbs are action-oriented (get, create, estimate, resolve, compare, list, read) and each noun clearly indicates the subject. While a few like 'loc_id_info' and 'how_geometry_works' deviate slightly from the strict verb_noun structure, they still fit the overall style and are easy to predict.

Tool Count4/5

The 20 tools are slightly above the typical 3-15 range but still well-scoped for a comprehensive geocoding and geography service. The extra tools reflect the breadth of operations offered (discovery, conversion, estimation, export, resolution, relationship analysis), each earning its place. The count feels reasonable given the domain, though it approaches the upper boundary of what an agent might easily navigate.

Completeness5/5

The tool surface covers the full lifecycle of geocoding workflows: discovery (get_catalog, get_pack, read_geometry_catalog), point resolution (resolve_point), reference resolution (resolve_reference), identifier identification (identify_reference_system), hierarchy traversal (resolve_loc_id_scope, loc_id_info), geometry retrieval (get_geometry), relationship analysis (compare_geographies), conversion (convert_reference, create_conversion_job), export (create_geometry_export), and estimation (estimate_geometry_package, estimate_conversion_job). The inclusion of help tools (get_tool_help, how_geometry_works) and job status retrieval ensures no dead ends. The absence of destructive or update operations is consistent with a read-only geospatial data service, so the surface is appropriate.

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