DaedalMap Reverse Geocoding (coordinates to loc_id)

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

The description adds context beyond the readOnlyHint annotation by specifying the catalog contains live, agent-ready data packs and that it is a free discovery operation. It does not contradict the annotation and provides some added behavioral context, though it omits details like rate limits or pagination.

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

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

The description is concise, with two sentences that are front-loaded ('Free discovery' immediately conveys the tool's nature) and no wasted words. Every word adds value.

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

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

Given the tool has no parameters, no output schema, and only a readOnlyHint annotation, the description is nearly complete for its simplicity. It explains what is returned and the platform, though it could potentially clarify the format of the data packs or intended use cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema description coverage is 100%. The description does not need to explain parameter semantics, and the baseline for 0-parameter tools is 4, which is appropriate here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a list of live agent-ready data packs on DaedalMap, with the specific verb 'Returns' and resource. This distinguishes it from sibling tools like get_pack (which presumably fetches a specific pack) and resolve_point (which likely resolves a point).

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

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

The phrase 'Free discovery' implies the tool is for discovering available data packs, but it does not explicitly state when to use this tool over alternatives or provide exclusions. It offers implied usage context but lacks explicit guidance or mention of sibling tools.

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

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

Annotations already provide readOnlyHint=true, but the description adds valuable behavioral context: 'Free discovery', the exact contents returned, and the purpose of seeing 'time shape, coverage limits'. This goes beyond the annotation and helps the agent understand what to expect from the call.

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

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

The description is two sentences, front-loaded with 'Free discovery', and every clause adds useful information. No fluff or repetition.

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

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

With one parameter, a rich schema, and no output schema, the description adequately explains what is returned and when to use it. It could be slightly more explicit about the return format, but the listed contents are sufficient for a minimal tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a detailed description of pack_id and example values. The description adds only that it's 'for one pack', which is already implied by the schema. Since the schema carries the parameter meaning well, the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns detailed metadata, coverage, freshness, canonical tool guidance, and first-query examples for one pack. The verb 'Returns' plus the specific resource and scope ('for one pack') makes it distinct from siblings like get_catalog or resolve_point.

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

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

Explicitly says 'Call this before querying a new pack', providing clear when-to-use guidance. It also explains the benefit (see time shape, coverage limits, paste-ready first query). However, it doesn't explicitly mention when not to use or name alternatives, so it's not a 5.

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

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

The annotation readOnlyHint=true already signals safety, and the description reinforces it by saying the tool 'Returns' guidance rather than mutating anything. It adds useful behavioral context about output contents—refusals, effective limits, provenance fields, recommended next calls—without contradicting the annotation.

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

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

Two dense, front-loaded sentences with zero fluff. The first sentence immediately states what the tool does and enumerates its rich output; the second provides the usage pattern. Every clause earns its place.

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

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

Even with no output schema, the description enumerates all major return categories (usage guidance, refusals, example, access limits, outputs, provenance, next calls, interaction contract), making the tool's behavior transparent. It also covers prerequisites and workflow, so an agent has enough context to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage for the single tool_name parameter with 'Exact tool name from tools/list.' The description adds the practical discovery workflow (use tools/list) but does not otherwise enhance parameter semantics beyond what the schema states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Free blind-caller guidance for one tool visible on this MCP facade.' It lists concrete outputs (when to use, refusals, example, limits, outputs, provenance, next calls), clearly distinguishing this help tool from sibling tools like get_catalog or resolve_point.

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

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

Explicitly directs the agent: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This gives a crisp when-to-use workflow and an implied when-not-to-use (familiar tools). It also names the prerequisite discovery tool (tools/list) as an alternative first step.

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

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

Beyond the readOnlyHint annotation, the description discloses useful behavioral traits: output brevity ('Each chain row is intentionally small'), non-returned data, the 'deepest served tier' behavior for small exploratory calls, and the payment/throughput distinction between anonymous and verified callers. There is no contradiction with the readOnlyHint; the operation is purely a read/query action. The description enriches the annotation with practical expectations around response size and quota behavior.

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

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

The description is a single dense paragraph that is front-loaded with the primary purpose, then packs exclusions, alternatives, batch rules, and billing details. Every sentence carries information, with no filler. It could be improved with bullet points for readability, but the density is justified for a tool with this many constraints. Very high signal-to-noise ratio, so 4 is appropriate rather than 5 due to the lack of visual structure.

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

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

Given the tool has 9 parameters, no output schema, and no nested objects, the description does an excellent job covering what the tool returns (small rows with loc_id, name, admin level, vintage), what it excludes, and the operational constraints (billing, batch limits). It even explains the cross-country alternative bulk_preset. The description fully equips an agent to decide whether this tool is appropriate and how to call it correctly, so a 5 is warranted.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so a baseline of 3 is appropriate. The description adds extra semantic value by explaining the relationship between parameters, such as 'Batches above the 25-point preview must declare exactly one country_scope and one target_admin_level' and explicitly contrasting bulk_preset with country_scope for cross-country use. It also clarifies the alias country_hint indirectly through schema but reinforces the alternative. This goes beyond the bare schema descriptions, warranting a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Compact reverse geocoding' and clearly states it 'Converts one WGS84 point, or a bounded point list, into the latest-available administrative loc_id chain.' This identifies a specific verb and resource, and the explicit exclusions (no polygons, hierarchy analysis, references) distinguish it from any generic lookup tool. The sibling tools (catalog, pack, help) are clearly not competitors for this geocoding function.

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

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

The description provides strong usage guidance: it explicitly states what the tool does NOT return and directs users to alternatives ('Pass the returned stack loc_ids to loc_id_info for details; use get_geometry for shapes and compare_geographies for relationships'). It also specifies exact batch constraints, including the 25-point exploratory limit, the requirement for country_scope and target_admin_level above that, the directive to split multi-country input, and the alternative bulk_preset for cross-country batches. This is textbook when-to-use and when-not-to-use guidance.

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