arcpro-mcp

by qiobn

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation or data type. 'list_*' tools operate on different entities (directory, feature classes, fields, layers, layouts), and 'get_*' tools retrieve different information. No overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., add_raster_layer, list_layers, select_by_attribute). Even 'ping' fits as a common verb. No mixing of conventions.
Tool Count4/5
With 25 tools, the server covers a broad range of ArcGIS Pro functionalities without being excessive. It is slightly on the high side but well-scoped for the domain.
Completeness3/5
The set covers core workflows: data loading, querying, selection, geoprocessing, and layout creation. However, it lacks tools for spatial selection, feature editing, symbology control, and other advanced operations common in GIS.
Average 3.8/5 across 25 of 25 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It reveals that the layout comes with a map frame pre-added and mentions supported units, but lacks information on whether the layout is automatically saved, if it requires an active project, or any potential 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the primary purpose. The second sentence about export_layout is concise and adds workflow context without unnecessary details. No filler or redundancy.
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 the tool has 6 parameters, 0 required, no annotations, and an output schema that is not explained, the description is incomplete. It does not describe the return value, whether the layout is persisted in the project, or how it relates to other tools like 'create_map' or 'export_layout' beyond a simple workflow hint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description does not detail individual parameters. It only lists the units enum values but fails to explain the purpose or constraints of parameters like name, map_name, width, height, and margin. The description adds minimal value beyond the schema's defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a print layout with a map frame already added', which specifies the verb and resource. It distinguishes from the sibling 'create_map' tool by focusing on print layouts, but does not explicitly differentiate from other sibling tools like 'export_layout', though it hints at a workflow.
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 suggests a workflow by saying 'Then call export_layout to write it to disk', implying that create_layout is used before export_layout. However, it provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description aligns with the idempotentHint annotation (calling repeatedly has same effect). However, it does not disclose what happens if the layer does not exist, whether changes are saved automatically, or any side effects. The description adds minimal value beyond 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence, no filler). However, it is too brief to be fully helpful; it sacrifices substance for brevity. It could be expanded with minimal additional context.
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?
With an output schema present, the return value is presumably documented there, but the description lacks crucial input context. It does not cover error scenarios (e.g., invalid layer), the role of optional parameters, or scope of effect. Incomplete for a tool with 3 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain any of the three parameters: what 'layer' expects (name/ID?), the effect of 'visible' boolean, or when 'map_name' is needed. This is a major gap as the description fails to compensate for missing schema documentation.
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 'Show or hide a layer on the map' clearly states the action (toggle visibility) and the resource (a layer). It distinguishes from sibling tools like add_raster_layer and remove_layer which add/remove layers, and zoom_to_layer which navigates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as add_layer or remove_layer. No mention of prerequisites like the layer must exist or that map_name is needed for multi-map projects.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the map is created and opened in ArcGIS Pro to view, implying it does not automatically open afterward. However, it does not mention permissions, side effects, or any destructive behavior. The description provides minimal behavioral context.
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 and relatively concise. However, the second sentence 'Open it in ArcGIS Pro to view it' could be considered redundant or better integrated. Overall, it is well-structured but not minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists (though not shown), so return values need not be explained. However, the description lacks context on potential name conflicts, required project setup, or limitations. Given the tool's simplicity, it is minimally complete but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with no descriptions in the schema. The description does not explain the 'name' parameter beyond its default value. It adds no additional meaning about constraints, uniqueness, or formatting. For a single parameter, this is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a new map in the project' which is a specific verb and resource. However, it does not distinguish from sibling tools like 'create_layout' or 'add_raster_layer' which also create new items. The verb 'create' and noun 'map' are clear but lack differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description simply says to create a map with no context on prerequisites, preferred scenarios, or exclusions. The sibling tools list suggests other creation tools exist, but no differentiation is made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action of adding a layer but does not mention side effects (e.g., whether it replaces existing layers), permissions, error handling, or that the path must be valid.
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?
Single sentence, front-loaded with key information. Efficient but could benefit from a bit more detail without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no enums) and an output schema, the description is minimally adequate but lacks info on error conditions and behavior when map does not exist.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. It implies path is a file path and map_name is optional, but provides no details on path format, allowed sources, or behavior when map_name is empty.
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 states the specific verb 'Add' and resource 'raster layer', with examples of supported formats (GeoTIFF, IMG). It clarifies the target as the active map or a named map, distinguishing from sibling tools like add_vector_layer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., add_vector_layer). No explicit when-to-use or when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already indicates this is a read-only operation. The description adds that it works on the active map but does not disclose additional behavioral traits such as performance implications or that it depends on the layer being available.
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 a single, front-loaded sentence that is concise. However, it sacrifices necessary detail about the parameter, so it is not optimally structured for usability.
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 the 0% schema description coverage, the description should compensate by explaining the 'layer' parameter, but it does not. While an output schema exists, the description lacks critical context for using the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'layer' is a string with no description in the schema (0% coverage). The description does not explain what values the 'layer' parameter accepts or how to specify it, such as layer name or ID.
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 counts the number of features in a layer of the active map. It uses a specific verb ('count') and resource ('features'), and it distinguishes itself from sibling tools like 'get_layer_features' and 'describe_data'.
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 the tool is used when you need a count of features, but it does not provide explicit guidance on when to use it versus alternatives, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide idempotentHint: true. The description adds no behavioral context beyond that, such as whether it overwrites without prompt, handles unsaved changes, or requires user interaction. No contradiction with 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?
Single sentence, perfectly concise with no redundant information. Every word earns its place.
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 zero-parameter tool with output schema, the description fully conveys the tool's action. No gaps remain given the simplicity of the operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description correctly omits parameter details. Baseline 4 applies for zero parameters; no additional value needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Save' and resource 'current ArcGIS Pro project (.aprx)', making purpose unambiguous. However, it does not explicitly distinguish this tool from siblings like get_project_info or other project-related tools, though the context of saving implies a distinct action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives (e.g., when to avoid saving, prerequisites like having a project open). The description simply states what it does without usage conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions adding to active or named map without detailing side effects, permissions, or error handling. Limited transparency.
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?
Two concise sentences, front-loaded with purpose. No redundancy, though could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple 2-param tool with output schema; description covers basic purpose and a precondition but lacks parameter details and behavioral context, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage; description adds a hint about using list_directory for the path but doesn't explain map_name or path format, leaving significant ambiguity.
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 adds vector layers to maps, lists supported formats, and distinguishes from sibling tools like add_raster_layer.
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?
Provides a clear precondition ('Confirm the path with list_directory first'), indicating when to use it, but lacks explicit exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe repeated calls. The description adds the basic action but lacks details on behavior when no selection exists, error states, or return values beyond what the output schema might imply.
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?
Single sentence, clear and direct. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with output schema and idempotent annotation, the description is minimal. It lacks usage notes, error handling behavior, and confirmation of idempotency, making it adequate but not 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?
The parameter 'layer' is described only as 'on a layer' in the description. With 0% schema description coverage, the description partially compensates by indicating the role of the parameter, but does not specify format (name, ID, etc.) or constraints.
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 action (clear) and the target (active selection on a layer). It distinguishes from sibling tools like select_by_attribute which creates selections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use the tool (e.g., before a new selection, after modification) or when not to use it. No mention of alternatives or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation already indicates destructiveHint: true, and the description adds 'This cannot be undone' for additional context on irreversibility. There is no contradiction.
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?
Two concise sentences with no wasted words, but the brevity leads to omission of important parameter information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool and existence of an output schema, the description omits behavior for edge cases like non-existent layers or the effect of the default map_name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'by name' hinting at the layer parameter, but with 0% schema coverage, it fails to clarify the map_name parameter or provide details on acceptable values or formats.
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 uses a specific verb 'Remove' and a clear resource 'layer from a map', and it distinguishes from sibling tools like add_raster_layer and set_layer_visibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description warns that the action cannot be undone but does not specify when to use this tool versus alternatives like set_layer_visibility, nor provides exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the behavioral effect: it sets the default location for inputs/outputs when full paths are not given. The idempotentHint annotation is consistent, and the description adds context about path resolution.
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 a single sentence that front-loads the action and purpose. It is concise, though could benefit from slight restructuring for clarity.
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 simple setter with one parameter and an output schema (not shown), the description is fairly complete. It explains the purpose and provides an example. Could mention persistence or impact on subsequent operations.
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?
With 0% schema description coverage, the description must compensate. It provides examples (folder or file geodatabase path) but does not specify constraints like whether the path must exist or the format. Adds some meaning beyond the schema.
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 verb 'Set' and the resource 'arcpy.env.workspace', explaining it defines the default location for inputs/outputs. This distinguishes it from sibling tools like get_workspace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites or scenarios where setting the workspace is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, indicating no side effects. The description adds that the tool returns the current workspace value but does not elaborate on behavior beyond that. It is adequate but not enhanced.
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?
A single, concise sentence that is front-loaded with the essential action. Every word serves a purpose, and there is no redundancy.
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 the tool's simplicity (no parameters, output schema exists), the description sufficiently conveys the return value. However, it could mention the complementary sibling 'set_workspace' for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with no parameters, so schema coverage is 100%. Per guidelines, 0 parameters yields a baseline of 4. No additional parameter semantics needed.
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 retrieves the current arcpy.env.workspace, specifying it as the default location for geoprocessing inputs/outputs. The verb 'get' and resource 'workspace' are specific, and the tool is distinguishable from siblings like 'set_workspace'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'set_workspace' or other information tools. No usage context or exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds behavioral detail about the return value (name, visibility, layer type), which is helpful. It does not contradict annotations.
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?
One concise sentence covering purpose and return structure. Very efficient, though slightly more structure (e.g., bullet list) could improve readability.
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 the tool's simplicity, readOnlyHint annotation, and existing output schema, the description adequately covers return contents and usage context. It could mention that it lists all layers without filtering, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description clarifies the single parameter map_name by explaining that an empty value corresponds to the active map, while a named map is used otherwise. This adds meaning beyond the schema's simple 'Map Name' string and default=''.
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 lists layers in the active or named map, specifying the returned attributes (name, visibility, type). This distinguishes it from sibling tools like add_raster_layer or remove_layer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to use this tool versus alternatives. The description only says what it does, not when it is appropriate or when to use other list tools like list_fields or list_feature_classes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the idempotentHint annotation, description adds concrete behavior details (zooms to full extent) and clarifies the need for an open map view, enhancing understanding of the tool's action.
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 short sentences, front-loads the main action, and every word adds value with no redundancy.
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 simple zoom tool with an output schema and minimal parameters, the description covers the key behavioral context and prerequisites, though it could benefit from parameter examples or further usage hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description does not explain what the 'layer' and 'map_name' parameters represent or their relationship, leaving significant ambiguity for an AI agent.
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?
Specifies verb 'zoom' and resource 'layer' with qualifiers 'active map view' and 'full extent', clearly distinguishing from sibling tools that perform different operations on map layers.
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?
States prerequisite 'Requires an open map view', providing clear context, but offers no guidance on when to use this tool instead of alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals the tool returns detailed metadata about a dataset, which goes beyond the readOnlyHint annotation by specifying the exact information obtained. No side effects or authorization needs are mentioned, but for a read-only metadata tool this is sufficient.
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 two sentences: the first concisely lists the output properties, and the second provides a crucial usage hint. Every sentence adds value with no redundancy or verbosity.
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 the tool has only one parameter and an output schema (handling return values), the description adequately covers purpose, output, and usage context. It is sufficient for an agent to use the tool correctly, though parameter semantics could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'path' has no description in the schema (0% coverage), and the tool description does not explain what 'path' refers to (e.g., file path, layer name, dataset identifier). The description fails to add meaning beyond the schema, forcing the agent to infer the required format.
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 describes a dataset and enumerates the specific metadata returned (data type, geometry type, feature count, extent, coordinate system). It is a specific verb-resource pair that distinguishes itself from sibling tools like get_project_info or list_fields.
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 advises using this tool before any distance- or area-based geoprocessing, providing clear context for when to invoke it. It does not mention when not to use it or list alternative tools, but the guidance is strong and specific.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the safety profile is clear. The description adds that it returns page size and units, which is useful but does not disclose other behavioral traits like authorization or rate limits.
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 a single sentence that is front-loaded and every word is necessary. It is appropriately sized with no wasted information.
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?
Given the tool has no parameters and an output schema exists, the description is complete. It explains what the tool lists and what additional information is provided, which is sufficient for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so baseline is 4. The description does not need to add parameter details since the schema covers it completely.
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 lists print layouts in the project, specifying that it includes page size and units. The verb 'list' and resource 'print layouts' are specific, and it distinguishes from sibling tools like create_layout and export_layout.
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 usage for viewing layouts but does not explicitly state when to use or when not to use, nor does it mention alternatives. It is adequate but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint, indicating safe retries. The description adds behavioral context: output is a full file path, format defaults to PDF, dpi applies to raster formats. It does not contradict annotations and discloses key behavior beyond the structured data.
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. Every clause adds value—no redundant text. Highly efficient.
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 the presence of an output schema, return values need not be described. The description covers essential parameter details and behavior. It does not mention error handling or file overwrite behavior, but overall is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the burden. It explains format (list of types), dpi (applies to raster, default 150), and output (full file path). The 'name' parameter is not elaborated, but three out of four parameters gain meaning.
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 starts with 'Export a layout to a file' which clearly states the action (export) and resource (layout). It distinguishes from siblings like create_layout, which creates but does not export, and other tools that operate on layers or selections.
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 does not explicitly state when to use this tool versus alternatives. It implies usage when a file output is needed, but lacks guidance on prerequisites, exclusions, or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so description focuses on additional behavior: 'limit caps the number of values returned.' No contradictions; adds value beyond annotations by clarifying the limit's effect.
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 main action and purpose. No redundant words, every sentence earns its place.
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?
With an output schema present, return values are covered. The description clearly states the tool's purpose and key parameter behavior, adequate for a simple read tool. Could mention required parameters but implicit given context.
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 0%, so description is expected to add meaning. It explains 'limit' (default 100, caps values), but does not elaborate on 'layer' or 'field' parameters. Minimal added value beyond naming.
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 returns distinct values of a field, with a specific use case ('useful before building where-clauses or categorized symbology'). It differentiates from sibling tools like describe_data or get_layer_features by focusing on unique values for a single field.
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 provides clear context on when to use ('useful before building where-clauses or categorized symbology'), but does not explicitly state when not to use or mention alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond the readOnlyHint annotation by specifying the types of workspaces supported (folder, file geodatabase, feature dataset) and the role of parameters. However, it does not mention potential performance implications for large workspaces or what the output format contains, though the output schema likely covers the latter.
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 with two sentences. The first sentence states the main purpose and scope, the second explains parameter behavior. Every sentence adds value, and the key information is front-loaded.
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 the tool has an output schema, the description covers the input parameters and workspace domain sufficiently. It is complete for an agent to understand when and how to use the tool. A minor improvement could be explicitly stating that it is a read-only operation, but the annotation already indicates that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter: pattern filters by name, geometry_type filters by geometry type (Point/Polyline/Polygon). This provides clear, actionable semantics beyond the schema's default values and titles.
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 lists feature classes in a workspace, specifying the resource (feature classes) and the action (list). It explicitly mentions the domain (folder, file geodatabase, feature dataset) and distinguishes from siblings like add_vector_layer or list_layers by focusing on a specific listing operation.
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 usage for listing feature classes but does not explicitly guide when to use this tool versus alternatives such as list_layers or list_fields. With 24 sibling tools, including other listing tools, explicit usage conditions or exclusions would improve this dimension.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide idempotentHint. Description adds return value (selected feature count) and explains selection_type behaviors. Does not detail side effects on existing selection, but the options imply them.
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 well-structured sentences that are front-loaded with the key purpose and example. Every sentence adds value without verbosity.
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?
Given the output schema exists (not shown but indicated), the description covers prerequisites, parameter options, and return value. It is thorough for a tool with moderate 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?
With 0% schema description coverage, the description adds meaning for where_clause (example) and selection_type (enum values). However, it does not clarify the 'layer' parameter format or that it expects a layer name from list_layers.
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 'Select features in a layer using a SQL where-clause' with an example, and differentiates from siblings like clear_selection, count_features, and get_layer_features by focusing on selection via SQL.
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?
Provides explicit guidance to 'use list_fields and get_unique_values first to build a valid clause' and lists the selection_type options. Does not explicitly mention when not to use, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description does not add behavioral details beyond that, nor does it contradict. It mentions glob pattern filtering, which is a usage feature, not a behavioral trait.
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 concise sentences: one describes the action, the other provides usage guidance. No wasted words, and both sentences contribute directly to agent understanding.
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?
The tool is simple, and the output schema exists to describe return values. The description covers the core purpose and a key use case. It could mention recursion behavior or whether subdirectories are included, but that is minor given the glob pattern option.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains the pattern parameter with an example ('*.shp') and implies the path is a directory. This adds meaning beyond the schema's bare type definitions.
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 'List files in a directory', specifying the verb and resource. It is distinct from sibling tools like list_feature_classes or list_layers, which operate on different entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use this tool to confirm exact filenames before loading data, and warns against guessing paths. This provides clear 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is clear. The description adds value by specifying the returned fields (name, alias, type, length), which is useful behavioral information beyond 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first describes the action and output, second provides usage guidance. No redundant or unnecessary information. Front-loaded and efficient.
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 simple read-only tool with an output schema and single parameter, the description covers the essential purpose, output details, and usage context. It could be improved by briefly noting error handling or data source format requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description compensates by clarifying that the 'dataset' parameter can also refer to a layer, and explains what the tool does with it (lists fields). This adds meaningful context beyond the bare parameter name.
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 lists fields (name, alias, type, length) of a dataset or layer, which is a specific verb+resource. It distinguishes from siblings like 'describe_data' by specifying the exact attributes returned.
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 says 'Use before building SQL where-clauses or attribute operations,' providing clear context. However, it does not mention when not to use it or suggest alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description adds specific behavioral details about what data is read (version, path, maps, etc.). No side effects or contradictions are present.
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, no wasted words, and the key instruction to call first is front-loaded.
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 the tool's simplicity and the existence of an output schema, the description is complete enough. It covers the purpose and key returned data without needing to detail output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description adds meaning by explaining what the tool returns. With zero parameters, baseline is 4, and the description effectively clarifies the output.
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 checks connectivity to the ArcGIS Pro bridge and reads project status, listing specific data (version, path, maps, etc.). It distinguishes from sibling tools that perform other operations like adding layers or creating maps.
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 says 'Always call this first,' providing clear guidance on when to use the tool. It does not specify when not to use or alternatives, but the directive is strong enough to indicate its role as a prerequisite.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation indicates safety, and the description adds behavioral details about row and column limits. No contradictions or omissions.
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?
Extremely concise and well-structured: two sentences, front-loaded with purpose, every word adds value.
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?
Given the presence of an output schema and the simplicity of the tool, the description is sufficiently complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds essential meaning for limit and fields parameters, though it could provide more detail on valid values.
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's purpose as 'Preview rows from a layer's attribute table,' using a specific verb and resource that distinguishes it from sibling tools.
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 provides clear usage context by explaining the limit and fields parameters, but does not explicitly state when to use alternative tools like get_unique_values or list_fields.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true. The description further specifies what data is returned, adding context beyond the annotation. No contradictions are present.
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?
A single, front-loaded sentence with no verbose or redundant information. Every word contributes to the tool's understanding.
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?
Given the tool's simplicity (no parameters, output schema exists), the description fully captures the tool's purpose and output. It complements the output schema by listing key return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100% (empty). The description adds value by explaining what the tool outputs, which is essential since the schema provides no parameter information.
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 uses the verb 'Get' with specific resource 'current project' and lists exact data returned (.aprx path, default geodatabase, maps with spatial reference), clearly distinguishing from sibling tools like add_raster_layer or create_map.
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 context is clear: this tool retrieves project-level information. While no explicit when-not-to-use or alternatives are mentioned, its simplicity and specific purpose make usage obvious among the listed siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: outputs are overwritten, and the tool returns arcpy messages. This covers the most important behavioral traits for a generic geoprocessing runner, though it could mention error handling or permissions.
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 three sentences, each earning its place: purpose, examples, warning, overwrite behavior, return value. It is front-loaded and concise with no wasted words.
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?
Given the complexity of running arbitrary geoprocessing tools, the description covers how to specify the tool and params, includes a critical warning, and states output behavior and return value. With an output schema existing, this is fully adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds substantial meaning: 'tool' is a dotted name like 'analysis.Buffer', 'params' is an array of positional parameters. Examples clarify the format. This compensates well for the lack of schema descriptions.
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 runs any ArcPy geoprocessing tool by dotted name with positional parameters, with concrete examples. It distinguishes from sibling tools which are domain-specific, making the purpose unambiguous.
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 provides a strong usage guideline: always check coordinate systems with describe_data before distance/area operations. It also notes outputs are overwritten. However, it does not explicitly state when not to use this tool or provide alternatives, but the context is clear.
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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