GIS MCP Server

by mahdin75

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation2/5
Many tools overlap in purpose, such as multiple spatial weights creation tools (distance_band_weights, knn_weights, weights_from_shapefile, build_and_transform_weights) and numerous geometry attribute getters (get_area, get_length, get_bounds, etc.). This makes it difficult for an agent to select the correct tool without confusion.
Naming Consistency2/5
Tool names follow no consistent pattern. Some use underscore (buffer, convex_hull), some are verb_noun (calculate_geodetic_area), others are acronyms (adbscan) or long phrases (ols_with_spatial_diagnostics_safe). The mix of styles reduces predictability.
Tool Count2/5
With 87 tools, the server is overloaded for a coherent tool surface. This breadth leads to redundancy and makes it hard for agents to navigate. A more focused scope (e.g., vector only or raster only) would be more appropriate.
Completeness3/5
The server covers many GIS domains: vector operations, spatial weights, raster processing, and spatial statistics. However, there are gaps such as missing tools for creating GeoDataFrames from scratch, multi-ring buffering, or network analysis. The coverage is extensive but not fully complete.
Average 2.9/5 across 80 of 87 tools scored. Lowest: 1.5/5.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 2 community issues answered or closed in the last 6 months
- 14 commits in the last 12 weeks
- Last stable release on July 31, 2026
- 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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose any behavioral traits such as computational cost, data requirements, or side effects. The agent has no insight into what the tool does beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but not informative. Conciseness is positive, but here it sacrifices clarity and utility. Every sentence should earn its place, and this one does not.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description could be shorter, but it still must provide enough context for the agent to choose this tool over siblings. The complete lack of detail makes it insufficient.
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 input schema has 4 parameters with no descriptions in the schema (0% coverage). The tool description does not explain any parameter meanings, leaving the agent to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Local Join Counts.' is vague. It does not specify what the tool does with join counts or how it differs from its sibling 'join_counts', which presumably performs a global join count. The verb is implied but not explicit.
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 like 'join_counts' or other spatial analysis tools. The description lacks context on prerequisites or typical use cases.
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?
With no annotations, the description carries the full burden. It gives no indication of side effects, read-only nature, or authorization needs. 'Counts' implies a read operation, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a phrase, not a full sentence. While brief, it is under-specified and lacks structure, making it unhelpful for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, an output schema, and complex spatial analysis context, the description is severely incomplete. No explanation of the output or how parameters influence results is provided.
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%, and the description provides no information about parameters such as 'shapefile_path', 'dependent_var', 'target_crs', or 'distance_threshold'. The agent gets no help understanding their roles or defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Global Binary Join Counts' is vague and lacks a verb. It does not clearly state what the tool does, such as whether it computes or returns join counts. The term 'join counts' is ambiguous without context.
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 usage guidance is provided. The description does not indicate when to use this tool versus alternatives like 'join_counts_local' or other spatial statistics tools on the server.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 method name, with no mention of side effects, data requirements, output characteristics, or any operational constraints. This is completely insufficient for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (three words) but fails to convey necessary information. While it is front-loaded, conciseness is achieved at the expense of utility, making it under-specified rather than efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not explain what the tool computes or returns. For a spatial autocorrelation tool with 4 parameters and siblings, the description is far from complete and leaves critical gaps.
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 coverage is 0%, and the description adds no explanation of parameters (e.g., 'shapefile_path', 'dependent_var', 'distance_threshold'). Defaults are present but their meaning is not described, so the agent cannot infer correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Local Moran's I.' identifies the statistical method but lacks a verb or explicit action (e.g., 'computes', 'identifies clusters'). It distinguishes from 'morans_i' (global version) by including 'local', but the purpose remains vague without specifying what the tool actually does.
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 siblings like 'getis_ord_g_local' or 'gearys_c'. The description does not mention context, prerequisites, or alternatives, leaving the agent without decision support.
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 exist, and the description does not disclose behavioral traits such as read/write nature, side effects, or prerequisites. The existence of an output schema is not leveraged in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but lacks substance; it is under-specified rather than concise. Every word should earn its place, and here the single sentence does not provide adequate guidance.
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 complexity of geodetic calculations, the presence of many sibling tools, and no annotation support, the description is woefully incomplete. It leaves the agent without critical context.
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%, yet the description fails to explain that parameters like ellps, a, b, f define an ellipsoid. It adds no meaning beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get information about a geodetic calculation,' but does not specify what kind of information (e.g., ellipsoid parameters, transformation results) or differentiate it from siblings like get_crs_info or calculate_geodetic_distance. The purpose is unclear.
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 alternative tools. With many geodetic siblings, the lack of usage context makes selection difficult.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden but only states 'combine two geometries.' No disclosure of output type, error handling, or side effects. Output schema exists but description adds no 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (3 words) but lacks structure and essential details. Conciseness is not matched by informativeness; it sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero annotations and no parameter descriptions, the description is insufficient. Even with an output schema, the description fails to explain behavior, prerequisites, or output semantics.
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 coverage is 0% and description does not describe parameters. No explanation of expected format (WKT, GeoJSON) or constraints for geometry1 and geometry2.
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 'Combine two geometries' states action and resource clearly, aligning with tool name 'union.' It distinguishes from unary operations like unary_union_geometries but does not differentiate from other binary set operations like intersection or symmetric_difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 intersection, difference, or symmetric_difference. No context on 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?
With no annotations provided, the description carries the full burden of explaining behavior. It does not mention what action occurs (e.g., parsing geometry, returning coordinates), the format of the output, error handling for invalid geometry, or any 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (6 words) but overly brief, sacrificing clarity and completeness. It front-loads the action but omits critical details, making it insufficiently informative.
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?
Although an output schema exists, the description does not set expectations for the return value (e.g., coordinates as array, object, or tuple). For a simple one-parameter tool, the description should at least state the output format.
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 parameter 'geometry' has 0% schema description coverage, and the description does not explain what format the string should be (e.g., WKT, GeoJSON). Without this context, the agent cannot correctly provide the input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description restates the tool name with minimal elaboration: 'Get the coordinates of a geometry.' It does not specify what type of coordinates (e.g., 2D, 3D, geodetic) and fails to distinguish this tool from siblings like 'get_centroid' or 'get_bounds' that also return coordinate data.
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 the many sibling tools that handle geometry coordinates. The context includes numerous alternatives (e.g., get_centroid, get_bounds), but the description offers no differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, and the description gives no information about behavioral traits such as computational demands, data requirements, or side effects. The agent has no insight into what happens during execution.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At three words, the description is extremely concise but at the expense of substance. It does not use its limited space to convey actionable information; instead, it sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a local spatial statistic with multiple parameters and an output schema, the description provides virtually no context. It does not mention what the output represents, how distance_threshold influences results, or any interpretation guidelines.
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 input schema has 0% description coverage, and the description does not explain any parameters. While parameter names like 'shapefile_path' and 'distance_threshold' are somewhat self-explanatory, the description adds no additional meaning, leaving the agent to guess default behaviors or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Local Getis-Ord G' identifies the tool as computing the local Getis-Ord G statistic, which differentiates it from the sibling global version 'getis_ord_g'. However, it lacks explanation of what the statistic is used for (e.g., hot/cold spot detection), leaving some ambiguity for an AI agent unfamiliar with the term.
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 usage guidelines are provided. The description does not indicate when to use this tool over alternatives like 'moran_local' or 'getis_ord_g', nor does it clarify prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully convey behavioral traits. It only says 'Get information', without mentioning read-only status, return format, or any side effects. This is insufficient for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, but it is under-specified. It lacks necessary details, making it more of a placeholder than an informative description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema details (though an output schema exists), the description does not explain what the tool returns or how to interpret the results, leaving the agent with insufficient context.
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 input schema has one parameter 'crs' with no description and 0% schema description coverage. The description does not clarify what format or values are expected (e.g., EPSG code, name), adding no value beyond the schema.
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 the verb 'Get' and the resource 'information about a CRS', but it does not differentiate from sibling tools like 'get_available_crs' or 'get_geocentric_crs', leaving ambiguity about what specific information is returned.
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 such as 'get_available_crs' or 'get_utm_crs'. The agent has no context for selecting the appropriate tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only restates the name, failing to disclose any behavioral traits such as the simplification algorithm, impact on topology, or validation requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but under-specified. The single sentence does not provide sufficient utility; it merely echoes the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity (3 parameters, output schema exists but undescribed), the description is wholly inadequate. It omits essential context about the operation and return values.
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% and the description does not mention any parameters. The three parameters (geometry, tolerance, preserve_topology) are left unexplained, despite being critical for correct usage.
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 'Simplify a geometry' clearly states the verb and resource, but it does not differentiate from sibling tools like 'normalize_geometry' or 'make_valid' which also modify geometry. Slight ambiguity remains.
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. Implied usage is for reducing complexity, but no explicit context or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose behavioral traits such as units of distance, supported geometry types, or behavior with negative distance. It only states the basic operation without any additional context.
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 extremely concise (one sentence), but it is under-specified for a tool with multiple parameters. It does not waste words but also does not earn its place by providing sufficient information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (6 parameters, no schema descriptions, no annotations) and the presence of an output schema, the description is incomplete. It fails to cover parameter usage, edge cases, or caveats that an agent needs to know.
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 input schema has 6 parameters with 0% description coverage, but the tool description does not explain any parameter (e.g., what 'distance' means, how 'resolution' affects results). This leaves agents to infer meaning from parameter names alone.
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 the action 'Create a buffer' on a 'geometry', indicating a specific verb and resource. While it doesn't detail the buffer operation (e.g., expansion/shrinkage), it is distinct enough from sibling tools like 'convex_hull' or 'envelope'.
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 such as 'simplify' or 'convex_hull'. The description does not mention any prerequisites, context, 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?
With no annotations and a minimal description, the behavioral transparency is poor. The description does not disclose side effects, computational requirements, or constraints like data size or coordinate system handling.
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 concise at one sentence, but it sacrifices critical information. While every word is earned, the brevity leads to omission of necessary 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?
Given the tool's complexity and many siblings, the description is incomplete. An output schema exists but doesn't compensate for the lack of explanation about what the Gamma Statistic measures and how it differs from other autocorrelation tests.
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%, but the description adds no information about parameters. Keys like 'distance_threshold' and 'dependent_var' remain unexplained, forcing the agent to rely on names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Compute' and resource 'Gamma Statistic' with context 'spatial autocorrelation', providing a basic purpose. However, it does not differentiate from sibling tools like morans_i or gearys_c, leaving ambiguity about when to use this specific statistic.
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 usage guidelines are provided. The description lacks any indication of when to use this tool versus alternatives, what prerequisites are needed (e.g., data type, variable assumptions), or typical use cases.
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 present, so the description must convey behavioral traits. It only says 'Scale a geometry' without explaining what scaling entails (e.g., origin, coordinate modifications), whether it mutates input or returns a new geometry, or any 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is a single sentence, it is under-specified for a tool with four parameters and many siblings. Conciseness is sacrificed for completeness; the description fails to inform.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of scaling geometry and the presence of similar sibling tools, the description is grossly incomplete. It lacks details on coordinate systems, output behavior, and integration with other operations, making it difficult 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.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description adds no information about parameters. The roles of 'xfact', 'yfact', 'origin', and the format of 'geometry' are completely unexplained, leaving the agent without guidance on how to fill them.
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 the action 'scale' and the resource 'geometry'. However, it does not distinguish this tool from similar sibling tools like translate_geometry or rotate_geometry, which also modify geometry.
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 or when not to use it. The description only states the basic purpose, leaving the agent to infer usage context.
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 does not mention that the operation is non-destructive, what coordinate system is used, or that zoff is optional. The minimal statement adds little beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but at the cost of missing essential information. It is not adequately structured to help an agent decide or invoke the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters, no annotations, and an output schema (not shown). The description fails to provide context on input format, output, or behavior. It is severely incomplete for a meaningful tool invocation.
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%, so the description must explain parameters. It does not clarify what 'geometry' format (WKT, GeoJSON) is expected, nor the meaning of xoff, yoff, zoff. The description adds no value over the raw schema.
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 'Translate a geometry' clearly states the verb and resource. In geometry contexts, 'translate' means shifting by offsets. This distinguishes it from sibling tools like rotate, scale, snap, and project. However, it could be more explicit about the offsets, so it's not a 5.
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 rotate_geometry or scale_geometry. There is no mention of typical use cases or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only restates the purpose. It fails to disclose expected input coordinate format (e.g., lon/lat vs x/y), return value format, or any edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While short, the description is underspecified rather than efficiently concise. It omits critical details, sacrificing utility for brevity.
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?
The tool is relatively simple, but the description does not address key aspects like input coordinate system, ellipsoid parameterization, or the return value. Without annotations or output schema details, the description is incomplete.
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%, and the description adds no extra meaning about parameters. It does not explain that point1 and point2 should be coordinate pairs (e.g., [lon, lat]) or that ellps specifies the ellipsoid model.
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 calculates geodetic distance between points, using a specific verb and resource. It distinguishes itself from sibling tools like get_length, get_area, and calculate_geodetic_area.
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. There is no mention of context, 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?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic operation, omitting details about input formats, output, error cases, or 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but severely under-specified. It lacks essential detail and does not earn its place as a useful description.
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 complexity of geometric difference operations, one sentence is insufficient. The output schema exists but is not referenced, and the description does not cover edge cases or prerequisites.
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 input schema has 0% description coverage, and the description does not explain the parameters. 'geometry1' and 'geometry2' are left undefined, providing no additional meaning beyond their names.
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 the verb 'find' and the resource 'difference between geometries', making the purpose understandable. However, it does not distinguish this operation from the sibling 'symmetric_difference', which could lead to confusion.
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 usage guidelines are provided. The description does not mention when to use this tool versus alternatives like 'intersection', 'union', or 'symmetric_difference', nor does it specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description offers no behavioral details such as input format (WKT, GeoJSON), behavior on invalid geometries, units of area, or any side effects. The single sentence is insufficient for transparency.
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 a single sentence, making it concise and front-loaded. However, it is too sparse and lacks necessary details, so it does not fully earn its place. It is minimally viable but with clear gaps.
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's one parameter, the presence of multiple sibling area-related tools, and no annotations, the description is incomplete. It omits input format, output units, and relation to 'calculate_geodetic_area', leaving significant gaps for an agent.
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 input schema has 0% description coverage for the 'geometry' parameter. The description fails to explain what format the geometry string should be (e.g., WKT, GeoJSON), leaving agents to guess. It does not compensate for the lack of schema documentation.
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 that the tool gets the area of a geometry, specifying verb and resource. However, it does not differentiate from the sibling tool 'calculate_geodetic_area', which serves a similar but distinct purpose.
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 like 'calculate_geodetic_area' or other geometry analysis tools. The description lacks context for appropriate usage.
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, and the description does not disclose behavioral traits such as whether the tool validates input, the format of the output CRS, or any side effects. The minimal description lacks transparency.
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) and front-loaded, but it is too brief to be fully informative. It earns a middle score for brevity but lacks substance.
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?
Although there is an output schema, the description does not mention what the tool returns (e.g., CRS definition string or object). For a simple tool, the description is incomplete and leaves the agent guessing.
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 sole parameter 'coordinates' has 0% schema description coverage, and the description offers no explanation of expected coordinate order, CRS of input, or value range. This is a significant gap.
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 the tool returns a geocentric CRS for given coordinates, distinguishing it from sibling tools like get_available_crs or get_crs_info. However, it could specify what 'geocentric CRS' means or that it returns a CRS object.
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 like get_utm_crs or get_crs_info. The description does not mention prerequisites or coordinate system context.
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?
With no annotations, the description should disclose behavioral traits, but it only states the action without mentioning return format, error handling, or any 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, but omits necessary details about the parameter and output, making it overly minimal.
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 lack of annotations and schema descriptions, the tool description is incomplete; it does not explain what 'type' means or how to use the parameter.
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 input parameter 'geometry' has no schema description (0% coverage) and the description does not clarify what format or value is expected, leaving a critical gap.
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 the tool retrieves the type of a geometry, distinguishing it from sibling tools that return other geometry attributes like area or centroid.
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, such as other geometry inspection tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits. It fails to mention error handling, return format, or any constraints, leaving the agent without critical information.
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 extremely short (5 words). While concise, it sacrifices necessary detail. It is not front-loaded with essential information such as coordinate format or output specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not indicate what the tool returns. For a simple tool with one parameter and no annotations, it should specify coordinate order and expected output. It fails to provide even minimal context.
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%, and the description does not explain the coordinates parameter (e.g., order: [longitude, latitude] or [easting, northing]?). It adds no meaning beyond the bare type definition.
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 UTM CRS for given coordinates. It uses a specific verb (Get) and resource (UTM CRS), which distinguishes it from sibling tools like get_crs_info and get_available_crs.
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., get_geocentric_crs, get_crs_info). There are no exclusions, prerequisites, or context about input requirements.
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?
Without annotations, the description must disclose behavior. It does not specify the return type (e.g., boolean) or how invalid input is handled (e.g., exception vs false). The description is insufficient for an agent to understand the tool's behavior.
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 extremely concise at one sentence, but it sacrifices critical details. It is appropriately sized but too terse to fully inform.
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's simplicity and presence of an output schema, the description should still specify input format and output semantics. It fails to provide complete context for a validation tool.
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?
With 0% schema description coverage, the description must compensate by explaining the geometry parameter format (e.g., WKT, GeoJSON). It provides no additional meaning, leaving the parameter ambiguous.
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 the tool checks geometry validity. While it doesn't explicitly define 'valid', it is a standard GIS operation that distinguishes from siblings like 'make_valid'.
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 such as 'make_valid' or 'get_geometry_type'. The description lacks context for appropriate usage scenarios.
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?
With no annotations, the description must fully convey behavioral traits. It only states what the tool does but does not mention that it is a read-only operation, nor does it disclose any nuances like coordinate system handling, orientation of the rectangle, or precision. This is insufficient for safe agent invocation.
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 a single sentence with no padding, achieving conciseness. However, it sacrifices necessary details about parameter format and behavioral context, making it only minimally adequate.
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's simplicity (one parameter, no annotations), the description is too sparse. It does not explain the return value or behavior, and the output schema exists but is not referenced. The description leaves significant gaps for an agent to use 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?
There is one parameter 'geometry' of type string, but the description does not specify the expected format (e.g., WKT, GeoJSON). Given 0% schema description coverage, the description should compensate but fails to add any meaningful semantics beyond the parameter name.
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 'Get minimum rotated rectangle of a geometry' clearly states the verb (Get) and the resource (minimum rotated rectangle of a geometry), making the purpose unambiguous. However, it does not differentiate from similar sibling tools like 'envelope' or 'convex_hull', which could lead to confusion.
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 such as 'convex_hull' or 'envelope'. The description lacks any contextual cues about appropriate use cases or prerequisites.
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?
With no annotations available, the description carries full responsibility for behavioral transparency. It does not disclose how the statistic is computed, handling of weights or missing data, significance testing, or any side effects, providing almost no behavioral insight.
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 at one sentence, starting with the action verb. However, it is overly terse, omitting essential details, so it is not a model of effective conciseness as it sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (spatial autocorrelation), 4 parameters with no schema descriptions, and an output schema whose content is unknown, the description provides no contextual completeness about input formats, output structure, or statistical interpretation.
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 input schema has 0% description coverage, and the tool description provides no explanations for any of the 4 parameters (shapefile_path, dependent_var, target_crs, distance_threshold). Users are left uninformed about parameter meaning, format, or constraints.
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 the tool computes 'Moran's I Global Autocorrelation Statistic', identifying the specific statistical method. However, it does not differentiate this from sibling tools like 'gearys_c' or 'getis_ord_g' which also compute global autocorrelation statistics, limiting clarity for selection.
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 usage guidance is provided; there is no indication of when to use this tool versus alternatives, prerequisites, or exclusions. The description merely states what it does without contextualizing its application.
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?
With no annotations, the description carries full burden but only states 'Rotate a geometry.' No mention of side effects, permissions, or behavior beyond the basic action.
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 concise (single sentence), but it lacks necessary substance to be helpful.
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 complexity of geometry rotation (geometry format, rotation point, angle units), the description is too minimal and incomplete. Output schema exists but is not leveraged.
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%, and the description adds no meaning to parameters like geometry format, angle unit, or origin options. The description provides no value beyond parameter names.
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 states the verb 'rotate' and the resource 'geometry', clearly indicating the tool's purpose. However, it does not differentiate from sibling tools like 'scale_geometry' or 'translate_geometry'.
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, no prerequisites or context provided.
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, so description carries full burden. It only says 'create', implying a new geometry is produced, but fails to disclose side effects, permissions, or output characteristics beyond the schema.
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?
Single sentence is concise and front-loaded with the action. However, the brevity sacrifices completeness; not every sentence earns its place as it lacks necessary details.
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 one parameter and an output schema, description is incomplete. It doesn't clarify the input string format or the nature of the triangulation (e.g., Delaunay), leaving significant gaps for correct usage.
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 has 0% description coverage, and description adds no meaning to the 'geometry' parameter. It does not specify input format (e.g., WKT, GeoJSON), leaving the agent uninformed.
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 it creates a triangulation of a geometry, using a specific verb and resource. However, it does not differentiate from sibling tools like convex_hull or voronoi, leaving ambiguity in some contexts.
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. No context about prerequisites, input format, or intended use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks any behavioral disclosure beyond the basic operation. No annotations are provided, so the description carries full burden but fails to mention input format requirements, output details, error behavior, or performance characteristics.
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 extremely concise at five words, but it successfully conveys the tool's core purpose. However, it sacrifices necessary detail for brevity, which is acceptable but not optimal given the tool's complexity and lack of annotation support.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
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 numerous sibling tools, the description is severely incomplete. It fails to explain what the intersection represents conceptually, how inputs should be formatted, or what the output structure is, leaving the agent without critical usage context.
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?
With 0% schema description coverage, the description adds no meaning to the parameters beyond their names ('geometry1', 'geometry2'). It does not specify accepted geometry formats (e.g., WKT, GeoJSON) or clarify whether the parameters represent points, lines, or polygons.
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 'Find intersection of two geometries,' which is a specific verb+resource combination. It effectively distinguishes this tool from sibling tools like union, difference, and symmetric_difference, which handle related but distinct geometric operations.
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 usage guidelines are provided. The description does not indicate when to use this tool over alternatives like clip_vector or point_in_polygon, nor does it mention prerequisites or context-specific scenarios.
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 bears full responsibility for behavioral disclosure. It only mentions 'project' without explaining traits like CRS format expectations, handling of invalid geometries, or 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is overly brief; it prioritizes brevity over completeness. While short, it fails to include essential details that would justify its length.
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 three required parameters and an output schema, the description lacks sufficient detail. It does not mention the output type or any constraints, making it incomplete for a tool of moderate complexity.
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?
Input schema has 0% description coverage, and the description adds no extra meaning beyond parameter names. It does not specify formats for geometry (e.g., GeoJSON) or CRS identifiers, which are critical for correct use.
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 the tool projects a geometry between CRS, specifying the verb and resource. However, it does not differentiate from sibling tools like reproject_raster or transform_coordinates, which could cause confusion.
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. There is no mention of prerequisites, context, or exclusions, leaving the agent without direction.
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 carries the full burden. It only states 'reads two shapefiles directly' but does not disclose if inputs are modified, what happens with mismatched schemas, or any 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is too brief. It could be expanded without losing conciseness to add valuable detail.
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 0% schema description coverage and no annotations, the description is insufficient. It does not cover parameter purposes, return behavior, or how the tool handles edge cases like differing geometries.
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%, and the description does not explain any of the three parameters. The tool name and description hint at shapefile paths and output, but no explicit mapping or format details are given.
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 it concatenates two shapefiles vertically. It uses specific verbs and resources, but does not distinguish from sibling tool merge_gpd, which may perform a similar operation.
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 like merge_gpd, dissolve_gpd, or sjoin_gpd. The description implies concatenation but does not describe context or prerequisites.
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?
With no annotations, the description carries the burden of behavioral transparency, but it omits important details: no mention of accepted geometry formats (e.g., WKT, GeoJSON), behavior with invalid or empty geometries, output geometry type (likely polygon or multipolygon), or coordinate system handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the one-sentence description is brief, it is under-specified and lacks helpful structure. It does not earn its place by adding value beyond the name; it essentially repeats the tool name.
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's simplicity (one parameter, output schema exists), the description is incomplete. It should specify accepted geometry types, output type, and edge cases (e.g., empty input). The output schema may mitigate partial needs, but the description itself is insufficient.
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 input schema has 0% description coverage for the 'geometry' parameter. The description does not clarify the expected format (e.g., WKT, GeoJSON, binary) or constraints (e.g., must be a polygon or linestring). This essential information is missing.
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 clear verb 'Calculate' and a specific resource 'convex hull of a geometry', which distinguishes it from sibling tools like 'buffer', 'envelope', or 'simplify'. The purpose is unambiguous.
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 like 'envelope', 'minimum_rotated_rectangle', or 'buffer'. There is no mention of prerequisites or typical use cases.
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?
The description lists return values (sector counts, angles, vector lengths, p-values) but omits any behavioral traits such as whether it modifies data, required permissions, or error conditions. With no annotations, this is insufficient for a compute-heavy tool.
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 (two sentences) and front-loaded with purpose. However, it comes at the cost of omitting parameter details, making it borderline inadequate for a tool with 10 parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count (10), 0% schema coverage, and no annotations, the description is grossly incomplete. It fails to explain any input parameters, leaving an agent with insufficient information to invoke 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?
Schema description coverage is 0%, and the description provides zero information about any of the 10 parameters, including required ones like shapefile_path and value_columns. The verb 'Run' gives no clue about parameter roles 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 explicitly states 'Run dynamic LISA (directional LISA) with giddy.directional.Rose.' This clearly names the action, the specific spatial statistic, and the underlying function, distinguishing it from sibling LISA tools like moran_local.
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, nor any exclusions or prerequisites. The description does not help an agent decide between dynamic_lisa and other spatial statistics tools like getis_ord_g_local or join_counts_local.
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, and the description does not disclose behavioral traits such as side effects, assumptions about coordinate order, or whether the operation is read-only. The agent relies solely on the word 'get' for safety.
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?
At 4 words, the description is extremely concise but may be too terse, omitting necessary details. It is front-loaded but sacrifices clarity for brevity.
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 simplicity of the tool and existence of an output schema, the description is minimally adequate but lacks details on the output format and assumptions. An ideal description would clarify coordinate input requirements.
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 'coordinates' lacks any description in the schema (0% coverage) and the description merely says 'given coordinates' without specifying required format, order (e.g., [lon, lat]), or coordinate system. This is a critical gap.
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 explicitly states the action 'get' and the resource 'UTM zone' for given coordinates. It is specific and differentiates from sibling 'get_utm_crs' which likely returns the CRS. However, it could clarify what a UTM zone is for non-experts.
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 siblings like 'get_utm_crs' or other geometry tools. The description does not provide any context for selection or exclusion criteria.
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?
With no annotations, the description must disclose behavior but only says 'Make a geometry valid'. It omits important details such as whether the geometry is modified in-place or returned, error handling for already-valid geometries, or the format of the input string.
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 a single sentence and avoids fluff, but it is too short for a tool that likely requires more context. Conciseness is achieved at the cost of completeness.
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 existence of an output schema and only one simple parameter, the description is incomplete. It fails to explain input format, definition of validity, return value, or error conditions, which are necessary for a new user.
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 schema has one parameter 'geometry' with 0% description coverage. The description adds only that it makes the geometry valid, not what format (WKT, GeoJSON) is expected or what 'valid' entails. This provides minimal added meaning.
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 the action 'Make a geometry valid', which is a specific verb+resource. It distinguishes from siblings like 'is_valid' (which checks validity) and other geometry tools, but does not explicitly differentiate itself.
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 usage guidance is provided. The description does not mention when to use this tool versus alternatives like 'is_valid' or other transformation tools, nor does it specify prerequisites or limitations.
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?
With no annotations, the description carries the full burden of behavioral disclosure. It does not state that the tool returns a geometry, nor does it mention any side effects or assumptions about input formats. The simplicity of the operation somewhat mitigates this, but the lack of detail is notable.
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 a single sentence, which is concise but lacks necessary detail. While brevity is valued, here it sacrifices clarity and completeness. The structure is efficient but not effective for guiding an agent.
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 complexity of geometry operations and the presence of many sibling tools, the description is insufficient. It does not mention the return type (though an output schema exists), nor does it differentiate from similar operations. An agent would need to infer too much from the name alone.
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%, meaning neither parameter has a description. The tool description only says 'geometries' but does not specify accepted formats (e.g., WKT, GeoJSON) or coordinate system expectations. An agent cannot determine how to construct valid inputs without additional context.
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 it finds the symmetric difference between geometries, which is a specific verb and resource. However, it does not distinguish itself from sibling tools like 'difference', 'union', or 'intersection', leaving ambiguity for an agent unfamiliar with geometric operations.
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. There is no mention of use cases, when not to use, or comparisons with similar tools like 'difference' or 'union'. This omission increases the risk of incorrect tool selection.
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 provide behavioral hints. The description does not disclose whether the tool handles overlapping areas, input order, or invalid geometries. Does not mention that it is a unary operation.
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?
One sentence, no waste, but it is too brief to be fully useful while still being minimally viable.
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 no annotations and an output schema, the description should clarify return value or side effects. It does not explain the unary nature nor differentiate from sibling 'union'. Incomplete for a geometry operation tool.
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?
Parameter 'geometries' lacks description in schema (0% coverage). The description adds no information about expected format (e.g., GeoJSON, WKT) or constraints.
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 identifies the action (union) and resource (multiple geometries), and implicitly distinguishes from binary union via sibling 'union'. However, it could specify input format more explicitly.
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 vs alternatives like 'union' or 'difference'. Missing context about when a unary union is preferred over pairwise operations.
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, and the description does not disclose behavioral traits such as whether the operation is read-only, performance implications, or input constraints (e.g., points must be unique).
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 with no fluff. While very concise, it captures the core function. Could be slightly expanded without losing conciseness.
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?
Despite having an output schema, the description fails to mention that input must be points and output is polygons, nor does it clarify coordinate system or error conditions. The definition is incomplete for reliable agent usage.
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 parameter 'geometry' is a string with 0% schema description coverage. The description adds no meaning, leaving the agent unaware of expected format (e.g., GeoJSON, WKT).
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 the purpose: creating a Voronoi diagram from points. However, it does not specify the format of the 'geometry' input (e.g., GeoJSON, WKT) or the output, which could cause ambiguity.
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 voronoi over sibling tools like 'triangulate_geometry' or 'convex_hull'. Agents are left to infer usage context without explicit recommendations.
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 bears full responsibility for behavioral disclosure. However, it only states the operation type without detailing any side effects, coordinate system requirements, or accuracy implications. This leaves significant behavioral unknowns.
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 a single concise sentence, but it omits critical parameter details that could be added without excessive length. It is not information-dense given the tool's complexity.
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?
Despite having an output schema (which may document return values), the description fails to contextualize parameters or provide usage guidance. For a tool with two parameters and multiple related siblings, this description is notably incomplete.
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 input schema has 0% description coverage for parameters. The description does not clarify the expected format for 'geometry' (e.g., GeoJSON, WKT) or the allowed values for 'ellps' beyond the default WGS84. The agent lacks essential parameter context.
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 ('calculate'), the resource ('area of a polygon'), and the method ('using geodetic calculations'). It effectively distinguishes from sibling tools like 'get_area' (planar) and 'calculate_geodetic_distance' (distance).
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 (e.g., 'get_area'), nor does it mention prerequisites or exclusions. The agent is left to infer usage context.
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?
With no annotations, the description carries the full burden. It only states the basic operation, omitting details such as whether the function is read-only, default ellipsoid (WGS84), or units (e.g., azimuth in degrees vs radians). The agent gains minimal insight into behavior beyond the action.
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 concise sentence with no wasted words. It is appropriately short for a straightforward calculation tool, though it could be slightly more informative without losing conciseness.
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 complexity (4 params, no annotations), the description is incomplete. It does not explain input coordinate system, units, or output format. An output schema exists but the description offers no additional context for correct invocation.
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%, so description must compensate. It mentions 'distance' and 'azimuth' but omits 'start_point' (what format? likely [longitude, latitude]) and 'ellps' (default WGS84). The description adds little meaning beyond the schema.
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 the tool computes a point from distance and azimuth. It distinguishes from sibling tools like 'calculate_geodetic_distance' and 'calculate_geodetic_area'. However, it does not explicitly mention that the calculation is on an ellipsoid, which is implied by the tool name.
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 (e.g., buffer, project_geometry). The description lacks context for when this specific geodetic calculation is appropriate.
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?
With no annotations, the description carries full burden for behavioral disclosure. It mentions using 'geopandas.clip' and returns a dict, but fails to specify side effects (e.g., file creation/overwriting), error handling for missing files or CRS mismatches, or whether it is a read-only operation.
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?
Description is short and structured with 'Args:' and 'Returns:' sections. The core purpose is stated in one sentence. No unnecessary words, though it could be more informative without being 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?
Despite a simple operation, the description lacks details on when to prefer this over similar tools (e.g., 'intersection', 'difference'). The output schema is not shown, and return description is basic. In a tool-rich environment, more context is needed.
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%, so description must compensate. It adds minimal context beyond parameter names: 'Path to the input geospatial file' for gdf_path is vague. No details on supported formats, paths relative rules, or behavior of output_path when null.
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?
Clearly states the action ('clip') and resource ('vector geometries') using a specific verb+resource. It distinguishes itself from sibling geometry tools like 'buffer' or 'intersection' through the unique operation name, but lacks explicit differentiation statements.
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 over alternatives like 'difference' or 'intersection'. Does not mention prerequisites such as CRS compatibility or file requirements, leaving the agent with little context for decision-making.
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, and the description gives no behavioral details such as the coordinate system of the output or any side effects. Output schema exists but is not referenced.
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?
Description is a single, well-structured sentence with no redundancy. It could add a bit more information 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?
For a single-parameter tool with an output schema, the description is incomplete. It omits parameter format and output details, relying entirely on the output schema.
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%, and the description adds no meaning beyond the parameter name. The expected format for 'geometry' (e.g., WKT, GeoJSON) is not specified.
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 the action (Get) and resource (bounding box of a geometry). It distinguishes from siblings like get_bounds by using the specific term 'envelope'.
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., get_bounds). No context about 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?
Description is minimal, adds no behavioral details beyond the name. Without annotations, the agent is left uninformed about side effects or execution 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?
Single sentence is short and to the point, but trades off completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 params, multiple siblings), the description fails to convey required inputs, output, or purpose nuances, making it inadequate for correct invocation.
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?
Description does not explain any of the four parameters (shapefile_path, dependent_var, target_crs, distance_threshold), leaving the agent blind despite 0% schema coverage.
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?
Description clearly states the tool computes Global Geary's C Autocorrelation Statistic, distinguishing it from siblings like morans_i and getis_ord_g.
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 Geary's C vs alternatives like Moran's I, no context on appropriateness or prerequisites.
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 exist, so the description must disclose behaviors. It only states it computes an analysis, with no mention of side effects, permissions, or data access patterns.
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 single sentence is concise and front-loaded, but it omits crucial details about parameters and usage, making it minimally adequate.
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?
Despite having an output schema, the description lacks parameter semantics and usage guidelines. For a tool with 4 parameters and no schema coverage, the description is incomplete.
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%, yet the description provides no explanation of parameters like shapefile_path, dependent_var, target_crs, or distance_threshold. The agent gains no understanding of how to set them.
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 explicitly states the action 'Compute Getis-Ord G' and the context 'for global hot spot analysis'. It clearly distinguishes from the sibling 'getis_ord_g_local'.
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 like Morans I or local versions. The description lacks context about appropriate scenarios.
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 carries the full burden. It does not disclose what happens for invalid geometry, what units are used, or whether the tool works for all geometry types. The description adds 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 a single, front-loaded sentence that efficiently conveys the core purpose. However, it could benefit from additional detail 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 the tool's simplicity and the presence of an output schema, the description is still too sparse. It does not explain what geometry types are accepted or any edge cases, leaving significant gaps for an AI agent.
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 input schema has 0% description coverage, and the description does not clarify the format or constraints of the 'geometry' parameter (e.g., WKT, GeoJSON). The agent is left to infer from the parameter name alone.
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 the purpose: 'Get the length of a geometry.' It uses a specific verb and resource, and distinguishes from sibling tools like get_area and get_centroid. However, it does not specify what type of geometry (lines, polygons) or what length means (e.g., perimeter for polygons).
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 guidelines are provided on when to use this tool vs. alternatives. There is no mention of context, prerequisites, or exclusions. The agent receives no assistance in deciding between get_length and similar geometric measurement tools.
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 function, not how it behaves (e.g., whether it's read-only, what geometry types are supported, or the output format). The presence of an output schema partially compensates, but the description lacks essential 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is optimally concise for the minimal information provided.
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 low parameter count and existence of an output schema, the description is insufficient. It fails to compensate for the missing parameter descriptions and lacks usage guidance, making it incomplete for reliable agent use.
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 input schema has one parameter 'geometry' with no description (0% coverage). The description adds no additional meaning, failing to specify the expected format (e.g., WKT, GeoJSON). This is a critical gap for correct invocation.
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 the action (get) and resource (bounds) and the input (geometry). It is specific enough to convey the basic purpose, though it could be more precise by specifying 'bounding box' to differentiate from sibling tools like 'envelope'.
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?
There is no guidance on when to use this tool versus alternatives (e.g., 'envelope', 'minimum_rotated_rectangle'), nor any conditions or prerequisites. The agent is left to guess the appropriate context.
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?
With no annotations, the description must disclose behavioral traits. It lists output components (coefficients, SE, fit metrics) but omits important details like side effects, performance implications, or assumptions about the input data. The mention of optional AK test is helpful but insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise but lacks structure. For a complex tool with many parameters, a more structured format (e.g., listing key parameters or output details) would be warranted, but the current form sacrifices completeness for brevity.
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's complexity (15 parameters, cross-sectional spatial model) and the absence of schema descriptions, the description is insufficient. It does not explain the input data requirements, how parameters interact, or the full output structure beyond a brief list, despite having an output schema.
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 input schema has 15 parameters with 0% description coverage, yet the tool description provides no explanation for any parameter. Critical parameters like weights_method, distance_threshold, and robust are left entirely unexplained, making selection and invocation difficult.
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 identifies the tool as a spatial lag model (spreg.GM_Lag) and specifies it operates on cross-sectional data. The verb 'Run' and the named model differentiate it from sibling tools like OLS or spatial autocorrelation tests.
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 spatial lag modeling on cross-sections, but provides no explicit guidance on when to use this versus alternatives like ols_with_spatial_diagnostics_safe. No when-not-to-use or prerequisite information is given.
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?
The description only states the basic function. No details on acceptable CRS formats, coordinate formats, error behavior, or return value format. Without annotations, this is insufficient for an AI to understand the tool's behavior fully.
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 short, which can be seen as concise, but it lacks detail needed for proper usage. It could benefit from a second sentence clarifying parameter formats.
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?
The description does not provide sufficient information about coordinate input format or CRS specification. While output schema exists, the lack of parameter details makes the tool difficult to use correctly.
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%, and the description provides no parameter details. The agent cannot determine coordinate order or CRS format from the description alone.
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 the action (transform) and objects (coordinates between CRS). It is sufficiently specific to distinguish from related tools like project_geometry which handles full geometries.
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?
No explicit when-to-use or when-not-to-use guidance. The description does not mention alternatives or context for choosing this over project_geometry.
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?
With no annotations, the description must cover behavioral traits. It states the tool returns a snapped geometry but does not mention that the input geometries remain unchanged, nor does it disclose potential side effects like coordinate modifications or performance implications for large geometries.
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 concise, using a clean docstring format with Args and Returns sections. It contains no redundant information and is well-structured for quick parsing.
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 lack of annotations and schema descriptions, the description is incomplete. It does not explain the snapping algorithm, edge cases (e.g., what happens if no vertices are within tolerance), or the context in which snapping is useful. The return format is described but the overall context for using this tool is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning. It describes each parameter as 'WKT string' and 'distance tolerance', which is helpful but omits details about tolerance units, acceptable values, or the format of WKT. It adds some value beyond the schema but is not comprehensive.
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 the verb 'snap' and the objects 'one geometry to another', specifying the use of shapely.ops.snap. This distinguishes it from sibling geometry tools like 'buffer' or 'intersect', but does not explicitly differentiate its unique behavior.
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 is provided. The description lacks information on prerequisites, such as the requirement for geometries to be within the tolerance distance for snapping to occur.
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 fully disclose behavior. It does not mention edge tile handling, tile format, coordinate system preservation, overwrite behavior, or side effects. The output schema exists but is not described, leaving behavioral gaps.
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 concise, with a clear purpose statement followed by a parameter list. No extraneous text. However, the parameter list could be integrated into the description to improve flow.
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 existence of an output schema, the description need not explain return values, but it should cover side effects (file writing) and prerequisites (directory existence, raster validity). The current description is incomplete for a tool that writes multiple files.
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 must add meaning. It provides basic labels (e.g., 'input raster path') but does not specify constraints (e.g., tile_size positive integer, destination_dir autocreation, supported raster formats). This adds minimal value over parameter names.
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?
Clearly states the tool splits a raster into square tiles and saves them individually. The verb 'split' and resource 'raster' are specific, and it distinguishes from sibling raster tools like clip_raster_with_shapefile or resample_raster.
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. No mention of prerequisites, edge cases, or scenarios where other tools (e.g., extract_band) would be more appropriate.
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, and the description only states it 'runs' the analysis without disclosing side effects, data validation steps, or what happens with invalid inputs. Behavioral transparency is minimal.
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 of 15 words, which is very concise. However, it omits necessary details for parameter and usage context, slightly reducing its effectiveness.
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's complexity (12 parameters, spatial econometrics), the description lacks essential context about output, prerequisites, and how parameters affect analysis. Output schema exists but is unmentioned.
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?
With 0% schema description coverage and no parameter explanations in the description, the agent gains no insight into critical parameters like weights_method, k, m, or permutations. This is a severe deficiency.
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 runs a 'giddy Spatial Markov' analysis on panel data from a shapefile, specifying the input format and type of analysis. This distinguishes it from sibling tools like morans_i or gearys_c.
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 like other spatial statistics. While it mentions Spatial Markov, it lacks guidance on appropriate conditions or comparisons.
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 carries full burden. It mentions an optional output path for saving, but does not disclose whether the operation modifies the input file or other side effects. The return format is described, but behavioral traits like required permissions or error handling are omitted.
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 concise: a one-sentence summary followed by a structured arg list. It is front-loaded and avoids unnecessary details.
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?
The tool has 3 parameters, all explained. An output schema exists, so the return description is sufficient. However, it lacks context on prerequisites (e.g., file must exist) and error handling, which would be helpful for a geospatial 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?
The description includes a brief arg list explaining each parameter (e.g., 'gdf_path: Path to the geospatial file'), which adds meaning beyond the schema's types. Given 0% schema description coverage, this compensates well.
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 'Dissolve geometries by attribute using geopandas.dissolve', which is a specific verb+resource. However, it does not explicitly differentiate from sibling tools like 'merge_gpd' or 'unary_union_geometries', but the operation is distinct enough.
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 states what the tool does without mentioning prerequisites or appropriate use cases.
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, so the description carries full burden. It does not disclose any behavioral traits such as if the list is cached, if it requires initialization, or the performance impact. The operation is likely read-only but not confirmed.
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?
Extremely concise at 4 words, front-loaded. However, it may be too minimal for a tool with no other documentation. Every word earns its place but could benefit from a brief context sentence.
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?
Tool complexity is low (no params, output schema exists). Description covers the basic purpose but omits what 'available' means (e.g., all EPSG codes? system-specific?). With output schema, return format is known, but completeness is average.
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%. Per guidelines, 0 parameters gives a baseline of 4. The description adds no parameter information, but none is 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?
The description clearly states it returns a list of available CRS, distinguishing it from more specific CRS tools like get_crs_info or get_geocentric_crs. However, it lacks any detail about the contents or scope of the list.
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 siblings like get_crs_info or get_utm_crs. The description does not mention context 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?
No annotations are provided, so the description must fully disclose behavior. It only lists parameters and a high-level purpose, omitting details about error handling, side effects (e.g., in-memory object creation), or output format beyond the schema.
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 short and uses a bullet list for parameters, making it scannable. Every sentence is functional, but it could be slightly more informative without adding length.
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 existence of sibling tools and an output schema, the description fails to differentiate when to use knn_weights vs. other weight creation tools. It does not mention that the output is a PySAL W object, nor does it cover edge cases or provide usage 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?
With 0% schema coverage, the description adds brief explanations for all three parameters (data_path, k, id_field), clarifying their roles and types. However, it lacks constraints (e.g., k must be positive integer, id_field must be unique) and typical usage examples.
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 'Create a k-nearest neighbors spatial weights (W) object from point data', which is a specific verb+resource combination. It distinguishes from siblings like distance_band_weights and build_and_transform_weights.
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 such as distance_band_weights. There is no mention of prerequisites, limitations, 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the operation type (merge based on attributes), preserves left geometry, and writes to output_path. However, it lacks details on potential side effects, error handling, or prerequisites like CRS alignment.
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 fairly concise yet includes structured parameter docs. It doesn't waste words, though the mismatch in parameter names adds unnecessary confusion. It could be slightly tighter by aligning with schema names.
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's complexity (merge with multiple join options) and schema with only 3 params, the description's parameter mismatch and lack of details on join keys (on, left_on, etc.) leave gaps. An output schema exists, so return values aren't needed, but prerequisites like attribute existence are missing.
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 input schema has 3 parameters with zero description coverage. The description adds meaning by describing parameters like left_shapefile_path and how, but these names mismatch the schema (shapefile1_path, shapefile2_path). The additional parameters not in the schema further complicate understanding, making the description less useful for the actual tool interface.
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 it merges two shapefiles based on common attribute columns and distinguishes it from a spatial join. However, the parameter names in the description (left_shapefile_path, right_shapefile_path) do not match the actual schema (shapefile1_path, shapefile2_path), which could cause confusion.
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 explicitly notes it performs a database-style join, not a spatial join, which hints at appropriate usage compared to sibling spatial join tools. However, it does not provide explicit when-to-use or when-not-to-use guidance, nor mention alternatives like sjoin_gpd.
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?
With no annotations, the description bears full responsibility for behavioral disclosure. It mentions the spatial join and return type, but omits important details such as performance considerations, error handling, or the fate of input data. The description is insufficient for an agent to fully understand 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 concise and uses a clear docstring-like structure with Args and Returns sections. The main functionality is front-loaded. Minor redundancy in the Returns section ('status, message, and output info') could be more specific, but overall efficient.
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?
There is an output schema, so return value details are not needed in the description. The description covers the core functionality adequately for a simple tool. However, for a 3-parameter tool with no annotations, it lacks depth in areas like file format constraints and error conditions, making it merely adequate.
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 must compensate. It lists three parameters with brief explanations, but lacks details on file formats, CRS requirements, or defaults. The description adds some meaning but does not fully compensate 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 the action ('Check'), the resources ('points inside polygons'), and the method ('spatial join with predicate='within''). It effectively differentiates from siblings like 'sjoin_gpd' by specifying the 'within' predicate.
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 on when to use this tool versus alternatives such as 'sjoin_gpd' or 'overlay_gpd'. The description implies usage for point-in-polygon checks but does not provide context for when it is appropriate or what alternatives exist.
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 fully disclose behavior. It states a read-compute-write operation but does not mention file overwrite behavior, required CRS, or potential side effects, leaving significant gaps.
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: one sentence for purpose and a clear bullet list for parameters. Every part serves a purpose, no wasted words, and well-structured for quick scanning.
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?
The tool is simple with 4 parameters and an output schema, so the description covers basics. However, it lacks behavioral context (e.g., overwrite, errors) and usage guidance, making it minimally adequate for a standalone read.
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 adds crucial meaning: clarifying that band indices are 1-based and that destination is an output path. This compensates well for the schema's lack of descriptions, though more formatting details would improve it.
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 the tool computes NDVI and saves to GeoTIFF, using a specific verb ('Compute') and resource (NDVI). However, it does not differentiate from similar tools like raster_algebra, which could also compute indices, lacking sibling distinction.
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 raster_algebra or concat_bands. It implies basic usage but offers no context for selection among many similar raster tools.
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 carries full burden. It states it uses geopandas.overlay and returns a dict with status, message, and output info, but lacks details on error handling, side effects, or prerequisites (e.g., file existence, CRS matching).
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 concise and well-structured with a docstring format (Args, Returns). It front-loads the main purpose and provides necessary details without extraneous text.
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 complexity (4 params, output schema exists), the description covers param descriptions and return structure. However, it could be more complete by mentioning file format expectations and CRS handling, and referencing siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must add meaning. It explains each parameter's purpose and lists valid options for 'how', but does not specify expected file formats or path requirements.
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 the verb 'overlay' and resource 'GeoDataFrames', and mentions using geopandas.overlay. It distinguishes from siblings by being a generic overlay tool with a 'how' parameter, but could be more explicit about its flexibility.
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 like the specific intersection, union, etc. siblings. The description only explains what it does, not when it's appropriate.
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 exist, so description carries full burden. It mentions source can be local or URL, but fails to disclose behavior regarding nodata values, file format restrictions, performance implications, or error handling. Minimal behavioral context beyond the basic calculation.
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 clear sentences with a structured parameter list. Every sentence earns its place; no fluff. Front-loaded with the core function.
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 statistics tool with one parameter and an output schema (not shown but present), the description covers the essential operation. However, it omits details like band interpretation, nodata handling, and coordinate reference system implications, leaving some ambiguity.
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%; description only adds that source is a path (local or URL). This is marginal value over the raw schema, which already shows a string parameter. No details on accepted formats, patterns, 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 verb (calculate) and the resource (raster) and specifies the outputs (min, max, mean, std for each band). It effectively distinguishes from sibling tools like 'raster_histogram' and 'zonal_statistics'.
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., focal_statistics for local windows, raster_histogram for distribution, zonal_statistics for zones). No when-not-to-use or prerequisites mentioned.
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 present, so the description carries the burden. It describes a read operation with no side effects, which is appropriate, but it doesn't elaborate on what 'stats' are returned or any limitations (e.g., file size, supported formats). The presence of an output schema partially mitigates this, but the description adds limited behavioral detail.
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 with no fluff. It is concise and efficient, though it could be slightly more informative without becoming 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?
For a single-parameter tool with an output schema, the description is mostly adequate but lacks details about the nature of the stats and data preview. It does not list supported file formats or handling of errors. The presence of many sibling tools suggests more context could help disambiguate.
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?
Only one parameter 'file_path' with a string type. Schema description coverage is 0%, so the description must compensate. It adds the context that the file is geospatial, but does not clarify allowed formats, path conventions, or that the function returns stats and a preview. Given the simplicity of the parameter, a score of 3 is appropriate.
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 the verb 'reads' and the resource 'geospatial file' and mentions returning 'stats and a data preview'. It distinguishes itself from sibling tools like 'write_file_gpd' by focusing on reading, but does not explicitly contrast with other read-like tools such as 'metadata_raster'.
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 usage guidelines are provided. The description does not specify when to use this tool over alternatives, such as 'metadata_raster' or 'get_geometry_type', nor does it mention prerequisites or context.
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?
With no annotations, the description must disclose behavior. It only says it performs a spatial join and returns a dictionary, but does not mention if it modifies input files, requires specific permissions, or handles large datasets. No contradictions, but insufficient disclosure.
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 well-structured with Args and Returns sections, providing clear organization. It is fairly concise given the parameter count, though the 'Args' block adds minor redundancy.
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?
The description covers inputs and return type, but omits details like default behavior when output_path is null, whether intermediate files are created, and any limitations on file formats. An output schema exists but is not referenced.
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 the description partially compensates by listing each parameter with a brief explanation. However, it lacks details on allowed values for 'how' and 'predicate' beyond examples, and no format for paths.
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 explicitly states 'Spatial join between two GeoDataFrames using geopandas.sjoin', which is a specific verb+resource. It clearly distinguishes from nearby siblings like sjoin_nearest_gpd.
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 such as overlay_gpd or merge_gpd. It does not mention scenarios where spatial join is appropriate or when to choose a different predicate.
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 carries full burden. It only states the basic operation without disclosing input format (WKT vs GeoJSON), error handling, or return type. This is insufficient for a tool with no 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?
The description is extremely concise with a single sentence. It is front-loaded and to the point, though it may be too terse and could benefit from additional detail without becoming 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 simplicity (one parameter, no nested objects) and existence of an output schema, the description is minimally adequate. It states the core function but lacks details on input format and output, so it is not fully 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 description coverage is 0%, so the description must compensate. It does not explain the expected format of the geometry string (e.g., WKT, GeoJSON), leaving ambiguity. The parameter name alone is insufficient.
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 'Get' and the resource 'centroid of a geometry', which is specific and distinguishes it from sibling tools like get_area, get_length, envelope, etc.
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?
No explicit guidance on when to use this tool versus alternatives. Usage is implied: if centroid is needed, use this tool. However, no exclusions or comparisons are provided.
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?
With no annotations, the description partially carries the behavioral transparency burden. It outlines the pipeline steps (read, build/load weights, convert numeric, check NaNs, run OLS) and notes the tool is 'safe'. However, it does not clarify what happens when NaNs are found, what 'convert numeric' entails, or error handling for missing parameters.
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 relatively concise: a one-line summary followed by a bulleted parameter list. It front-loads the purpose. However, the first sentence could be more streamlined (e.g., removing jargon like 'MCP pipeline'). Overall, it is clear and organized.
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 9 parameters, no annotations, and no schema descriptions, the description covers all parameters and outlines the pipeline. However, it omits details on the output (though output schema exists), the exact diagnostics included, and behavior when both 'weights_path' and 'weights_method' are provided. It is adequate but has notable gaps.
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?
Although the input schema has 0% description coverage, the tool's parameter list in the description adds meaningful explanations for all 9 parameters, such as specifying that 'data_path' is a path to shapefile or GeoPackage, and conditional requirements for 'threshold' and 'k'. This adds significant value beyond the schema types.
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 the tool performs an OLS pipeline with spatial diagnostics, including reading a shapefile, building/loading weights, converting numeric fields, checking NaNs, and running OLS. While it distinguishes from siblings by specifying a safe pipeline, it could be more specific about the spatial diagnostics output.
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 does not provide any guidance on when to use this tool versus alternatives like morans_i or simple OLS. No explicit when-to-use or when-not-to-use conditions are given, leaving the agent to infer from the name and parameter list.
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, so the description must convey behavioral traits. It only states 'compute histogram' without disclosing side effects, permissions, or whether it is read-only. No mention of return format or storage.
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: one sentence for purpose and brief parameter list. No unnecessary words or redundancy.
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 existence of an output schema (not shown), the description suffices for a simple tool with two parameters. However, lacks details on supported file formats or behavior when bands vary, which could help in context with many sibling tools.
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 has 0% description coverage; the description adds meaning for both parameters: 'source' is path to input raster and 'bins' is number of bins. However, it does not explain expected input formats or constraints beyond the schema types.
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 computes histogram of pixel values for each band, using specific verbs and resource. It distinguishes from sibling raster tools like raster_band_statistics by focusing on histogram specifically.
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 like raster_band_statistics or zonal_statistics. Does not mention prerequisites or context where histogram computation is preferred.
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 carries full burden. It fails to disclose behavioral traits such as what 'adaptive' means, how parameters like eps and min_samples affect clustering, or any data quality requirements. The output schema exists but behavioral details beyond return format are absent.
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, front-loading the essential purpose and constraints. It is concise but very brief; while efficient, it lacks structural elements like bullet points or separate sections that could improve readability for a tool with 6 parameters.
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?
Despite having an output schema, the description fails to explain the adaptive nature of DBSCAN, expected input geometry, or parameter interplay. With 6 parameters and a moderately complex algorithm, the description is too sparse to enable confident usage without external knowledge.
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%, yet the description only adds value for one parameter: dependent_var should not be provided. No other parameters (shapefile_path, target_crs, distance_threshold, eps, min_samples) are explained, leaving the agent without guidance on their meaning or usage 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 tool performs 'Adaptive DBSCAN clustering', with specific constraints 'requires coordinates, no dependent_var'. The verb 'clustering' and the resource 'Adaptive DBSCAN' differentiate it from siblings, as no other tool in the list mentions clustering algorithms.
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 implicitly guides usage by stating prerequisites (coordinates) and a constraint (no dependent_var), but does not explicitly mention when not to use or suggest alternatives. Given the specialized nature, it provides clear context for appropriate invocation.
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, so description must cover behavioral aspects. It describes building and transforming weights and parameter details but does not disclose what the output is (e.g., returns a pysal weights object), side effects, or permissions. The output schema exists but is not referenced in the description.
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 well-organized with a clear list of parameters and explanations. It is informative but slightly lengthy; could be tightened by removing redundant default value notes. Still, it front-loads the core action and uses bullet points effectively.
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 7 parameters, no schema descriptions, and no annotations, the description covers parameter semantics well but omits the tool's return behavior (despite existence of output schema) and any prerequisites (e.g., valid file path). This gap reduces completeness for an agent deciding to invoke the tool.
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?
Input schema has 0% description coverage, so the description adds crucial meaning by explaining each parameter, including conditional requirements (e.g., threshold for distance_band). It specifies allowed methods and transform types. However, it lacks examples or more detailed constraints for enum-like 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 explicitly states it builds and transforms spatial weights in one step, with clear verb ('build_and_transform'), resource ('weights'), and lists parameters. It distinguishes from siblings like 'weights_from_shapefile' (only build) and 'build_transform_and_save_weights' (build and transform then save).
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 on when to use this tool versus alternatives. It mentions 'in one step' but does not compare with separate build and transform tools or other siblings like 'distance_band_weights' or 'knn_weights'. No when-not-to-use or prerequisite conditions are given.
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?
With no annotations, the description carries full burden. It mentions inputs and return dictionary but does not disclose side effects, read-only nature, or potential destructive actions beyond writing an output file.
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 reasonably concise but uses a verbose docstring format with Args and Returns. It could be more compact while retaining 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?
Given the simple tool nature and the mention of return dictionary (status, message, output path), the description is complete enough for basic usage, though it lacks edge cases.
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 meaning: explains raster_path, statistic (with options), size (odd integer), and output_path (optional). This adds value beyond the schema alone.
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 'Compute' and the resource 'focal (moving window) statistics on a raster', which distinguishes it from sibling tools like zonal_statistics.
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 raster_algebra or zonal_statistics, nor any mention of 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adds some behavioral context by stating that it uses 'shapely.geometry.shape' and returns a dictionary with status, message, and WKT geometry. However, it lacks details on error handling, performance implications, or validation of input GeoJSON.
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 concise with two introductory sentences followed by a brief '[Args:]' and '[Returns:]' list. It is front-loaded with the purpose. Could be slightly structured better by separating the details, but overall efficient.
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 low complexity and that an output schema is indicated (though not shown), the description covers the core conversion purpose, parameter, and return format. However, it lacks usage guidelines, error mentions, and compatibility notes, 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 schema has 0% description coverage, so the description must compensate. It explains the single parameter as 'geojson: GeoJSON dictionary,' which adds meaning beyond the schema's 'object with additionalProperties true.' However, it does not provide examples or constraints on the GeoJSON structure.
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: 'Convert GeoJSON to a Shapely geometry using shapely.geometry.shape.' It specifies the input (GeoJSON) and output (Shapely geometry), and distinguishes it from the sibling tool 'geometry_to_geojson' which performs the reverse operation.
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 like 'geometry_to_geojson' or other geometry manipulation tools. The description does not mention any prerequisites, context, or exclusions for usage.
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 mentions the underlying implementation (shapely.ops.nearest_points) and the return format (dictionary with status, message, and WKT point). However, it lacks detail on error handling, behavior with invalid geometries, or performance considerations. With no annotations, the description carries full burden and provides moderate 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?
The description is concise at three sentences, with a clear front-loaded purpose and structured Args/Returns sections. Every sentence adds information, though the Args/Returns section partially duplicates schema information.
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 description explains the return format (dictionary with status, message, and nearest point as WKT) and the tool's simple parameter requirements. With an output schema present, the description is sufficiently complete for this straightforward operation, though it could mention edge cases.
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 explains that geometry1 is the first geometry (e.g., a point) and geometry2 is the second geometry, both as WKT strings. Given the schema coverage is 0%, the description adds minimal extra meaning beyond what the schema provides. It does not specify valid WKT formats 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 that the tool finds the nearest point on geometry2 to geometry1, using the specific verb 'Find' and resource 'nearest point on geometry'. It distinguishes itself from sibling tools like 'snap_geometry' or 'project_geometry' by focusing on the nearest point operation.
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. It does not mention prerequisites, limitations, or scenarios where this tool is preferred over others like 'project_geometry' or 'calculate_geodetic_distance'.
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?
With no annotations, the description is the sole source of behavioral info. It only states the operation and parameters, but omits side effects (e.g., file creation, data mutation), permissions, performance implications, or error handling. The return type is vaguely described as 'Dictionary with status, message, and output info' without specifics.
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 concise with a clear structure (Args and Returns sections) and no superfluous content. However, the Returns section is vague and could be slightly more informative without losing conciseness.
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 5 parameters, no annotations, and an output schema (though not detailed in context), the description covers basic functionality but lacks guidance on output structure, edge cases, or integration with sibling tools. It is adequate for a straightforward tool but leaves several behavioral aspects unaddressed.
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 the description must compensate. It provides basic meanings for each parameter (e.g., 'Path to the left geospatial file'), going beyond just type definitions. However, it lacks details on formats, unit for max_distance, and default behaviors, making it minimally helpful but not thorough.
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 'Nearest neighbor spatial join using geopandas.sjoin_nearest', explicitly specifying the verb ('join') and the resource (geospatial data). It distinguishes itself from siblings like sjoin_gpd by emphasizing 'nearest neighbor', making the tool's unique 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for nearest neighbor joins, but does not explicitly state when to use this tool over alternatives like sjoin_gpd (exact spatial join) or other operations. No when-to-use or when-not-to-use guidance is provided, leaving the agent to infer from the tool name and description.
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?
Without annotations, the description carries the full burden. It discloses the return format (dictionary with status, message, and statistics) but does not mention performance, CRS requirements, or potential side effects like file locking.
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 concise (two sentences plus structured Args/Returns) and front-loaded with the core purpose. Each sentence adds value without redundancy.
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 tool with 3 parameters and no annotations, the description is adequate but incomplete. It lacks details on coordinate system handling, required raster/vector compatibility, and potential errors. The output schema exists but is not described.
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 value by explaining the stats parameter with examples ('mean', 'min', 'max', 'std'). However, it does not specify the exact allowed values or format for all parameters, leaving 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 verb 'calculate' and the resource 'statistics of raster values within polygons'. It distinguishes from sibling tools like 'focal_statistics' and 'raster_band_statistics' by specifying the zonal operation.
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 such as 'focal_statistics' or 'raster_histogram'. It lacks explicit context for intended usage 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?
No annotations are provided, and the description does not disclose behavioral traits such as validation, error handling, performance implications, or requirements (e.g., CRS or geometry type). It only mentions 'from point data' but lacks depth.
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 concise with one sentence and clear bullet points for parameters. No redundant information; every sentence serves a purpose.
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 large suite of sibling tools, the description lacks differentiation from other weight creation tools (e.g., knn_weights, weights_from_shapefile). It does not mention the output structure even though an output schema exists. Adequate but with gaps.
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 adds meaningful context to all four parameters (e.g., threshold in CRS units, binary vs inverse distance) beyond the input schema which has zero descriptions. This compensates for the 0% schema coverage effectively.
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 creates a distance-based spatial weights object from point data, with a specific verb and resource. It distinguishes from siblings like knn_weights (k-nearest) and weights_from_shapefile (contiguity).
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 explicit guidance on when to use this tool versus alternatives (e.g., knn_weights or weights_from_shapefile). It only describes parameters without contextual usage advice.
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 states the core action without disclosing error handling (e.g., invalid band_index), overwrite behavior, or performance considerations. The behavioral impact is narrow and under-specified.
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: a one-line purpose and a three-line parameter list. Every sentence adds value, no redundancy. Well-structured for quick parsing.
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?
Covers the basic operation and parameters but lacks broader context: no mention of required permissions, coordinate system handling, or when to prefer this over sibling extraction tools. With an output schema present, return values are covered, but overall completeness is average.
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 adds meaning beyond the bare schema by explaining each parameter's purpose. Notably, 'band_index' is clarified as 1-based, and 'source' supports path or URL. However, details like accepted raster formats are missing.
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?
Clearly states the verb 'extract' and the resource 'band from a multi-band raster', with the specific output format 'single-band GeoTIFF'. Unambiguously distinguishes from sibling tools like concat_bands or compute_ndvi.
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 vs alternatives. Sibling tools like concat_bands or compute_ndvi are not mentioned, and no context is provided for selecting this tool over others.
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?
With no annotations provided, the description must fully disclose behavior. It only states the basic operation and return value, but does not disclose performance implications, side effects (e.g., file writing), or error conditions. For a raster processing tool, this is insufficient 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?
The description follows a clean docstring format with Args and Returns sections. It is concise yet covers the key parameters and output. A minor improvement would be removing redundancy, but overall it is well-structured and information-dense.
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 existence of an output schema, the description adequately explains the return value. It covers inputs, outputs, and the optional save behavior. For a tool of moderate complexity, it is mostly complete, though it could mention supported raster formats or CRS handling.
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 schema has 0% description coverage, so the description adds essential meaning. It explains raster_path, azimuth (in degrees), angle_altitude (in degrees), and output_path (optional). However, it omits value ranges (e.g., azimuth 0-360, altitude 0-90) and defaults, which could help the agent use the tool correctly.
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 ('Generate hillshade') and the input resource ('from a DEM raster'). Among sibling tools like compute_ndvi or reclassify_raster, this tool has a distinct purpose, and the description effectively communicates its specificity.
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 lacks any guidance on when to use this tool versus alternatives (e.g., slope or aspect). It does not mention prerequisites like CRS requirements or coordinate system, nor does it address limitations such as memory constraints for large rasters.
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?
With no annotations, the description must fully disclose behavior. It states output is saved to output_path and returns a dict with status/message, but lacks details on error handling, overwrite behavior, or performance implications. It does not contradict any annotations (none provided).
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 brief and well-structured in a standard docstring format with Args and Returns sections. Every sentence is informative, and the purpose is front-loaded with no redundant 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?
The description covers the basic purpose and parameters but lacks output schema details (e.g., exact keys in the returned dict) and constraints on the mapping dictionary. Given simplicity, it is adequate but not thorough.
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 adds meaning beyond the schema by explaining each parameter: raster_path (input path), reclass_map (mapping dict with example), output_path (save location). Schema coverage is 0%, so this is essential. It could be strengthened by specifying numeric key/value 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 tool's action ('Reclassify raster values') and the method ('using a mapping dictionary'). It distinguishes itself from sibling tools like clip_raster_with_shapefile or raster_algebra by specifying reclassification with a mapping.
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 vs alternatives, such as raster_algebra or resample_raster. There is no mention of prerequisites, data type constraints, or scenarios where this tool is inappropriate.
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 states it 'saves the result' but does not disclose side effects like overwriting policy, permissions required, or whether the output is immediately available. Lacks behavioral context beyond basic operation.
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?
Main sentence followed by parameter list. Clear structure, though the parameter descriptions are somewhat verbose. No unnecessary words, but could be slightly more concise.
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?
Output schema exists but no annotations. Description does not explain return value or confirmation of success. Given the tool writes a file, more detail on output behavior would improve completeness.
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?
Schema descriptions coverage is 0%. The description compensates fully: explains source accepts local path/URL, scale_factor meaning with examples, resampling method names, and destination path. This adds crucial 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?
Description clearly states 'Resample a raster dataset by a scale factor and save the result.' This provides a specific verb and resource, and distinguishes from sibling raster tools like clip_raster or reproject_raster.
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. Does not mention prerequisites, restrictions, or compare to other raster processing tools.
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 carry the burden. It discloses CRS conversion behavior but does not mention overwrite behavior, error handling, or limitations (e.g., polygon count, raster size). Partial but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact: a clear one-line purpose followed by a bulleted list of parameters. No redundant or generic language. Every sentence adds value.
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 tool with 3 required parameters and an output schema (assumed to document return), the description covers the main flow but omits important context: file overwrite behavior, required permissions, expected output format from the output schema, or error scenarios.
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?
Despite 0% schema description coverage, the description adds meaning to all three parameters: clarifies raster_path_or_url can be URL or local path, shapefile_path must be .shp, destination is local path. This exceeds the schema's empty strings.
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 specifies the action ('Clip a raster dataset'), the input resource ('polygons from a shapefile'), and the output ('write the result'). It distinguishes from sibling 'clip_vector' by explicitly mentioning raster and shapefile.
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 like 'clip_vector' or other raster operations. No conditions or prerequisites mentioned, only a technical CRS conversion note.
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?
Without annotations, the description carries the burden; it explains the core operation and return structure but does not discuss side effects, reversibility, or permission requirements.
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 concise, front-loaded with the main action, and includes a clear parameter list without extraneous text.
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 presence of an output schema and many sibling tools, the description covers basics but lacks detail on what 'multi-part geometries' means or when exploding is necessary; adequate but not comprehensive.
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 compensates by explaining both parameters (gdf_path as file path, output_path as optional save path), adding meaning beyond type-only 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 tool splits multi-part geometries into single parts using a specific library method (geopandas.explode), distinguishing it from sibling tools like dissolve_gpd or merge_gpd.
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, nor any context about prerequisites or scenarios where it is inappropriate.
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 does not disclose side effects, file requirements, or permission needs beyond creating a weights object.
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 bullet points. No wasted words, front-loaded with main purpose.
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?
Adequate for a simple tool with output schema, but lacks prerequisite info (e.g., shapefile must exist) and error cases.
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?
Adds meaning beyond schema: explains contiguity options and id_field purpose. However, shapefile_path not described in text.
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?
Clearly states it creates a spatial weights from a shapefile using contiguity. Distinct from sibling tools like distance_band_weights or knn_weights.
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?
No explicit guidance on when to use contiguity vs other weight methods. Purpose is implied but no alternatives or exclusions mentioned.
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, so description carries burden. Indicates write operation but omits details like overwrite behavior, permissions, or format support beyond examples. Return value is described.
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?
Purpose is front-loaded in first sentence. Docstring format is clear but slightly verbose (3-line parameter section). Appropriate length for the context.
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?
Covers core purpose, parameters, and return value. Missing details like error handling, overwrite policy, or file path constraints. Output schema exists but not shown, so completeness is adequate but not strong.
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 coverage, description adds essential meaning: explains each parameter (gdf_path, output_path, driver) and provides OGR driver examples. This fully compensates for the schema's lack of description.
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?
Description clearly states action ('Export a GeoDataFrame to a file') with concrete format examples. Distinguishes from sibling read_file_gpd by implying 'write' vs 'read'.
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 on when to use this tool versus alternatives like save_results. Does not state prerequisites or when not to use (e.g., need existing file?).
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?
With no annotations, the description carries full burden. It mentions using shapely.normalize and output format but does not clarify if the operation is destructive or if it might modify the geometry in place. Basic transparency but lacks details on side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with three sentences covering purpose, parameter, and returns. Front-loaded with action verb and essential info, no waste.
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 low complexity and presence of an output schema, the description is mostly complete: it explains input, process, and output. Could mention error handling for invalid WKT, 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 only parameter 'geometry' is described as a WKT string, adding meaning beyond the schema's type-only definition. However, no additional constraints or examples are provided, though it is sufficient for a single-param tool.
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 normalizes geometry orientation/order using shapely.normalize, with specific input (WKT) and output (dict) details. It distinguishes itself from sibling tools like 'is_valid' or 'make_valid' by focusing on normalization.
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 on when to use this tool instead of alternatives. The description implies use for normalizing geometry order but does not mention when not to use or provide context about related tools.
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 carries full burden. It mentions using shapely.geometry.mapping and the return structure, but does not disclose error behavior, performance characteristics, or limitations. Adds some context but not deeply transparent.
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 concise, with a clear first sentence stating the purpose, followed by structured Args/Returns. No redundant information, every sentence earns its place.
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 that there is an output schema (context signal true), the description's mention of 'Dictionary with status, message, and GeoJSON representation' adds some completeness. However, it does not cover possible status values or error messages. For a simple tool with one parameter, it is adequate but could be more thorough.
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 has 0% description coverage, so the description must compensate. It specifies that the geometry parameter is a WKT string, adding meaning beyond the schema's 'string' type. This is helpful for correct invocation.
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 conversion from Shapely geometry (WKT) to GeoJSON. This is a specific verb-resource pair and distinguishes from sibling tool geojson_to_geometry which does the inverse.
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 converting geometry formats, but does not explicitly state when to use this tool versus alternatives like geojson_to_geometry or other geometry manipulation tools. No exclusions or context provided.
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 carry the full burden. It discloses that the tool saves to a destination path, but does not mention potential side effects (e.g., overwriting files), performance considerations, or supported CRS formats beyond EPSG example. For a simple operation it is adequate but not detailed.
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 short and to the point, with a clear initial sentence stating the purpose followed by a compact parameter list. No unnecessary words or repetition.
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 4 parameters, no annotations, and the presence of an output schema (which relieves the description from explaining return values), the description is fairly complete. It covers purpose, parameter explanations, and expected behavior. Missing minor details like error handling, but still informative.
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?
Schema coverage is 0%, so description must explain parameters. It does so effectively: source includes local path or HTTPS URL, target_crs shows example format, destination is local path, and resampling lists example methods. This adds significant clarity beyond the schema's type hints 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 reprojects a raster dataset to a new CRS and saves the result. It uses a specific verb ('Reproject') and resource ('raster dataset'), differentiating it from siblings like clip_raster_with_shapefile or resample_raster.
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 alternative transformation tools (e.g., resample_raster for change in resolution). It lacks explicit context for when-to-use, when-not-to-use, or suggestions for 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?
No annotations are provided, so description carries full burden. It describes the pipeline steps and mentions overwrite behavior, but lacks details on side effects like file permissions, error cases, or whether the original file is modified. The overwrite parameter is listed, but behavioral context is minimal.
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 concise with a clear pipeline statement followed by a parameter list. It is front-loaded with the overall purpose. No redundant sentences, but the parameter list is necessary given 10 parameters. Slightly longer than ideal but appropriate for complexity.
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 10 parameters, no annotations, and exists output schema, the description covers the pipeline, parameter details, and conditional requirements. It lacks guidance on method selection or error handling, but overall provides sufficient context for an agent to use the tool effectively.
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?
Schema description coverage is 0%, so description must compensate. It provides thorough explanations for all parameters, including conditional requirements (e.g., threshold required for distance_band, k for knn) and default values. This adds significant meaning beyond the schema's type and default info.
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 as a pipeline that reads a shapefile, builds spatial weights, optionally transforms, and saves to file. It distinguishes itself from sibling tools like 'build_and_transform_weights' (which likely doesn't save) and 'weights_from_shapefile' (which might only build).
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 explains what the tool does but does not explicitly state when to use it vs alternatives. It implies use when saving is needed, but no direct comparison or when-not guidance is given. Siblings include many weight-building tools, so explicit differentiation would help.
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?
Description mentions alignment handling and operation type but does not disclose error conditions, behavior with different extents, or return value. Since annotations are absent, description carries full burden but omits important behavioral details.
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?
Description is concise with clear bullet-point parameters. Every sentence adds value, no fluff or repetition.
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?
Covers purpose, parameters, and basic behavior. Lacks mention of return value or prerequisites like same CRS. Output schema exists but description could still note what the function returns.
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 meaning to all 5 parameters, including path, band index, operation type, and destination. However, it could include constraints like valid operation values or expected format for paths.
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?
Description clearly states 'Perform algebraic operations (addition or subtraction) on two raster bands' with a specific verb and resource. It distinguishes from siblings like compute_ndvi or concat_bands by focusing on algebraic operations.
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?
No explicit guidance on when to use this tool vs alternatives like weighted_band_sum or concat_bands. Usage is implied by the description but lacks exclusions or context for when another tool would be more 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?
No annotations are provided, so the description carries the full burden. It specifies that weights must match band count and sum to 1, but does not disclose whether destination overwrites existing files, performance implications, or error handling.
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: one sentence for purpose and three short parameter lines. No redundant information, front-loaded with the main action.
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 presence of an output schema (likely returning a file path), the description adequately covers purpose, parameters, and constraints. Lacks error conditions but acceptable for a basic computation tool.
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 adds meaning: weights must match bands and sum to 1, destination is output path. This compensates well for the missing 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?
Description clearly states 'Compute a weighted sum of all bands in a raster using specified weights.' This specific verb+resource distinguishes it from siblings like extract_band (extract single band) and concat_bands (concatenate bands).
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?
No explicit when-to-use or alternatives provided. The description implies usage for weighted band combinations, but does not guide the agent against using raster_algebra or other tools for similar tasks.
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 provided, so description bears burden. It mentions side effects (writing file) and return dict, but lacks details on overwrite behavior, error handling, or required CRS alignment.
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-line summary followed by Args block is clear and front-loaded. Each sentence adds value, though the Args section could be integrated for brevity.
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?
Covers purpose, parameters, and return format. Lacks edge-case behavior (e.g., file overwrite, dimension mismatch) but is adequate given the output schema exists for return details.
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's type and purpose (e.g., 'array: 2D or 3D list...', 'dtype: Optional data type...'). Adds significant 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 explicitly states 'Write a numpy array to a raster file using metadata from a reference raster', which is a clear verb+resource combination. It distinguishes from sibling raster tools (e.g., reclassify, reproject) by focusing on creating a new file from an array.
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?
No explicit when-to-use or when-not-to-use guidance. The purpose implies usage when you have an array and need a raster, but it does not mention alternatives or prerequisites like array shape matching reference raster.
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 carries full burden. It discloses automatic behaviors: reads files in sorted order, aligns mismatched CRS/resolution/dimensions. Misses potential failure modes or large data handling, but covers key automatic alignment adequately.
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?
Description is well-structured with main action, parameter list, and notes. Each sentence is informative without redundancy. Slight improvement possible by front-loading the core purpose more concisely.
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 (two parameters, automatic alignment) and existence of output schema, the description covers essential operation and constraints. Sibling tools like extract_band suggest alternatives, but the tool's behavior is well-explained for its scope.
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%, and the description provides clear parameter descriptions: folder_path as input raster directory, destination as output file. This adds meaning beyond the bare schema types, compensating 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 the tool concatenates multiple single-band rasters into one multi-band raster, using specific verbs and resource. It distinguishes from siblings like extract_band (opposite) and raster_algebra (mathematical operations).
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?
No explicit guidance on when to use this tool versus alternatives like extract_band or tile_raster. The description mentions automatic alignment handling, which implies benefit for mismatched rasters, but lacks direct comparisons or exclusions.
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?
Without annotations, the description discloses that it opens the raster, reads the DatasetReader.crs attribute, and returns two representations. It doesn't cover error cases or performance, but is adequate for a simple read operation.
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: first states purpose, second details implementation. No extraneous words, front-loaded with key information.
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 retrieval tool with a single parameter and an output schema, the description explains the operation and return types. It doesn't discuss supported raster formats or file accessibility, but is 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 single parameter path_or_url has no schema description, but the description clarifies acceptable values (local path or HTTPS URL). This adds meaningful context 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 tool retrieves the CRS of a raster, with specific verb and resource, and mentions it returns both PROJ.4 dict and WKT. It is distinct from sibling CRS tools like get_crs_info which are not raster-specific.
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 indicates it operates on raster datasets from local paths or URLs, but lacks explicit guidance on when to use this vs. other CRS tools, such as for non-raster sources or when only a CRS name is needed.
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 discloses read-only behavior and the supported input types (local path and HTTPS URL). While no annotations are provided, the description adequately communicates the tool's non-destructive nature. The presence of an output schema reduces the need to detail return values.
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 concise with only a few sentences, front-loading the key purpose and then clarifying input modes. No unnecessary information, and the structure is easy to scan.
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 (one parameter, output schema exists), the description covers the essential context: read-only mode, supported inputs, and the purpose. It is complete enough for an agent to select and invoke the tool, though it omits error handling or file format constraints.
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 for 'path_or_url' is 0%, but the description compensates by explaining that it is a file path or HTTPS URL, with examples. This adds significant semantic meaning beyond the bare 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 tool opens a raster dataset in read-only mode and returns metadata. It specifies two modes (local file path and HTTPS URL) and distinguishes itself from sibling tools like get_raster_crs or raster_band_statistics by being a general metadata retrieval tool.
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 provides context for when to use the tool (to get metadata from a raster), but does not explicitly exclude alternatives or advise against misuse. No mention of when to use this over more specific metadata tools such as get_raster_crs or raster_histogram.
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?
With no annotations provided, the description must disclose behavioral traits. It describes the saved output but does not mention whether files are overwritten, permission requirements, or error handling. The description is straightforward but lacks deeper 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, uses a clear bullet-point structure for parameters, and front-loads the purpose. Every sentence adds value without repetition.
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 description covers purpose, parameters, and returns. With an output schema present, it doesn't need to detail return structure. However, it could mention supported formats or error behavior for completeness.
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?
The description adds significant meaning beyond the input schema, which has 0% schema description coverage. It explains each parameter's purpose and semantics, including the default for folder and formats. The schema only defines types, so the description is essential.
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: 'Save any GIS-MCP result dict to files, only when the user requests.' It uses a specific verb (save) and resource (result dict), and distinguishes it from siblings since no other tool in the list is about saving arbitrary result dicts.
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 says 'only when the user requests', indicating the appropriate context for use. However, it does not explicitly state when not to use it or suggest alternatives, which keeps it from a 5.
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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