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

With no annotations, description carries full burden. It discloses fallback to web app and return of both platform variants, but does not cover authentication, rate limits, or error handling for invalid coordinates.

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

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

Description is extremely concise at three sentences, with the most important information (purpose and fallback) front-loaded. Every sentence adds value.

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

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

Given 8 parameters and complexity, description adequately covers core functionality and return variants, but lacks details on coordinate constraints, parameter relationships, and output schema. An 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.

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

Schema description coverage is only 25%. Description adds minimal meaning beyond schema (e.g., mention of point and routing), but does not elaborate on coordinate parameters, origin/dest, or return format, which are needed given low schema coverage.

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

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

Description clearly states the tool generates deeplinks for showing a point or navigation, with specific verb 'generate' and resource 'deeplinks', distinguishing it from sibling tools that handle other mapping functions.

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

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

Description mentions fallback behavior and return variants, but lacks explicit guidance on when to use this tool versus alternatives, and does not specify 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.

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

No annotations exist, so the description carries the full burden. It does not disclose behavioral traits such as output format, API key requirements, or geographic limitations. However, detailed parameter descriptions in the schema provide some behavioral context (e.g., constraints for historical traffic mode).

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

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

The description is a single sentence of 14 words, front-loaded with the core action, and contains no superfluous information.

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

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

Given the tool's complexity (13 parameters, no output schema), the description does not explain what the tool returns (e.g., duration, distance, polyline). The parameter details are well-documented, but the overall completeness for an agent to use the tool effectively is moderate.

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

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

Schema description coverage is 69%, and the parameter descriptions in the schema are detailed (e.g., traffic_mode explains modes and constraints). The tool description adds minimal extra meaning beyond 'traffic modeling', so it meets the baseline without excelling.

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

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

The description clearly states the verb 'Calculate' and the resource 'route between two points', and specifies the distinguishing feature 'choosing how traffic is modeled'.

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

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

The description implies usage for route calculation but does not explicitly mention when to use this tool versus siblings like 'neshan_distance_matrix' or 'neshan_map_matching'. No when-not-to-use guidance is provided.

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

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

No annotations exist, so the description bears full burden for behavioral disclosure. It does not state that the tool is read-only, any required authentication, rate limits, or performance characteristics. The description only states the core function, leaving the agent uninformed about side effects or constraints.

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

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

The description is very short and front-loaded, but it is undersized for the tool's complexity. It could include more detail without being verbose, so it is not optimally sized.

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

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

The tool has no output schema, so the description should explain return values like distance and duration units or format. It fails to do so. Given the complexity of a distance matrix and the lack of structured output information, the description is incomplete.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions, which already specify lat/lng arrays. No extra context on formatting or constraints.

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

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

The description clearly states the tool computes travel distance and duration for every origin-destination pair. The verb 'compute' and resource 'distance and duration' are specific and distinguish this matrix operation from single-pair directions or other map tools.

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

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

No guidance is provided on when to use this tool versus alternatives like neshan_direction or when to avoid it (e.g., for large matrices). There is no mention of prerequisites, limitations, or context for use.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the endpoint does not resolve plaque numbers or POI names, which is key behavioral info. It also mentions cost (cheaper). While it doesn't cover all possible behaviors (e.g., rate limits, auth), it provides sufficient transparency for a simple geocoding tool.

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

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

Three sentences, no redundancy, front-loaded with the core purpose. Every sentence adds distinct value: purpose, cost/usage guidance, and limitation. No wasted words.

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

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

For a simple tool with one parameter and no output schema, the description is complete. It covers what the tool does, when to use it (and when not to), and its limitations. No additional information is necessary.

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

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

Schema coverage is 100%, with a single parameter 'address' described generically. The description adds meaning by specifying it handles Persian addresses and noting limitations (no plaque/POI resolution). This adds value beyond the schema's minimal description.

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

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

The description clearly states the core purpose: 'Convert a free-text Persian address into geographic coordinates.' It uses a specific verb ('convert') and resource ('address into coordinates'), and distinguishes from the sibling 'neshan_geocode_plus' by highlighting cost and address types.

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

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

Provides explicit guidance: 'Cheaper than neshan_geocode_plus — prefer this by default. Switch to neshan_geocode_plus only when the address includes a plaque (پلاک) number or refers to a point of interest by name.' This clearly states when to use this tool vs the alternative.

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

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

No annotations are provided, so the description must carry the full burden. It mentions the tool is more expensive and handles plaque/POI resolution, but lacks details about rate limits, returned data format, error behavior, or whether results are cached. This partial disclosure is adequate but not thorough.

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

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

The description is two focused sentences. The first sentence defines purpose and differentiation. The second provides usage guidance and accuracy tips. No redundant or extraneous text; every sentence earns its place.

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

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

Given 9 parameters, no output schema, and no annotations, the description covers the essential purpose, usage distinction, and parameter hints. However, it does not describe the return value format (e.g., coordinates, confidence) or error conditions, leaving some gaps. For a geocoding tool, this is mostly complete but could improve.

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

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

Schema description coverage is low (33%), so the description compensates by explaining the purpose of city, province, bias, and bounding box parameters ('improves accuracy'). However, it does not detail the exact format or constraints for bounding box coordinates (e.g., order of ne/sw or bias lat/lng). This adds meaningful context but could be more precise.

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

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

The description clearly states it geocodes addresses with plaque numbers or named points of interest, and explicitly distinguishes from sibling tool 'neshan_geocode' which cannot resolve those. This provides a specific verb, resource, and scope, achieving full differentiation.

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

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

The description gives explicit usage guidance: 'only use this when plaque/POI resolution is actually needed' and notes it is 'More expensive than neshan_geocode'. It also advises providing city, province, bias, and bounding box to improve accuracy, offering clear when/why/alternatives.

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

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

With no annotations, the description carries the full burden. It discloses that the call is expensive and only works for owner-claimed places. However, it omits details about error cases (invalid hash, unverified hash), idempotency, or rate limiting.

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

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

The description is two sentences long, each serving a purpose: stating the function and providing usage guidance. It is front-loaded with the main action and avoids repetition or fluff.

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

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

Given the tool's simplicity (1 param, no output schema), the description covers the core purpose, prerequisite (verified flag), and expense concern. It lists example output fields (address, category, hours, region) which partially compensates for the missing output schema. Could be improved by mentioning error handling or output format.

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

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

The schema covers 100% of parameters with a description linking hash to neshan_search results. The description adds the critical condition that it only works for verified places, providing context beyond the schema. For a single parameter, this is well-handled.

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

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

The description clearly states it fetches full details using a poiHash from neshan_search results. It specifies the resource (place details) and the action (fetch), and distinguishes from siblings like neshan_search which returns a list, as well as other tools like directions or geocoding.

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

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

The description explicitly advises when to use this tool: only for items with verified_details_available: true, and cautions against blanket use due to expense. It implies usage after neshan_search but does not explicitly name alternatives for non-verified places or bulk needs.

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

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

With no annotations, the description carries full burden. It discloses the return type (GeoJSON FeatureCollection), geometry control via 'polygon', metric property, and the ability to request both time and distance. It does not mention side effects or safety, but for a calculation tool, this is adequate.

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

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

The description is two sentences, front-loaded with the purpose, and every word is informative. No redundant or irrelevant information.

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

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

Given the tool's complexity (6 parameters, no output schema), the description covers key aspects: purpose, output format, and parameter interplay. It lacks details on coordinate system, error handling, or behavior of multiple features, but is largely sufficient for typical use.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining output structure (FeatureCollection with geometry and properties) and how parameters interplay (both time/distance can be requested simultaneously), which goes beyond the schema's per-parameter descriptions.

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

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

The description clearly states the purpose: 'Calculate the reachable area from a point within a given time or distance (isochrone).' It also describes the output format (GeoJSON FeatureCollection) and distinguishes from sibling tools by its specific functionality, though it does not explicitly contrast with them.

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

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

The description implies that at least one of 'time' or 'distance' must be provided (from schema), and that both can be used simultaneously. However, it does not provide explicit guidance on when to choose this tool over siblings, nor any exclusions or prerequisite conditions.

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

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

With no annotations, the description carries full behavioral burden. It only states 'snap' without detailing output (e.g., matched coordinates, segment IDs), error handling, or constraints (e.g., minimum points, sampling rate). Minimal transparency for a potentially complex operation.

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

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

The one-sentence description is concise but omits critical details. Every sentence should earn its place; while succinct, it sacrifices completeness for brevity.

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

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

For a tool with only one parameter and no output schema, the description should clarify return values or behavior. It fails to mention what the tool outputs (e.g., matched path points) or any important caveats, making it incomplete for an agent to rely on.

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

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

Schema coverage is 100% and the parameter description is clear. The tool description adds no extra meaning beyond what the schema provides, so baseline score of 3 is appropriate.

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

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

The description clearly states the tool's action (snapping GPS points onto the road network) and the resource (a sequence of GPS points). It distinguishes map matching from sibling tools like directions or geocoding, though it could specify the output type (e.g., matched points).

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

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

No guidance on when to use map matching versus alternatives like direction or TSP. The description does not mention typical use cases (e.g., noisy GPS data) or prerequisites (e.g., point format requirements), leaving the agent to infer context.

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

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

With no annotations, the description discloses key behaviors: file creation, auto-fit behavior, behavior without map_key (markers/routes still work). It lacks details on file size, performance, or cleanup, but covers the main behavioral traits adequately.

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

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

The description is concise (5 lines) and front-loaded with the main purpose. It could be slightly more structured with bullet points, but every sentence adds value and it avoids verbosity.

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

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

Given 9 parameters with thorough schema descriptions and no output schema, the description adequately explains the output (file_path to open in browser) and auto-fit behavior, making the tool's usage fully understandable.

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

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

Schema coverage is 100%, but the description adds context beyond the schema: explains auto-fit, file_path output, and map_key distinction from service key. This adds value, exceeding the baseline of 3.

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

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

The description states a specific verb ('Generate') and resource ('interactive Neshan map HTML file'), and clarifies it creates a page with markers and routes, distinguishing it from siblings like static maps or direction tools.

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

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

The description implies usage for interactive map creation but does not explicitly contrast with alternatives (e.g., static_map for images, deeplink for navigation), leaving the agent to infer when to choose this tool.

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

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

No annotations are provided, so description carries full burden. It only states the core function without disclosing behavioral traits like geographic coverage, precision, error handling, or return format.

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

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

A single, efficient sentence of 8 words that is front-loaded and contains no redundant information. Every word earns its place.

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

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

For a simple tool with two parameters and no output schema, the description is mostly adequate. However, it lacks context about geographic limits (e.g., Iran-only) and what a 'human-readable Persian address' entails.

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

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

Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond the schema, hence baseline score.

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

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

The description clearly states the tool converts coordinates (lat/lng) to a human-readable Persian address, using a specific verb and resource. It distinguishes from sibling 'neshan_geocode' which does forward geocoding.

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

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

The description implies when to use (when you have coordinates and need an address), but does not explicitly provide exclusions or alternatives. Context from sibling names helps, but no direct guidance.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It fails to mention that the tool uses a center point (lat, lng) or that optional bounding box parameters can be used to restrict the search area. There is no information about authentication, rate limits, or whether the search is limited to certain regions within Iran. The description is too vague.

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

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

The description is a single, efficient sentence that gets straight to the point. It is not verbose, but could be slightly more structured by breaking into two sentences or adding a bullet for key parameters. Still, it earns a high conciseness score.

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

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

For a tool with 8 parameters (3 required) and no output schema, the description is insufficient. It does not explain how the search center relates to the lat/lng parameters, nor does it mention the optional bounding box. The tool is part of a larger set of Neshan services, but the description provides no context for integration or typical use cases.

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

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

With schema description coverage at 50%, the description should add meaning for the undocumented parameters (ne_lat, ne_lng, sw_lat, sw_lng). It does not clarify that these define a bounding box for filtering results. The description merely restates 'near a location,' which does not compensate for the missing parameter descriptions. The required parameters (term, lat, lng) are covered in the schema, but the optional parameters need textual clarification.

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

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

The description clearly states the tool searches for places, addresses, and POIs near a location in Iran. It specifies the verb (Search), the resource (places, addresses, POIs), and the geographic context (Iran), making the purpose unambiguous. Though it doesn't explicitly distinguish from siblings like geocode or reverse_geocode, the general search intent 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.

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 neshan_geocode or neshan_reverse_geocode. There is no mention of prerequisites, limitations, or comparison with other tools, leaving the agent without decision support for tool selection.

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

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

No annotations are provided, so the description carries the full burden. It only states the tool renders a PNG image, without mentioning behavioral traits like destructive potential, authentication requirements, rate limits, or how output is returned (binary, URL, etc.).

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

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

The description is a single concise sentence that immediately states the tool's primary function. No extraneous content.

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

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

Given the tool has 7 parameters and no output schema or annotations, the description is too brief. It does not specify the return format (e.g., PNG binary, data URL), how to use the output, or any constraints (e.g., max image size beyond schema boundaries). This likely leaves an agent uncertain about result handling.

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

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

Schema description coverage is low (43%) with only zoom, marker, and map_type documented. The description adds that the map is centered on the given coordinate (lat, lng), but width, height, and other parameters lack any additional explanation. The description fails to compensate for the low schema coverage.

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

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

The description clearly states it renders a static map image in PNG format centered on a coordinate. This distinguishes it from interactive map tools (neshan_map_view) and route-based tools, but does not explicitly differentiate from the sibling neshan_static_map_arc.

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

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

The description provides no guidance on when to use this tool instead of alternatives. While the purpose is implied by the name and description, explicit context is missing.

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

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

No annotations exist, so the description must carry behavioral burden. It states the output is a PNG image, but does not disclose side effects, auth requirements, or how the image is returned.

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

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

The description is two concise sentences with zero waste, effectively front-loading the core purpose.

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

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

Given 11 parameters and no output schema, the description is insufficient. It omits return format, coordinate semantics, and differentiation from static_map siblings.

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

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

With schema coverage at 64%, the description adds no parameter-specific context. The required coordinate parameters (origin_lat, etc.) lack descriptions in both schema and tool description.

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

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

The description clearly states the tool renders a PNG with a curved arc between two points, and provides concrete use cases like visualising geographic connections.

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

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

The description explicitly says when to use it (visualising geographic connections without full routing), but does not contrast with sibling tools like neshan_static_map.

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

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

Without annotations, the description details the three outputs including chart color codes and map radius, but omits potential side effects, rate limits, or data freshness. Still informative.

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

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

The description is concise, uses bullet points for clarity, and front-loads the main purpose. Every sentence adds value.

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

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

Given no output schema, the description fully explains return components. Parameters are well-covered in schema. Tool complexity is adequately addressed.

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

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

Input schema already provides 100% coverage with descriptions for lat/lng. The description adds no further parameter context (e.g., coordinate system, precision), so baseline 3 is appropriate.

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

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

The description clearly states it analyzes historical traffic patterns and lists three specific outputs (kpi, chart, static_map), distinguishing it from sibling tools like static_map or direction.

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

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

The description does not explicitly state when to use this tool versus alternatives, nor does it provide when-not or prerequisite guidance. It is implied for traffic analysis around a point.

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

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

No annotations are provided, so the description carries full burden. It only states the high-level purpose without disclosing any behavioral traits such as constraints, assumptions, or side effects beyond what the name implies.

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

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

A single sentence of 10 words efficiently conveys the tool's purpose with no redundancy. It is front-loaded and easy to parse.

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

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

Given the absence of an output schema and annotations, the description lacks information about the return format (e.g., ordered list of indices or waypoints) and contextual details like usage scenarios or limitations.

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

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

Schema coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the parameter descriptions in the schema. All parameters have sufficient descriptions in the schema itself.

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

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

The description clearly states the verb 'Find' and the resource 'optimal visiting order', with the acronym 'TSP' specifying the problem type. It distinguishes this tool from siblings like neshan_direction (simple routing) and neshan_vrp_logistic (more complex vehicle routing).

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

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

No explicit guidance on when to use this tool versus alternatives like neshan_direction or neshan_vrp_logistic. The description does not state prerequisites 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.

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 such as whether the tool modifies data, requires authentication, or has rate limits. It only describes the function without side effects or constraints.

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

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

The description is concise (two sentences) and front-loaded with key purpose. However, the line break after 'optimization.' is unnecessary and slightly disrupts flow. Otherwise efficient.

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

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

With 11 parameters, nested objects, and no output schema, the description should explain return value structure or provide examples. It only mentions 'route results' but lacks detail on format, pagination, or error handling. Adequate but incomplete for a complex tool.

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

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

All parameters have descriptions in the schema (100% coverage). The description adds a high-level overview but does not deepen understanding beyond what the schema already provides. Baseline 3 is appropriate given the schema's completeness.

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

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

The description uses specific verbs ('Solve a Vehicle Routing Problem') and clearly states the resource (logistics/delivery optimization) and objective (minimizing distance/duration). It distinguishes the tool from siblings by focusing on multi-vehicle VRP, contrasting with TSP or simpler routing tools found in sibling list.

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

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

The description implies usage for logistics optimization but does not explicitly state when to use this tool vs. alternatives like `neshan_tsp` for single-vehicle problems. No guidance on when not to use or prerequisites beyond the schema.

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