Israel Statistics MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, such as get_catalog_chapters for chapters and get_index_data for index data, but there is some overlap between get_all_indices and get_main_indices that could cause confusion. The descriptions help clarify, but an agent might need to infer the difference between 'all indices' and 'main indices'.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with 'get_' prefix, such as get_all_indices and get_index_data. There are no deviations in naming style, making the set predictable and easy to parse.
Tool Count5/5
With 9 tools, the count is well-scoped for a statistics API server, covering various aspects like indices, chapters, topics, and calculations. Each tool appears to serve a specific function without redundancy, fitting the domain appropriately.
Completeness4/5
The tool set provides comprehensive coverage for querying and calculating statistics, including data retrieval, catalog browsing, and calculations. A minor gap might be the lack of update or delete operations, but this is reasonable for a read-only statistics API, and agents can work around this limitation.
Average 2.9/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 9 of 9 community issues answered or closed in the last 6 months
- 37 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions retrieving data but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the response format looks like. For a tool with no annotations, this is a significant gap in 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 a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and front-loaded, though it could be slightly more informative to earn a higher score.
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, no output schema, and 5 parameters, the description is incomplete. It doesn't explain what 'main indices' or 'different bases' are, how results are structured, or any behavioral context. For a data retrieval tool with multiple parameters, this leaves significant gaps for an agent.
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 100%, so the schema already documents all 5 parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining 'different bases' in relation to parameters. Baseline 3 is appropriate as the schema does the heavy lifting.
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 states the tool 'Get main indices by different bases from Israel Statistics API' which provides a clear verb ('Get') and resource ('main indices'), but it's vague about what 'different bases' means and doesn't distinguish from siblings like 'get_all_indices' or 'get_main_indices_by_period'. The purpose is understandable but lacks specificity for sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_all_indices' or 'get_main_indices_by_period'. The description mentions 'by different bases' but doesn't explain what this entails or how it differs from other tools, leaving the agent without clear 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 provided, the description carries the full burden of behavioral disclosure. While it mentions 'optional chapter filtering', it doesn't describe important behavioral aspects: whether this is a read-only operation, what format the results come in, whether there are rate limits, authentication requirements, or what happens with large result sets beyond the pagination parameters documented in 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 a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for what it does convey, though it could be more front-loaded with critical usage information given the lack of annotations and sibling tool 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?
For a tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'indices' are in this context, what format the results will be in, or how this comprehensive tool relates to the many sibling tools. The agent would struggle to understand when and how to use this tool effectively without additional 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?
The schema has 100% description coverage, so all parameters are well-documented in the structured schema. The description adds minimal value beyond what's already in the schema - it mentions 'optional chapter filtering' which corresponds to the 'chapter' parameter, but doesn't provide additional semantic context beyond what the schema already explains thoroughly.
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 all indices') and resource ('from Israel Statistics API'), with additional context about 'different bases' and 'optional chapter filtering'. However, it doesn't explicitly differentiate this tool from its siblings like 'get_main_indices' or 'get_index_data', which appear related but have different purposes.
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. With multiple sibling tools like 'get_main_indices', 'get_main_indices_by_period', and 'get_index_data', there's no indication of how this comprehensive 'get all indices' tool differs from those more specific tools or when an agent should choose one over another.
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 'Get list' but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the response format looks like. The description is minimal and lacks essential operational 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, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
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, no output schema, and multiple sibling tools, the description is incomplete. It doesn't explain return values, differentiate from alternatives, or provide behavioral context, making it inadequate for an agent to fully understand when and how to use this tool effectively.
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 100%, so the schema fully documents all 4 parameters. The description adds no additional meaning about parameters beyond what's in the schema, meeting the baseline of 3 for high schema coverage without extra value.
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 'list of index chapters from Israel Statistics API', which is specific and understandable. However, it doesn't differentiate from sibling tools like 'get_all_indices' or 'get_main_indices', leaving ambiguity about what makes this tool unique for chapters versus other index-related tools.
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. With multiple sibling tools like 'get_all_indices', 'get_main_indices', and 'get_chapter_topics', there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.
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 behavioral disclosure but only states the basic action. It doesn't mention whether this is a read-only operation, potential rate limits, authentication needs, error handling, or the format of returned topics (e.g., list, structured data). For a tool with 5 parameters and no output schema, this leaves significant gaps in understanding its behavior.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a straightforward data retrieval tool, though its brevity contributes to gaps in other dimensions like guidelines and transparency.
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 (5 parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain what 'topics' are in this context, how results are structured, or handling of large datasets via pagination. Without annotations or output schema, the agent lacks critical context for effective use, especially compared to sibling tools in the same API domain.
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 description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all parameters. Since the schema fully documents parameters like 'chapterId' with enum mappings and 'page' for pagination, the description meets the baseline but doesn't enhance understanding of parameter usage or interactions.
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 topics') and resource ('for a specific chapter from Israel Statistics API'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'get_index_topics' or 'get_catalog_chapters', which likely retrieve similar statistical data, leaving some ambiguity about when to choose this specific tool.
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 'get_index_topics' or 'get_catalog_chapters'. It mentions the API source but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and parameters alone.
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 full burden for behavioral disclosure but offers minimal information. It states it 'calculates price linkage' but doesn't describe what the calculation does (e.g., inflation adjustment), how it works, what the output looks like, error conditions, rate limits, or authentication needs. For a calculation tool with 9 parameters, this leaves significant 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just one sentence: 'Calculate price linkage using Israel Statistics API index calculator.' It's front-loaded with the core purpose and wastes no words. Every element earns its place by establishing what the tool does and its data source 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 (9 parameters, calculation functionality) and lack of both annotations and output schema, the description is insufficiently complete. It doesn't explain what 'price linkage' means, how the calculation works, what format the result takes, or provide any examples. For a calculation tool with this many inputs, users need more context about the operation and expected outputs.
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 description adds no parameter-specific information beyond what's already in the input schema, which has 100% coverage with detailed descriptions for all 9 parameters. The baseline score of 3 reflects that the schema does all the heavy lifting - the description doesn't compensate but also doesn't detract from the comprehensive 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 the tool's purpose: 'Calculate price linkage using Israel Statistics API index calculator.' It specifies the verb ('calculate') and resource ('price linkage'), but doesn't differentiate from sibling tools like 'get_index_data' or 'get_subject_codes' which might provide related data. The purpose is specific but lacks 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. It mentions the Israel Statistics API context but doesn't explain when to choose this calculator over other sibling tools like 'get_index_data' for index information or 'get_all_indices' for listings. There's no mention of prerequisites, typical use cases, 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 carries full burden for behavioral disclosure. The description only states what the tool does at a high level without mentioning authentication requirements, rate limits, error handling, response structure, or whether this is a read-only operation. For a tool with 10 parameters and no annotations, this is insufficient.
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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a tool with comprehensive schema documentation, though it could benefit from additional context about when to use it versus sibling tools.
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 (10 parameters, no output schema, no annotations), the description is inadequate. It doesn't explain the return format, error conditions, authentication needs, or how this tool differs from similar sibling tools. The high parameter count and lack of output schema mean users need more guidance than what's provided.
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 100%, so the schema already fully documents all 10 parameters with detailed descriptions, examples, and constraints. The description adds no additional parameter information beyond what's in the schema, meeting the baseline expectation when schema coverage is complete.
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 ('index data from Israel Statistics API'), providing specific purpose. However, it doesn't differentiate this tool from sibling tools like get_all_indices, get_main_indices, or get_main_indices_by_period, which likely retrieve similar data with different scopes or filters.
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. With multiple sibling tools that likely retrieve index data (e.g., get_all_indices, get_main_indices, get_main_indices_by_period), there's no indication of how this tool differs in scope, filtering, or 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 provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't describe what 'index topics' are, the response format, pagination behavior, error conditions, or rate limits. The description only states what the tool does at a high level without operational 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?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a tool with well-documented parameters in the schema and gets straight to the point with zero wasted content.
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 7-parameter tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'index topics' are, how results are structured, or provide context about the Israel Statistics API domain. The agent would need to rely heavily on the parameter schema alone to understand this tool's functionality.
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 description coverage is 100%, providing comprehensive parameter documentation. The description adds no parameter-specific information beyond what's already in the schema, so it meets the baseline expectation without adding extra value. The description doesn't compensate for any gaps because there are none in 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 action ('Get') and resource ('index topics from Israel Statistics API'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_all_indices' or 'get_chapter_topics', but the specific focus on 'topics' provides some implicit 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 'get_all_indices' or 'get_chapter_topics'. It doesn't mention prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage from the tool name alone.
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 filtering by period but doesn't disclose important behavioral traits: what 'main indices' specifically refers to, whether this is a read-only operation, what the response format looks like, potential rate limits, authentication requirements, or error conditions. The description is minimal and lacks 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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for what it communicates and is front-loaded with the essential information.
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 tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'main indices' are, what data format to expect, how results are structured, or provide context about the Israel Statistics API. The agent would need to guess about the response format and the nature of the data being retrieved.
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 100%, so all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema descriptions. It mentions 'filtered by period' which aligns with startDate/endDate parameters, but provides no extra context about parameter usage or relationships.
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 ('main indices'), and specifies filtering by period from a specific API. It distinguishes from sibling 'get_main_indices' by adding the period filtering aspect. However, it doesn't explicitly differentiate from other siblings like 'get_all_indices' or 'get_index_data' which might also involve indices.
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. With multiple sibling tools related to indices (get_all_indices, get_main_indices, get_index_data, etc.), there's no indication of when period-filtered main indices are appropriate versus other index-related 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API source but fails to describe key behaviors such as pagination handling, rate limits, authentication needs, error responses, or what the output format looks like. This leaves significant gaps for an agent to understand how to interact with the tool effectively.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy for an agent to quickly grasp the intent.
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 7 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects like pagination, error handling, and response structure, which are crucial for proper tool invocation. The high schema coverage helps with parameters, but overall context for usage remains 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?
The schema description coverage is 100%, providing detailed documentation for all 7 parameters. The description adds minimal value beyond this, as it doesn't elaborate on parameter interactions or provide additional context not already in the schema. This meets the baseline score of 3 for high schema coverage.
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 resource ('index codes for a specific subject/topic'), specifying the source ('from Israel Statistics API'). It distinguishes this tool from siblings like 'get_all_indices' or 'get_main_indices' by focusing on subject-specific codes, though it doesn't explicitly contrast them.
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 when you need index codes for a particular subject, and the input schema hints at prerequisites (e.g., 'Get this ID first by calling getChapterTopics or getIndexTopics'). However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_all_indices' or 'get_index_data', leaving usage context somewhat inferred.
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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