Datagov Israel MCP

Overview Schema Related Servers Score Discussions

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, such as searching datastores vs. fetching data from APIs, but 'datastore_search' and 'resource_search' could be confused as both involve searching within datasets. The descriptions help clarify, but some overlap exists.
Naming Consistency4/5
Tools follow a consistent snake_case pattern with clear verb_noun structures like 'package_search' and 'organization_show', but 'fetch_data' deviates slightly with a less specific verb. Overall, the naming is predictable and readable.
Tool Count5/5
With 10 tools, the server is well-scoped for interacting with a data catalog, covering operations like listing, searching, and showing details for datasets, organizations, and resources. Each tool earns its place without being overwhelming.
Completeness4/5
The toolset provides good coverage for browsing and querying a CKAN-based data catalog, including CRUD-like operations for packages and organizations. Minor gaps exist, such as no tools for creating or updating datasets, but agents can work around this for read-only access.
Average 2.8/5 across 10 of 10 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

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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?
With no annotations provided, the description carries full burden but offers no behavioral information. It doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, or what the search returns. This leaves the agent with critical gaps in understanding how the tool behaves.
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 a single sentence that directly states the tool's action. There's no wasted verbiage or unnecessary elaboration, making it efficiently front-loaded.
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?
For a complex tool with 10 parameters, 0% schema coverage, no annotations, no output schema, and multiple similar sibling tools, the description is completely inadequate. It doesn't explain what the tool searches, how results are returned, when to use it, or what any parameters mean.
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%, meaning none of the 10 parameters have descriptions in the schema. The tool description provides no information about any parameters, not even explaining the required 'resource_id' or what the 'q' parameter searches. This fails to compensate for the complete lack of schema documentation.
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 'Search a datastore resource' states the basic action but is vague about what 'datastore resource' means and doesn't distinguish from siblings like 'resource_search' or 'package_search'. It provides minimal differentiation beyond the tool name itself.
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 is provided on when to use this tool versus alternatives like 'resource_search' or 'package_search' in the sibling list. The description offers no context about appropriate 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?
With no annotations provided, the description carries full burden but only states it fetches from a 'public API', missing key behavioral details such as authentication requirements, rate limits, error handling, or whether it's read-only. It doesn't disclose if this is a safe operation or has 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without unnecessary words. However, it's slightly under-specified given the tool's complexity, as it could benefit from a bit more detail to be fully 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?
Given no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover parameter meanings, behavioral traits, or return values, making it inadequate for a tool with 3 parameters and public API interactions. More context is needed for effective 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?
Schema description coverage is 0%, so the description must compensate but only mentions 'dataset name query', which loosely maps to 'dataset_name'. It doesn't explain the purpose of 'limit' and 'offset' parameters, their constraints, or how they affect the fetch operation, failing to add meaningful semantics beyond the bare schema.
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 action ('fetch data') and target ('from public API'), but is vague about what 'data' means and doesn't distinguish from siblings like 'datastore_search' or 'package_search'. It mentions 'dataset name query' which provides some context but lacks specificity about the type of data or API.
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 'datastore_search' or 'package_search' is provided. The description implies usage for fetching data with a dataset name, but doesn't specify prerequisites, exclusions, or comparative contexts with sibling 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 carries the full burden of behavioral disclosure. It mentions 'matching query terms,' implying a search operation, but doesn't disclose key traits like whether it's read-only, requires authentication, has rate limits, or what the output format is. For a search tool with 6 parameters and 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence: 'Find packages (datasets) matching query terms.' It's front-loaded and wastes no words, making it easy to parse quickly. Every word contributes to the core purpose, earning its place efficiently.
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 (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the search behavior, result format, or how parameters interact, leaving the agent with insufficient context to use the tool effectively. For a search tool with multiple parameters, more detail is needed to be 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?
The schema description coverage is 0%, meaning none of the 6 parameters have descriptions in the schema. The tool description only mentions 'query terms,' which loosely relates to the 'q' parameter but doesn't explain the purpose of other parameters like 'fq', 'sort', 'rows', 'start', or 'include_private'. It adds minimal value beyond the schema, failing to compensate for the low coverage.
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's purpose as 'Find packages (datasets) matching query terms,' which includes a verb ('Find') and resource ('packages/datasets'), making it clear what the tool does. However, it doesn't differentiate from siblings like 'package_list' or 'resource_search,' leaving ambiguity about when to use this versus other search/list tools. The purpose is clear 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. With siblings like 'package_list' (likely lists all packages) and 'resource_search' (likely searches resources within packages), there's no indication of this tool's specific context, such as whether it's for general package searches or has unique filtering capabilities. No explicit when/when-not instructions 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 provided, the description carries full burden for behavioral disclosure. While 'Find' implies a read-only operation, it doesn't specify authentication requirements, rate limits, pagination behavior (beyond what parameters suggest), error conditions, or what constitutes a 'resource' in this system. The description provides minimal behavioral context for a search 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 extremely concise - a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it front-loaded and efficient despite its content limitations.
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 search tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'resources' are, how results are returned, what fields can be searched, or provide any context about the search domain. The agent would struggle to use this tool effectively based on the provided information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for all 4 parameters, the description provides no additional semantic information about what 'query', 'order_by', 'offset', or 'limit' mean in this context. It doesn't explain query syntax, valid ordering fields, or how pagination works. The description fails to compensate for the complete lack of parameter documentation in the schema.
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 'Find resources based on their field values' states a general purpose (searching resources) but lacks specificity about what 'resources' refers to in this context. It doesn't distinguish this tool from sibling tools like 'datastore_search', 'package_search', or 'fetch_data', leaving ambiguity about what type of resources are being searched.
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 about when to use this tool versus alternatives like 'datastore_search' or 'package_search'. The description doesn't mention any prerequisites, constraints, or appropriate contexts for using this search tool, leaving the agent to guess based on tool names 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 the full burden of behavioral disclosure. It states this is a read operation ('Get metadata'), which implies it's non-destructive, but doesn't mention authentication needs, rate limits, error conditions, or what metadata is returned. For a tool with zero annotation coverage, 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 front-loads the key information ('Get metadata about one specific package'). There is no wasted verbiage, making it easy to parse quickly.
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 no annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't cover what metadata is returned, error handling, or usage context relative to siblings. Given the complexity of interacting with packages/datasets, more detail would help an agent 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?
The description implies a single parameter (the package ID) by mentioning 'one specific package', but doesn't explain what format the ID should be (e.g., string, numeric) or where to find it. With 0% schema description coverage, the schema only documents the parameter name and type, so the description adds minimal value beyond what's already in the structured data.
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 metadata') and target resource ('one specific package (dataset)'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'package_list' or 'package_search', which likely retrieve multiple packages or search across packages rather than a single specific one.
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 'package_list' (for listing multiple packages) or 'package_search' (for searching packages). It mentions 'one specific package' but doesn't clarify prerequisites (e.g., needing a package ID) or exclusions (e.g., not for bulk 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 are provided, so the description carries full burden for behavioral disclosure. It states this is a read operation ('Get details'), implying it's likely safe and non-destructive, but doesn't address potential authentication needs, rate limits, error conditions, or what 'details' entail (e.g., format, depth). For a tool with zero annotation coverage, this leaves 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 a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.
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 low schema coverage, the description is incomplete. It doesn't explain what 'details' include, potential return formats, error handling, or prerequisites. For a tool that retrieves organizational data, this lacks necessary context for effective use.
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 1 parameter with 0% description coverage, so the description must compensate. It implies the 'id' parameter is used to specify which organization to retrieve details for, adding semantic meaning beyond the bare schema. However, it doesn't clarify the format or constraints of the 'id' (e.g., numeric, string pattern), leaving some ambiguity.
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 ('details of a specific organization'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'organization_list' or 'status_show' that might also retrieve organizational information, which prevents a perfect score.
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 siblings like 'organization_list' (likely listing multiple organizations) and 'status_show' (possibly showing status rather than details), there's no indication of when this specific retrieval is appropriate, leaving usage unclear.
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 of behavioral disclosure. It states it 'Get[s] a list', implying a read operation, but doesn't specify if it's paginated, rate-limited, requires permissions, or what the return format is. This leaves significant gaps for an agent to understand how to handle 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, clear sentence that directly states the tool's function without any wasted words. It's front-loaded with the key action and resource, making it highly efficient and easy to parse.
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 output schema, the description is incomplete for a tool that likely returns a list of IDs. It doesn't explain the return format (e.g., JSON array, pagination), any limitations (e.g., max results), or error handling. For a read operation with no structured support, more context is needed to ensure reliable use.
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 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't add parameter details, and the baseline for this scenario is 4, as it avoids redundancy and focuses on the tool's purpose without unnecessary elaboration.
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 ('list of all package IDs (datasets)'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'package_search' or 'package_show', which would require more specific scope or usage 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?
The description provides no guidance on when to use this tool versus alternatives like 'package_search' or 'package_show'. It lacks context about prerequisites, such as whether authentication is needed, or any exclusions or limitations in its 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a read operation ('Get'), implying non-destructive behavior, but lacks details on permissions, rate limits, or response format. This leaves gaps in understanding how the tool behaves in practice.
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 wasted words, making it easy to parse and understand quickly. It's appropriately sized for a simple tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks behavioral details and usage context, making it incomplete for fully informed use without additional inference.
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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add param info, but that's acceptable here, earning a baseline score as it doesn't detract from the schema's completeness.
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 the resource ('list of licenses available for datasets on the site'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'package_list' or 'organization_list', which might also list entities, so it misses full 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 doesn't mention context, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone, which is insufficient for optimal 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 are provided, so the description carries full burden for behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify whether this returns all organizations at once (vs. paginated), what format the names are in, or if there are any access restrictions. For a tool with zero annotation coverage, 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 states exactly what the tool does without any wasted words. It's appropriately sized for a simple listing tool and front-loads the core functionality immediately.
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 zero-parameter listing tool with no output schema, the description is minimally adequate. It states what the tool returns but doesn't cover format, pagination, or access considerations. Given the simplicity (no parameters, no complex annotations), it meets basic requirements but lacks depth that would help an agent use it effectively.
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 tool has zero parameters with 100% schema description coverage, so the schema already fully documents the lack of inputs. The description adds no parameter information, which is appropriate here since there are no parameters to explain. A baseline of 4 is correct for zero-parameter tools where the schema handles everything.
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 ('names of all organizations'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'organization_show' or 'datastore_search' that might also retrieve organization data, preventing a perfect score.
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 siblings like 'organization_show' (likely for specific organizations) and 'datastore_search' (potentially for filtered searches), there's no indication of when this broad listing tool is appropriate versus more targeted options.
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 states what is returned but doesn't mention performance characteristics, error conditions, authentication requirements, or whether this is a read-only operation (though implied by 'Get').
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 function without any fluff. It's front-loaded with the core action and resources, making it immediately understandable.
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 zero-parameter read operation with no output schema, the description adequately covers what the tool returns. However, without annotations or output schema, it lacks details about response format, error handling, or system dependencies that would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema coverage, so the schema already fully documents the lack of inputs. The description appropriately doesn't add parameter information, maintaining focus on the tool's purpose without unnecessary detail.
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 specific action ('Get') and the resources returned ('CKAN version and a list of installed extensions'). It distinguishes itself from siblings like 'package_list' or 'organization_list' by focusing on system metadata rather than data content.
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. While the purpose is clear, there's no mention of use cases, prerequisites, or how it differs from other system-related tools (none listed in siblings).
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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