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ahmedvnabil

Open Emirates Intelligence

by ahmedvnabil

Server Quality Checklist

67%
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  • Latest release: v0.2.2

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: dashboard summary, market snapshot, search, source management (add, list, get, health), data retrieval (records, datasets, geo), and aggregation. No ambiguity between tools.

    Naming Consistency4/5

    Tools consistently use the 'uae_' prefix. Most tools follow a 'uae_source_<action>' pattern, though 'uae_dashboard_summary' and 'uae_market_snapshot' deviate slightly. Overall pattern is predictable.

    Tool Count5/5

    With 11 tools, the set is well-scoped for an open data intelligence server. Each tool serves a specific function without redundancy, and the count feels appropriate for the complexity of the domain.

    Completeness4/5

    The tool set covers core operations: search, catalog browsing, data retrieval, aggregation, and health checks. It lacks update/delete for sources, but for a read-heavy intelligence service, this is a minor gap.

  • Average 3.4/5 across 11 of 11 tools scored. Lowest: 2.4/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 33 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

  • Behavior2/5

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

    No annotations are provided, so the description carries full behavioral disclosure burden. It mentions 'source-backed' without explaining what that entails, and omits any information about destructive actions, auth requirements, or rate limits. The description is too vague to inform safe usage.

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

    Conciseness3/5

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

    The description is a single sentence with no redundant information, but it is so brief that it sacrifices necessary detail. Concise yet inadequate.

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

    Completeness2/5

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

    Despite having an output schema (reducing need to explain returns), the description fails to clarify the meaning of 'source-backed' or how parameters affect the snapshot. With no required parameters, usage is ambiguous. Sibling tool context is available but not leveraged.

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

    Parameters1/5

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

    Schema description coverage is 0%, meaning the description adds no meaning beyond the parameter names. The 'limit' and 'topic' parameters have defaults but no explanation of their purpose or allowed values, leaving the agent without enough context to use them correctly.

    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 builds a market snapshot with counts by emirate/area/product, using a specific verb 'Build' and resource. However, it does not differentiate from sibling tools like uae_dashboard_summary, which might have overlapping functionality.

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

    Usage Guidelines2/5

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

    No explicit guidance on when to use this tool versus alternatives. There are siblings like uae_dashboard_summary and uae_sources_list, but the description provides no context for choosing between them.

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

  • Behavior2/5

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

    With no annotations, the description bears full responsibility for behavioral disclosure. It only adds 'WRITE' and token requirement, but omits critical traits like idempotency, error behavior on duplicate IDs, or side effects on the registry.

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

    Conciseness3/5

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

    The description is very short (one sentence with a prefix), which is concise but lacks essential information. It is front-loaded but does not earn its place due to missing details.

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

    Completeness2/5

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

    Given the tool has 9 parameters, no schema descriptions, and no annotations, the description is insufficient. It does not explain return values (despite an output schema existing) nor provide enough context for correct invocation.

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

    Parameters1/5

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

    Schema description coverage is 0%, so the description must compensate. It does not mention any of the 9 parameters (e.g., id, name_en, name_ar, owner, base_url) nor their meaning or constraints. The agent receives no guidance on parameter usage.

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

    Purpose5/5

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

    The description clearly states the action ('Add'), the resource ('metadata-only source'), and the target ('local registry'). It effectively distinguishes from sibling tools like 'uae_source_get' (retrieve) and 'uae_sources_list' (list).

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

    Usage Guidelines2/5

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

    The description includes '[WRITE — requires token]' which hints at authentication requirements, but offers no guidance on when to use this tool versus alternatives like 'uae_source_get' or when not to use it. No context for prerequisites or exclusions.

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

  • Behavior2/5

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

    The description mentions 'live, timeout-bounded' but does not disclose whether the probe is read-only or has side effects, response behavior on success/failure, or any permissions needed. Since no annotations are provided, the description carries full burden and falls short.

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

    Conciseness4/5

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

    The description is a single sentence with no wasted words, but it could benefit from slightly more detail without becoming verbose.

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

    Completeness2/5

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

    Given the tool's simplicity (one parameter, no annotations), the description still lacks key details like return value or behavior. An output schema exists but is not provided, so the description should compensate for that gap, which it does not.

    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 sole parameter 'source_id' has no schema description (0% coverage). The description does not explain what the source ID represents, how to obtain it, or its format beyond the title 'Source Id'.

    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 ('run') and the resource ('live, timeout-bounded health probe for one source'), distinguishing it from siblings like uae_source_get or uae_source_records. However, it does not elaborate on what the health probe entails, leaving some ambiguity.

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

    Usage Guidelines2/5

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

    No guidance on when to use this tool versus alternatives like uae_source_get or uae_dashboard_summary. The description does not specify context, 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.

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It only says 'full metadata' without specifying what fields are included, idempotence, rate limits, or error conditions. Minimal behavioral disclosure.

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

    Conciseness3/5

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

    The description is a single short sentence with no waste, but it is under-specified. It could be more informative while remaining concise.

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

    Completeness3/5

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

    Given the presence of an output schema (which may document return values), the description covers the basic purpose. However, with no annotations and only one parameter, it could include more behavior context or usage hints.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate. While it mentions 'by id', it does not explain the source_id parameter's format, constraints, or examples beyond the schema's basic title.

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

    Purpose5/5

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

    The description clearly states the action 'Get', the resource 'full metadata for one source', and the method 'by id'. It distinguishes from sibling tools like uae_sources_list (which lists sources) and uae_source_add_metadata (which adds metadata).

    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 uae_sources_list for listing or uae_source_health for checking health. No when-not-to-use or prerequisite information is given.

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

  • Behavior3/5

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

    With no annotations, the description explains the basic behavior (grouping and reducing) but does not disclose whether it is read-only, any rate limits, or error conditions.

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

    Conciseness4/5

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

    The description is short (two sentences plus a code example) and front-loaded, efficiently conveying the core functionality without extra words.

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

    Completeness2/5

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

    Despite having an output schema, the tool has 8 parameters and aggregation logic, yet the description only covers group_by and vague aggregation types, leaving significant gaps for proper 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 coverage is 0%, and the description only explains the group_by parameter format. The other 7 parameters (top, limit, query, metric, dataset, source_id, value_field) are left completely unexplained.

    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 groups records and applies aggregation functions (count, sum, avg, min, max). It also distinguishes itself as a generalized form of uae_market_snapshot, providing 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 Guidelines3/5

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

    It mentions being a generalized form of uae_market_snapshot, which gives context on when to use it, but does not explicitly state when not to use it or provide alternatives.

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

  • Behavior2/5

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

    No annotations are provided, so the description must bear the full burden. It only says 'list the datasets' without disclosing behavior like pagination, error handling, rate limits, or authentication. The existence of output schema is not detailed. This is insufficient for transparency.

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

    Conciseness5/5

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

    The description is two sentences long, no fluff, front-loaded with purpose, and includes a practical usage hint. Every sentence earns its place.

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

    Completeness2/5

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

    Given the tool has 4 parameters and no annotations, the description is too brief. It lacks parameter documentation, behavioral details, and information about the output schema (which exists but is not described). Completeness is low.

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

    Parameters1/5

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

    Schema description coverage is 0%, yet the description adds no information about any of the four parameters (limit, query, offset, source_id) beyond what the schema provides. It fails to compensate for low coverage.

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

    Purpose5/5

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

    The description clearly states it lists datasets inside a multi-dataset portal (CKAN/OpenDataSoft/ArcGIS) and distinguishes that simple single-dataset sources return one entry. It also links to the sibling tool uae_source_records, providing clear purpose and differentiation.

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

    Usage Guidelines4/5

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

    The description gives context on when to use (for multi-dataset portals) and how to use the result (as dataset argument to uae_source_records). However, it does not explicitly state when not to use or provide alternatives, but the context is clear from sibling tools.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries full burden. It discloses the tool returns GeoJSON and works on coordinate-bearing sources, but does not address error handling, rate limits, or behavior when sources lack coordinates. This 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.

    Conciseness5/5

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

    The description is concise with two sentences and a line for parameter formats. It is front-loaded with the output format and purpose, with no wasted words.

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

    Completeness4/5

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

    Given the presence of an output schema (presumably GeoJSON), the description does not need to explain return values. It mentions the tool works on coordinate-bearing sources and provides parameter formats, but lacks details on error handling or non-spatial source behavior.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate. It only adds meaning for bbox and near parameters (format strings), leaving limit, query, dataset, and source_id undocumented. This is insufficient for 6 parameters.

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

    Purpose5/5

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

    The description clearly states the tool returns spatially-filtered records as GeoJSON, identifying the verb ('filtered'), resource ('records'), and output format. It distinguishes itself from siblings like uae_source_records by focusing on spatial queries.

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

    Usage Guidelines4/5

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

    The description provides context that the tool works on any source with coordinates (e.g., MOIAT industrial licenses) and gives format hints for bbox and near parameters. However, it does not explicitly state when not to use it or mention alternatives, so it lacks exclusions.

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

  • Behavior3/5

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

    With no annotations, the description carries full responsibility for behavioral disclosure. It states records are 'live, redacted' and that responses include 'provenance + a data-quality block in `meta`.' This indicates read-only behavior and some response structure. However, it does not mention authentication, rate limits, error handling, or side effects.

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

    Conciseness5/5

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

    The description is three sentences, each serving a distinct purpose: core action, dataset parameter use, and response content note. No redundant or irrelevant information. Front-loaded with the main action.

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

    Completeness4/5

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

    Given the tool has 5 parameters and an output schema, the description covers the essential purpose and the key parameter (dataset). It also notes the presence of provenance and data quality in responses. However, it could elaborate on the query parameter's semantics or pagination behavior.

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

    Parameters4/5

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

    Schema description coverage is 0%, so the description must add meaning. It explains `limit` (default 10) and `dataset` (an id from uae_source_datasets). It also implies `offset` and `query` are available but does not describe them. This adds value over the bare schema, but not all parameters are explained.

    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 'Fetch up to `limit` live, redacted, source-cited records from a source.' This specifies the verb (fetch), resource (source-cited records), and constraints (live, redacted, limit). It also mentions multi-dataset portals. However, it does not explicitly differentiate from sibling tools like uae_search or uae_source_aggregate.

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

    Usage Guidelines4/5

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

    The description provides guidance on when to use the `dataset` parameter: 'For multi-dataset portals pass `dataset` (an id from `uae_source_datasets`).' This implies that for single-dataset sources, dataset is not needed. However, it does not specify when to use this tool over alternatives like uae_search for cross-source queries or uae_source_get for a single record.

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

  • Behavior3/5

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

    No annotations provided, so description carries full burden. It discloses concurrency and caching behavior, adding value, but does not detail what 'health snapshot' entails, potential staleness, or authentication needs.

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

    Conciseness5/5

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

    Single sentence, no redundancy, front-loads key attributes (concurrent, cached, fast, never stalls). Every word earns its place.

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

    Completeness4/5

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

    Zero parameters and an output schema exists, so description covers essential context. Could mention what 'health' includes but output schema likely handles that.

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

    Parameters4/5

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

    No parameters; baseline score of 4 applies. Description need not add parameter info.

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

    Purpose5/5

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

    The description clearly states the tool provides a 'cached health snapshot across all sources' with performance characteristics, distinguishing it from sibling tools like uae_source_health (likely per-source) and uae_market_snapshot (different domain).

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

    Usage Guidelines4/5

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

    The description implies use when a fast, non-blocking overview is needed ('fast, never stalls'), but does not explicitly state when not to use or mention alternatives.

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

  • Behavior4/5

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

    With no annotations provided, the description discloses key behaviors: it searches the catalog, ranks results by relevance, and with deep=true searches live portals. It does not mention read-only nature explicitly, but for a search 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.

    Conciseness5/5

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

    The description is concise: two sentences cover purpose, ranking, deep mode, and use case. No redundant information; front-loaded with key functionality.

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

    Completeness4/5

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

    Given the tool's complexity and presence of an output schema, the description covers main behaviors (bilingual, federation, deep mode). It lacks details on pagination or error handling, but is sufficient for initial understanding.

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

    Parameters3/5

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

    Schema description coverage is 0%, so the description bears responsibility for parameter meanings. It explains the deep parameter and implies query accepts Arabic and English, but does not describe limit or further details for query. Partial compensation.

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

    Purpose5/5

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

    The description clearly states the tool performs federated bilingual search across a catalog, ranks official sources by relevance, and offers a deep mode for dataset discovery. This is specific and distinguishes it from sibling tools which focus on source management.

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

    Usage Guidelines4/5

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

    The description indicates the tool is ideal for dataset-discovery agents and explains the deep mode. While it does not explicitly state when not to use it or mention alternatives, the context implies its primary use case for general search and dataset discovery.

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

  • Behavior4/5

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

    With no annotations, the description bears full burden. It discloses the tool returns all sources and metadata, which is sufficient for a read-only list. However, it could mention that no parameters are needed and that it's safe to call.

    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, front-loaded sentence with no unnecessary words. It directly states the action and scope.

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

    Completeness4/5

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

    Given the tool's simplicity (no parameters, has output schema), the description adequately captures the functionality. It could mention that it returns all sources for context, but it does not need to elaborate further.

    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, simplifying the need for additional description. The schema coverage is 100%, so the description adds no further parameter details, which is acceptable.

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

    Purpose5/5

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

    Description clearly states the tool lists every registered official UAE open-data source with metadata, using specific verb 'list' and resource. It distinguishes from sibling tools like uae_source_get (which retrieves a single source).

    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 this tool is for obtaining an overview of all sources, but does not provide explicit guidance on when to use it versus alternatives like uae_source_get for individual sources. No exclusions or conditions are mentioned.

    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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