azure-utils-mcp

Server Quality Checklist

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

Latest release: v0.2.0
Disambiguation5/5
Tools are clearly disambiguated by service prefix (authorization_, cosmosdb_, servicebus_) and distinct verbs. Even similar operations like peek across different targets (queue, subscription, DLQ) are precisely named, leaving no ambiguity.
Naming Consistency5/5
All tools follow a consistent pattern: service_verb_noun (e.g., cosmosdb_list_databases, servicebus_send_batch). The naming is uniform across all three services, making it predictable for agents.
Tool Count3/5
31 tools is high but justifiable given coverage of three distinct Azure services. However, the PIM portion only has 2 tools, which feels thin compared to the 11 for Cosmos DB and 18 for Service Bus, indicating slight over-scoping on the latter.
Completeness4/5
Cosmos DB covers essential operations (list, read, write, query, delete) with container info and count; Service Bus covers listing, peeking (with file variants for large payloads), purging, requeueing, and sending. Missing: ability to consume/receive messages from Service Bus (only peek), but that may be by design to avoid destructive operations. Minor gap but overall solid.
Average 4.1/5 across 31 of 31 tools scored. Lowest: 3/5.
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 status not available
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses non-destructive peeking, file writing, metadata return, and auth mechanism (connection_string_env_var or DefaultAzureCredential). Missing details on whether output_file is overwritten or appended, and no mention of max_count behavior or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with three short paragraphs, front-loaded with purpose. No redundant information, though some details could be integrated more efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers core functionality and auth, but lacks details on parameter behaviors (e.g., session_id, max_count) and output_file handling. Output schema exists, which partially compensates, but the description could still be more thorough.
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?
Only one parameter (connection_string_env_var) is explained in the description. The other six parameters (namespace, topic, subscription, output_file, max_count, session_id) have no description, so the description adds minimal value beyond the schema for most parameters.
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 peeks at messages from a Service Bus topic subscription and saves bodies to a file, using specific verb and resource. However, it does not explicitly differentiate from sibling tools like servicebus_peek_subscription_messages, though the file-saving aspect is evident.
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. The description implies use for saving message bodies to a file but does not mention when not to use it or provide comparative context with related peek 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 present, so the description must cover behavioral traits. It correctly states non-destructiveness and output details (bodies to file, metadata returned). It also explains authentication logic. Missing details on file overwrite behavior, error handling, and performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two clear paragraphs. It uses line breaks for readability. The first sentence effectively states the core purpose. It could be more structured (e.g., listing parameters) but is efficient with no redundant information.
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 complexity (5 params, output schema exists) and no annotations, the description covers the main behavior and authentication but misses edge cases like file overwrite behavior, error conditions, and a full explanation of max_count. It is adequate but has gaps.
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%. The description only explains the connection_string_env_var parameter (fallback auth). Other parameters (namespace, queue, output_file, max_count) are not described beyond their names and one mention of output_file. This does not sufficiently compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool peeks at dead letter queue messages and saves bodies to a file, specifying the verb 'peek', resource 'dead letter queue', and output destination. It distinguishes from siblings like servicebus_peek_dlq by mentioning file output and metadata-only context, but could explicitly differentiate from similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context: non-destructive operation, file output, and authentication fallback. However, it does not explicitly state when to use this tool over siblings like servicebus_peek_dlq or servicebus_purge_dlq, nor does it offer guidance on the max_count parameter.
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 covers important behaviors: account name normalization and authentication fallback. However, it does not explicitly state that the operation is read-only or disclose any other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, starting with the core purpose. It could be better structured with bullet points for readability, but it is not verbose.
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 (2 params, 1 required) and the presence of an output schema, the description adequately covers account handling and auth. It misses explicit usage guidance but is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema lacks descriptions (0% coverage), but the description compensates fully by explaining the account parameter's input flexibility and the key_env_var's default and authentication mechanism. This adds significant meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it lists all databases in an Azure Cosmos DB account, which is a specific verb+resource. It distinguishes from siblings like cosmosdb_list_accounts and cosmosdb_list_containers by targeting databases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives. It lacks context for when to choose list_databases over list_accounts or list_containers.
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?
Discloses auth method (key_env_var) and required 'id' field. No annotations provided, so description carries full burden. Missing critical detail about how partition key is determined (only mentioned in text but not in schema) and potential 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?
Short, well-structured description with clear front-loading and bulleted details. Could be slightly more concise but effectively communicates key points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main behavior and return type, with output schema present. However, missing partition key handling explanation and error scenarios make it incomplete for a write operation with complex input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. Explains 'id' field requirement and key_env_var behavior, but does not elaborate on account, database, container, or the item structure beyond 'id'. Partial semantic support.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Insert or replace an item in a Cosmos DB container' with specific verb and resource. Explains upsert semantics and distinguishes from siblings like cosmosdb_read_item and cosmosdb_delete_item.
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?
Clearly describes the upsert behavior and when it creates vs replaces. However, lacks explicit guidance on when to choose this over alternative tools like cosmosdb_query_items or cosmosdb_read_item.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It explains the scheduled_enqueue_time format and auth selection logic, but omits details on success/failure responses, rate limits, idempotency, or error handling. The tool likely has read-only or destructive aspects, but these are not addressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using short paragraphs to convey key points. It front-loads the main purpose and then covers additional details. A more structured format (e.g., bullet points for parameters) could improve readability, but current length is appropriate.
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 sends messages and has an output schema (presumably returning status), the description covers auth, scheduling, and basic namespace/queue identification. Missing details include expected behavior on failure, message size limits, retries, and return value semantics. Adequate but not comprehensive for a complex Azure resource.
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 input schema has 8 parameters with 0% description coverage. The description adds value by explaining scheduled_enqueue_time (ISO 8601 format), connection_string_env_var (auth behavior), and namespace format. However, session_id, correlation_id, and application_properties receive no explanation, leaving gaps for an agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies it sends a single message to an Azure Service Bus queue or topic, using a specific verb and resource. It distinguishes itself from siblings like servicebus_send_batch (multiple messages) and various peek/purge tools, making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides practical context: namespace can be short or FQDN, and auth method is determined by the presence of a connection string environment variable or DefaultAzureCredential. It does not explicitly contrast with sibling tools like servicebus_send_batch, but the single vs. batch distinction is implicit from the name and description.
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 carries full burden. It clearly warns about destructive, unrecoverable deletion and explains authentication behavior (key-based vs DefaultAzureCredential). However, it omits details about success/failure responses 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 concise, front-loaded with the primary action, followed by a warning, required fields, and authentication detail. Every sentence adds essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description leaves three parameters (account, database, container) unexplained. It also does not mention required permissions or account name format, which could cause ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains item_id, partition_key, and key_env_var, but does not describe account, database, or container parameters, though these are somewhat self-explanatory from context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Delete an item from a Cosmos DB container', which is a specific verb-resource pair. It clearly differentiates from sibling tools like cosmosdb_read_item and cosmosdb_upsert_item by emphasizing deletion.
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 highlights that the operation is destructive and irreversible, implying caution, but does not provide explicit guidance on when to use this tool versus alternatives like soft deletion or other Cosmos DB tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description details message preservation (body, session_id, correlation_id, application_properties), the removal from DLQ after requeue, the stop condition when max_messages is exceeded, and authentication behavior based on connection_string_env_var. Since no annotations are provided, the description carries the full burden and does so thoroughly.
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 two concise paragraphs: first explaining the action and key behaviors, second focusing on the authentication parameter. No superfluous text, though the second paragraph could be integrated more seamlessly. It is front-loaded with the core purpose.
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 an output schema being present, the description does not mention what the tool returns (e.g., count of requeued messages, success/failure). It also does not describe all parameters thoroughly; only one of five parameters receives detailed explanation. For a tool with 5 parameters and no schema descriptions, this is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must add meaning. It explains connection_string_env_var and its role in authentication, and implicitly clarifies max_messages via the stop condition. However, namespace, topic, and subscription are not explicitly described beyond their names, leaving potential ambiguity for agents unfamiliar with Azure Service Bus.
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 'Move messages from a topic subscription's dead letter queue back to the topic', specifying the source, destination, and action. It distinguishes from sibling tools like servicebus_requeue_dlq (operates on queue DLQ) and servicebus_purge_subscription_dlq (removes without requeue).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like servicebus_requeue_dlq or peek-then-requeue flows. The stop condition based on max_messages is mentioned but not in a decision-making context. Prerequisites or when-not-to-use are absent.
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 return format (JSON with 'count' field) and auth behavior (key-based vs DefaultAzureCredential). However, it does not cover rate limits, permissions needed, or potential errors.
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 about 6 lines, well-structured with examples. Every sentence adds value: purpose, filter usage, auth. 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 5 parameters and an output schema, the description adequately covers input parameters with examples, return format, and auth. It mentions the output schema return field. Missing details on error cases or performance, but overall complete for a count tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning: explains the 'where' parameter with examples and syntax, and the 'key_env_var' parameter with default and auth implications. The required params (account, database, container) are self-explanatory given the tool name, but the description could offer more 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 'Count items in a Cosmos DB container, with an optional filter.' It uses a specific verb (count) and resource (items in Cosmos DB container), and differentiates from siblings like cosmosdb_query_items (which returns items, not just count) and cosmosdb_get_container_info (which returns container metadata).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the optional filter and mentions auth mechanism, but does not explicitly compare to alternatives like query_items. Usage is implied for counting rather than fetching items, but no direct exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It explains that the tool returns metadata and describes authentication fallback (key_env_var or DefaultAzureCredential), but does not explicitly state that the operation is read-only, idempotent, or free of side effects. It also does not mention error conditions or rate limits.
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: first states purpose, second lists returns, third explains account and auth. It is concise, front-loaded, and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and an output schema, the description covers purpose, return fields, and auth. It does not mention error conditions or prerequisites (e.g., container must exist). However, the output schema presumably documents return structure, reducing the need for that detail. Overall, it is mostly complete for a read-only metadata tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains that 'account' can be a short name or full endpoint URL and describes the 'key_env_var' parameter's role and default. The other parameters (database, container) are straightforward and need no additional explanation. This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves metadata for a Cosmos DB container and lists specific return fields (partition key path, indexing policy, etc.), distinguishing it from sibling tools like cosmosdb_list_containers which list containers rather than return detailed metadata.
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 container metadata is needed and explains authentication behavior, but does not explicitly state when to use this tool versus alternatives like cosmosdb_list_containers or cosmosdb_query_items. No 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 that the tool returns the full item document as JSON and explains key-based vs. DefaultAzureCredential auth. This adds useful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) with no redundant information. Key points are front-loaded: purpose, requirements, and auth behavior.
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, the description adequately covers required parameters, auth, and return type. It lacks explicit error handling or 'not found' behavior, but remains sufficient for typical use.
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%. The description adds meaning for item_id, partition_key, and key_env_var, but does not describe account, database, or container, which are self-explanatory but still lacking explicit documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Read a single item from a Cosmos DB container by ID and partition key,' which is a specific verb and resource. It clearly distinguishes from sibling tools like cosmosdb_delete_item and cosmosdb_query_items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that both item_id and partition_key are required and why, and discusses auth behavior via key_env_var. However, it does not explicitly state when to use this tool versus alternatives like cosmosdb_query_items for multiple items.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes activation outcomes and statuses, but does not disclose side effects, idempotency, or required permissions. The behavior is partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with the purpose front-loaded. Each sentence adds value, covering parameter details and return statuses without unnecessary fluff.
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 the presence of an output schema (not shown but indicated), the description covers parameter semantics and return statuses adequately. It could mention error handling or side effects, but is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant meaning: role and scope must be exact from list_eligible, justification is required by Azure PIM, duration is ISO 8601 with default and cap. This compensates well for the schema's lack of 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 tool activates an eligible Azure PIM role assignment, specifying the verb 'activate' and the resource 'Azure PIM role assignment'. It distinguishes itself from the sibling 'authorization_list_eligible_roles' by focusing on activation.
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 explicitly ties parameter values to the output of 'authorization_list_eligible_roles', provides context for justification (required by Azure PIM), and explains duration defaults and caps. It lacks explicit when-not guidance but the prerequisite is clear.
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?
No annotations are provided, so the description carries the full burden. It discloses that the result is a sorted JSON array, and describes authentication behavior based on environment variable presence. This is useful beyond the schema, though it doesn't explicitly state that the operation is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three short paragraphs. The first sentence clearly states the purpose, followed by the return format and authentication details. Every sentence adds value, though it could be slightly more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description adequately covers parameter semantics, authentication, and return type. It doesn't need to explain return values further. The description is complete for a list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds critical meaning: account can be a short name or full endpoint, database is the database name, and key_env_var has a default and explains the authentication logic. This compensates well for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all containers in a Cosmos DB database, using a specific verb and resource. It also notes the sorted JSON array return, differentiating it from sibling tools like cosmosdb_get_container_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains authentication methods (key vs DefaultAzureCredential) but does not explicitly state when to use this tool versus other Cosmos DB tools like cosmosdb_list_accounts or cosmosdb_query_items. Usage context is implied but no exclusions or alternatives are given.
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 carries full burden. It discloses destructiveness and the stopping behavior when max_messages is exceeded. It also explains authentication method. Missing details on required permissions or failure scenarios, but adequate for a destructive tool.
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 at 5 lines, with no wasted words. The destructive warning is front-loaded. Each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the destructive nature and 5 parameters, the description covers core purpose and behavior, but lacks explanation for required parameters (namespace, topic, subscription) and does not mention output schema. Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It explains connection_string_env_var's role in authentication, but does not add meaning for namespace, topic, subscription, or max_messages beyond their names. Partial compensation, but gaps remain.
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: deleting all messages from the dead letter queue for a topic subscription. It uses specific verb 'delete all messages' and resource identification. Among sibling tools, it distinguishes from similar operations like peek or requeue.
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 warns that the operation is destructive and messages cannot be recovered, and explains behavior when max_messages is exceeded. However, it does not explicitly contrast with alternative tools like peek or requeue, nor specify when not to use this tool.
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 batch send behavior, message structure, and auth method. However, it does not mention failure handling, partial success, rate limits, or atomicity, which are relevant for a batch operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively short and front-loads the purpose. Bullet points for message fields are clear. Could be slightly more concise, but no wasted information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are covered. The description covers sending, message format, and auth. It lacks details on error behavior and transactional guarantees, which are somewhat important for batch operations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning for 'messages' (lists expected fields) and 'connection_string_env_var' (explains auth). It does not elaborate on 'namespace' or 'queue', but their purpose is clear from context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it sends multiple messages to an Azure Service Bus queue or topic in a single batch. It distinguishes from siblings like servicebus_send_message and other peek/purge tools by highlighting batch capability.
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?
It mentions 'useful for seeding test data' and implicitly differentiates from servicebus_send_message by explaining batch behavior. It does not explicitly provide when-not-to-use or alternative tools, but the context of sibling tools helps.
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?
No annotations provided, but the description discloses behavioral traits: max_items capped at 1000, cross-partition queries enabled automatically, and key_env_var-based authentication behavior. These add value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: purpose first, then examples, constraints, alternatives, and auth details. No unnecessary 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?
With an output schema present, the description does not need to explain return values. It covers purpose, usage, constraints, auth, and alternatives. Lacks error handling or performance notes, but adequate for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains query syntax and constraints for max_items and key_env_var, but account, database, container are not described beyond their names. Adds meaning for 3 of 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 'Run a SQL query against a Cosmos DB container and return results.' It includes SQL syntax examples and distinguishes from the sibling tool cosmosdb_query_items_to_file, which is for large result sets.
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?
It explicitly advises using cosmosdb_query_items_to_file for large results. It also mentions the max_items cap and cross-partition query behavior, but does not provide explicit when-not-to-use scenarios beyond that.
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?
In absence of annotations, description discloses key behaviors: file output, only item count returned, max_items cap at 1000, auth variation. Lacks detail on file overwrite 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?
Concise and well-structured: main action first, then details on output, limitations, and auth. No unnecessary sentences.
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 no annotations but output schema exists, description covers core functionality and usage scenario well. Some parameter details missing, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%; description adds meaning for key_env_var and max_items (cap at 1000) but does not explain standard params like account, database, container, query.
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 runs a SQL query and saves results to a file, distinguishing it from sibling tools like cosmosdb_query_items by noting the file output and context window avoidance.
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?
Explicitly says to use when result set may be large, and explains auth method selection. Could be more explicit about when not to use, but guidance is clear.
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?
No annotations are provided, so the description carries the full burden. It discloses that the operation is read-only, non-destructive, returns message bodies and metadata, caps max_count at 100, and details session handling and authentication. It does not cover error behavior or empty queue scenarios.
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 and well-structured, with a clear opening statement followed by important details in separate sentences. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no annotations, and an output schema, the description covers core functionality, constraints, and alternatives. It could include notes on performance or rate limits but is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It details connection_string_env_var, session_id, and mentions max_count cap, but does not explain the required parameters 'namespace' and 'queue', which are ambiguous for new users.
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 is for non-destructively peeking messages in a Service Bus queue. It distinguishes from the sibling tool for large message bodies (peek_messages_to_file) and from other peek tools like peek_dlq, making its purpose distinct.
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 advises using the alternative tool for large bodies and explains session behavior (when to provide session_id vs omit). However, it does not compare against all relevant siblings like peek_dlq or peek_subscription, leaving some ambiguity.
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?
Given no annotations, the description discloses key behaviors: non-destructive, read-only, no locking or consumption, max_count cap at 100, and auth mechanism via environment variable. It also lists return content (message bodies, DLQ reason, error description, metadata). Lacks details on error handling or timeout behavior but is largely transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (~100 words), front-loaded with the main purpose, and structured with key points in short paragraphs. No redundant or vague sentences; every line adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a peek tool with an output schema, the description covers purpose, behavior, cap, alternative tool, and auth. It omits pagination details and what happens when no messages are available, but overall provides sufficient context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It clarifies max_count (capped at 100) and connection_string_env_var (purpose and auth behavior). However, it does not elaborate on namespace, topic, or subscription beyond their names, leaving some interpretation to the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Non-destructively peek at messages in the dead letter queue for a topic subscription.' It specifies the verb (peek), resource (dead letter queue for subscription), and emphasizes non-destructive read-only nature, distinguishing it from similar tools like servicebus_peek_subscription_messages.
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?
Explicitly advises using servicebus_peek_subscription_dlq_to_file when message bodies may be large, providing a clear alternative. However, it does not mention other related tools for DLQ operations (e.g., requeue, purge) or explicitly contrast with peeking active messages, which is implied by the tool name.
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?
No annotations provided, so description carries full burden. It clearly states the tool is non-destructive, describes output format (JSON keyed by sequence number), metadata returned (dead letter reason, error description, sequence number, enqueue time), and auth mechanism (connection string or DefaultAzureCredential). Missing details like file overwrite behavior, but sufficient for a peek tool.
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 5 sentences, front-loaded with the main purpose. No redundant information, each sentence adds value. Well-structured and readable.
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 6 parameters, 4 required, and an output schema, the description covers the main action, output format, auth, and metadata returned. It does not explain handling of empty DLQ or file overwrite, but for a peek tool it is mostly complete. The output schema exists, so return values are covered.
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 description adds meaning. It explains connection_string_env_var behavior and output_file format. However, other parameters (namespace, topic, subscription, max_count) are not elaborated beyond their names. The description implies their roles through the main action, but more detail on max_count would help.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'peek', the resource 'dead letter queue for a topic subscription', and the specific action of saving message bodies to a file. It distinguishes from sibling tools like servicebus_peek_subscription_dlq (no file output) and servicebus_peek_dlq_to_file (queue vs subscription).
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 mentions 'non-destructively peek', implying use for investigation. It specifies saving bodies to file and returning metadata in context. While it does not explicitly state when not to use or list alternatives, the context of siblings like servicebus_peek_subscription_dlq and servicebus_peek_subscription_messages_to_file allows inference. A small gap for explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. Discloses destructive behavior, early stop condition, and auth mechanism. Lacks details on rate limits or return behavior, but sufficient for a purge tool.
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?
Four concise sentences, each serving a purpose: action statement, destruction warning, stopping condition, auth explanation. No unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers essential purpose, destruction warning, and key behavior. With an output schema likely present, return values need not be described. A brief note on potential latency could enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, description partially compensates by explaining connection_string_env_var and implicitly referring to max_messages. However, namespace and queue parameters remain unexplained without schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it deletes all messages from an Azure Service Bus queue. It highlights the destructive nature and distinguishes from sibling tools like peek or list operations.
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?
Explicitly warns of irreversibility and mentions stopping condition based on max_messages. Does not explicitly state when to use vs alternatives but context is clear.
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?
Despite no annotations, the description discloses key behavioral traits: destruction irreversibility, the max_messages limit effect (stops purging if exceeded), and authentication fallback. It does not cover error states or concurrency, but the provided details are valuable and accurate.
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 (5 sentences) and front-loaded with the core purpose in the first sentence. Every sentence adds value: warning, max_messages behavior, and connection_string_env_var details. No unnecessary text.
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 (5 parameters, destructive, no annotations, output schema exists), the description covers essential aspects: destructive nature, limiting behavior, and auth. It omits prerequisites or error handling, but the presence of an output schema reduces the need for return value explanations. Overall, it is sufficiently complete for an agent to use 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?
Schema description coverage is 0%, but the description explains the behavior of max_messages (stops if limit exceeded) and connection_string_env_var (auth method fallback), adding meaning beyond schema properties. Namespace, topic, and subscription are self-explanatory from their names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete all messages from an Azure Service Bus topic subscription,' identifying the exact resource (topic subscription) and action (delete all messages). It distinguishes from sibling tools like servicebus_purge_subscription_dlq by not mentioning DLQ, implying it operates on the main subscription.
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 warns that the operation is destructive and messages cannot be recovered, but does not provide explicit guidance on when to use this tool versus alternatives such as peek or requeue. Usage is implied (to clear a subscription), but no when-not-to-use or alternative suggestions are given.
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?
No annotations exist, so the description carries full burden. It explains message preservation (body, session_id, correlation_id, application_properties), the completion (removal) step, the stopping condition based on max_messages, and authentication mechanisms (connection_string_env_var vs DefaultAzureCredential). However, error handling and idempotency are not discussed.
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 (4 sentences) and front-loaded with the main purpose. Every sentence provides necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 2 required, no annotations, and an output schema, the description covers behavior (re-queue, preserve fields, stop condition) and auth. Minor gaps include potential side effects (order) and error scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds meaning for connection_string_env_var (auth fallback) and max_messages (stop threshold). Namespace and queue are not individually explained, but their role is clear from context. Overall adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Move messages from a queue's dead letter queue back to the main queue') with a specific verb and resource. It distinguishes from sibling tools like purge_dlq and peek_dlq, which have different outcomes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for requeuing dead-letter messages but lacks explicit guidance on when to use this tool versus alternatives like purge_dlq. No when-not-to-use or fallback advice is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes returned fields (role name, scope, status) but lacks details on authentication needs or rate limits. Since it's a simple list, this is adequate but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences covering purpose, return info, and usage hint. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and zero parameters, the description's summary of returned data plus usage guidance makes it complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has zero parameters, so description correctly omits param details. Baseline 4 applies as no param info needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and resource 'eligible roles' with scope 'across all accessible subscriptions'. It distinctively separates from sibling authorization_activate_role.
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?
Explicitly says 'Use this to discover what roles are available before calling authorization_activate_role', providing clear context for when to use this tool. Could elaborate on when not to use, but sufficient.
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?
No annotations provided; description discloses output format (sorted JSON array), namespace handling, and authentication behavior. Does not mention error cases or rate limits, but acceptable for a read-only list tool.
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?
Three concise sentences front-loaded with purpose, then output format, then parameter details. 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?
Output schema exists, so return values are covered. Description covers purpose, namespace handling, and authentication. Lacks mention of pagination limits or error scenarios, but minor for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant meaning beyond schema: explains namespace short name vs FQDN and automatic suffix, and connection_string_env_var's role in authentication. Schema coverage is 0%, so description carries full parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'List', resource 'queues', and scope 'in a namespace'. Distinguishes from sibling tools like servicebus_list_namespaces and servicebus_list_topics.
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?
Provides guidance on namespace format and authentication methods, but no explicit when-to-use or alternatives compared to siblings like other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses return format (sorted JSON array, optionally with subscriptions), namespace format flexibility (short name or FQDN), and authentication behavior (connection string vs DefaultAzureCredential). Minor gaps: no mention of errors or rate limits.
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 well-structured paragraphs. First paragraph states purpose and behavior, second paragraph details the environment variable parameter. No redundant information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description still provides sufficient details about return format and options. All critical aspects (parameters, behavior, auth) are covered. The tool is straightforward and the description leaves no major gaps 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?
Schema coverage is 0%, so description must add value. It provides meaning for all three parameters: namespace (short name or FQDN), include_subscriptions (triggers mapping return), connection_string_env_var (env var name and auth fallback). This compensates well for lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all topics in an Azure Service Bus namespace' with a specific verb and resource. It distinguishes from siblings like servicebus_list_queues by focusing on topics, and describes return format options (sorted JSON array or mapping with subscriptions).
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 when to use (listing topics) but provides no explicit guidance on when not to use or alternatives. No contrast with sibling tools such as servicebus_list_queues or servicebus_list_namespaces is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Details read-only nature, no locking or consumption, max_count cap of 100, return contents, and authentication method with fallback. Since no annotations exist, the description fully covers behavioral traits.
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?
Concise, front-loaded with primary purpose, then behavioral details, then alternative, then param explanation. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers core functionality, return data, and authentication. Missing explanation for session_id parameter, but overall sufficient given output schema handles return structure.
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 description must compensate. It explains connection_string_env_var behavior and mentions max_count cap, but does not describe other parameters like session_id or the required namespace/topic/subscription.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it peeks at messages in a topic subscription, non-destructively. Differentiates from sibling tools like servicebus_peek_subscription_messages_to_file and servicebus_peek_dlq.
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?
Provides explicit guidance to use the '_to_file' variant for large messages. Does not mention other alternatives like peek_dlq for dead-letter queues, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses destructive behavior, irrecoverability of messages, and the stop condition when max_messages is exceeded. It also explains authentication logic, offering significant behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, all essential. It front-loads purpose, then warns of destruction, explains stop condition, and ends with authentication. 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 no annotations and 0% schema coverage, the description covers destruction, stop condition, and auth. It does not mention the output schema, but rule allows that. Still, it adequately informs the agent about key behaviors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains connection_string_env_var fully, including auth logic. However, namespace and queue parameters are only mentioned by name with no additional semantics, and max_messages is not explained beyond its default. 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 deletes all messages from a dead letter queue for an Azure Service Bus queue. It uses a specific verb and resource, and is distinct from sibling tools like servicebus_peek_dlq or servicebus_requeue_dlq.
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 clear context: it is destructive, stops if max_messages is exceeded, and explains authentication fallback. However, it does not explicitly compare to alternatives like requeue or peek, which would help the agent decide when to use this tool.
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 covers key behaviors: it lists all accounts, auto-resolves subscription, and returns error if no subscription available. It does not describe return format, but output schema exists to cover that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose. No wasted words, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema, the description is complete: it explains subscription resolution and error cases. No additional information is necessary.
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; baseline is 4. No additional semantic value needed beyond the schema, which is trivially covered.
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 'List all Azure Cosmos DB accounts in the current subscription,' with a specific verb and resource. Among siblings, it's the only tool for listing accounts, so it's well-distinguished.
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 explains subscription resolution (environment variable then az login) and error handling, providing clear context for usage. It does not explicitly mention when not to use, but for a simple list tool, this is adequate.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains subscription resolution and error handling if no subscription is available, giving useful context about prerequisites and failure modes. However, it does not explicitly state that the operation is read-only or non-destructive, though it's implied.
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 very concise: two sentences, no filler. The first sentence states the core purpose, and the second adds essential context about subscription resolution and error behavior. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an existing output schema (context signals indicate output schema exists), the description sufficiently covers the tool's behavior, including subscription resolution and error cases. It is complete for the intended use case.
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, so the baseline is 4 per the guidelines. The description adds value beyond the schema by explaining how the subscription is automatically resolved, which is relevant to using the tool. No parameter explanation is needed.
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 ('List all Azure Service Bus namespaces') and the scope ('in the current subscription'). It distinguishes itself from sibling tools like servicebus_list_queues and servicebus_list_topics which deal with entities within a namespace.
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 tool and how subscription resolution works (environment variable vs az login). It implicitly differentiates from other servicebus tools by focusing on namespaces, but lacks explicit 'when not to use' or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses non-destructive nature, file output, metadata-only return in context, and dual authentication options (env var vs DefaultAzureCredential). No annotations provided, so description carries full burden and meets it well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise paragraphs with no redundant content. Purpose in first sentence, use case and auth details efficiently grouped. Front-loaded with critical info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage context, behavior, and authentication. With output schema existing, return format is handled. Lacks error handling or file overwrite behavior, but overall sufficient for agent decision-making.
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 has 0% description coverage, but description adds significant meaning: explains `connection_string_env_var` in detail (auth switching), clarifies `output_file` purpose, and implies the role of other params. Missing individual param descriptions, but overall adds value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Non-destructively peek at messages in an Azure Service Bus queue, saving bodies to a file.' Distinguishes from related tools by specifying the file-saving behavior and large-body use case.
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?
Explicitly advises when to use this variant ('when message bodies may be large to avoid filling the context window'), implying when to use the regular peek instead. Could be stronger with explicit 'do not use when...' but sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that messages are not locked or consumed (read-only), returns metadata including dead letter reason, and describes authentication behavior. No annotations are present, so the description carries full burden and does it well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise paragraphs with front-loaded main action. Every sentence adds value, no redundancy. Efficiently communicates key points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage constraints, auth, return values, and alternative tool. With an output schema present, the description of return values is a bonus. Complete for a peek tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. Description adds meaning for connection_string_env_var (env var name and auth fallback) and mentions max_count cap. Namespace and queue are not elaborated but are self-explanatory from context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Non-destructively peek at messages in the dead letter queue for an Azure Service Bus queue,' specifying both the action and resource. It differentiates from sibling tools like servicebus_peek_dlq_to_file by noting the read-only nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly explains when to use (non-destructive peek), mentions max_count is capped at 100, and provides an alternative tool for large message bodies. Also clarifies authentication mechanism via environment variable vs DefaultAzureCredential.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![azure-utils-mcp MCP server](https://glama.ai/mcp/servers/BrianDeacon/azure-utils-mcp/badges/card.svg)](https://glama.ai/mcp/servers/BrianDeacon/azure-utils-mcp)

Score Badge

Copy to your README.md:

[![azure-utils-mcp MCP server](https://glama.ai/mcp/servers/BrianDeacon/azure-utils-mcp/badges/score.svg)](https://glama.ai/mcp/servers/BrianDeacon/azure-utils-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BrianDeacon/azure-utils-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server