queue-aiops
Server Quality Checklist
Latest release: v0.8.0
- Disambiguation3/5
Most tools have distinct purposes, but there is notable overlap between queue_overview and rabbitmq_overview, and between redis_memory_pressure_rca and redis_memory_stats. The RCA tools are clearly diagnostic, but the overview tools could be confused for simple listing tasks.
Naming Consistency3/5The naming is readable and consistently snake_case, but conventions vary: some tools use verb_noun (list_queues, delete_policy), some use noun_qualifier (redis_memory_stats), and some use rca or analysis suffixes. This mixed style is still navigable but not uniform.
Tool Count2/5With 28 tools, the set exceeds the typical well-scoped range. While the server covers both Redis and RabbitMQ, the count feels heavy, and several tools could be consolidated without losing functionality.
Completeness4/5The tool surface covers core read diagnostics and write remediation for both Redis and RabbitMQ, including lifecycle operations for queues and policies. Minor gaps exist, such as no exchange/binding management or direct message browsing, but agents can work around these for common AIOps workflows.
Average 4.5/5 across 28 of 28 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 25 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description relies on '[READ]' to signal a safe, non-mutating operation. It also discloses what metrics are reported, which gives some behavioral context. However, it does not mention potential side effects, required permissions, or the return format, leaving gaps for a tool with no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured. The purpose is front-loaded with '[READ]', and the Args section clearly documents the only parameter. Every element earns its place with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only stats tool with one optional parameter and no output schema, the description covers the essential details for selection and invocation. It could be enhanced by mentioning when to use it over sibling tools, but as a standalone stats tool it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description adequately explains the 'target' parameter as 'redis target name from config; omit for the default.' This adds meaning beyond the schema by clarifying provenance and default behavior, compensating 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads Redis memory stats, listing specific metrics (used vs maxmemory, eviction policy, fragmentation, peaks). The '[READ]' prefix indicates a read operation, and the focus on memory posture distinguishes it from sibling RCA tools like redis_memory_pressure_rca, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as redis_memory_pressure_rca or redis_server_info. The only usage note is about the optional 'target' parameter, which is more parameter guidance than tool-selection guidance.
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?
There are no annotations provided, but the description explicitly marks the operation as [READ], indicating it is safe and non-mutating. It also states the data source. However, it does not disclose potential edge cases, output size, or failure modes, relying solely on the [READ] label for safety transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a purpose statement and a parameter definition. The [READ] prefix and purpose are front-loaded, and every word is informative with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple read tool with no output schema and no annotations, so the description must carry more information. While it states the core purpose, it does not describe the return format, behavior across multiple databases, or error handling, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional parameter with no description, but the tool description explains 'target: redis target name from config; omit for the default.' This fully clarifies the parameter's meaning and default behavior, exceeding what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves per-db key counts and expiry coverage from INFO keyspace, specifying the resource and data source. The [READ] prefix signals its read-only nature. However, it does not explicitly differentiate from siblings like redis_server_info, so it is clear but not fully distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as redis_server_info or memory stats. The description only describes what it does and the parameter, leaving the agent to infer usage context.
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 itself must convey behavior. It does state '[READ]' and lists the read-only information returned, implying a non-mutating operation. However, it does not disclose any permissions required, potential errors, or how the tool behaves when the target is omitted beyond 'omit for the default' (which is a param detail, not behavior). For a simple read tool, this is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, with a clear summary at the start and a concise parameter explanation. No superfluous words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity, no output schema, and no annotations, the description sufficiently conveys purpose, parameters, and read-only nature. It lists the key output fields, though not exhaustively. Some information about return format or error handling is missing, but for a health info tool this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, target, is fully explained in the Args section: it specifies the Redis target name from config and that omitting it uses the default. This compensates for the 0% schema description coverage, giving meaning to the parameter beyond its schema type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning Redis server identity and health metrics (version, role, clients, ops/sec, hit rate), which distinguishes it from more specific Redis tools like redis_memory_stats or redis_clients. However, it lacks an explicit action verb, instead using '[READ]' and a label, which is still fairly clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to choose this tool over siblings is provided. The phrase 'health basics' implies general overview, but there's no stated alternative for deeper dives or exclusions. The context signals show siblings covering specific areas (memory, latency, clients), but the description itself doesn't mention them.
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 exist, so the description carries the burden. It signals read-only via [READ] and explains the target fallback, but does not mention return format, auth, or empty-match behavior. Adequate for a simple getter but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three lines: intent, then two parameter explanations. No wasted words. The front-loaded [READ] tag helps.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with two optional parameters, the description covers core operation and parameter semantics. It lacks return format and edge cases, but given simplicity and no output schema, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description must compensate. It explains pattern as 'Config-name glob' with an example, and target as 'redis target name from config; omit for the default.' This adds meaningful semantics beyond the schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs 'CONFIG GET for a glob pattern' with a concrete example ('maxmemory*'). The [READ] prefix and command name distinguish it from mutation siblings like redis_config_set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives are mentioned. While siblings include redis_config_set, there is no contrast between reading and writing config. The description implies use for fetching config values but does not define 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?
Since no annotations are provided, the description carries the burden and does well: it discloses the undo behavior (undo deletes it only if new), records whether the queue already existed, and supports dry_run preview. The inline [WRITE][risk=medium] header also telegraphs side effects. No contradiction with structured annotations (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably compact, with a two-sentence summary followed by a bullet-style Args list. The opening includes a safety header and the body includes only relevant behavioral notes; no verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It covers purpose, behavioral details, and all parameters, but does not describe the return value or output of the tool, which is significant given there is no output schema. It also omits any mention of prerequisites or error conditions, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions are absent (0% coverage), so the Args section is the only source of parameter semantics. It explains all seven parameters, including defaults and examples (e.g., x-arguments), fully compensating for the schema's lack.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it declares (creates) a RabbitMQ queue, using a specific verb and resource. It distinguishes itself from siblings like delete_queue and list_queues by adding 'undo deletes it if new'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is 'the replay target for delete_queue's undo', which provides a specific use case context. However, it does not explicitly state when to prefer this over other queue operations or when not to use it, so usage guidance is implied rather than explicit.
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?
The [READ] prefix indicates a read-only operation, which is the key behavioral trait given no annotations are present. However, the description does not disclose potential errors, permission needs, or any side effects, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused line followed by a structured Args list. Every sentence adds value, and the core purpose is front-loaded with the [READ] prefix and the resource scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no annotations or output schema, the description provides sufficient context for a simple read tool: it names the parameters, their meanings, and summarizes the return content (counts, rates, consumers, memory, arguments). It does not describe the exact return structure, but that is acceptable for this scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description enriches all three parameters: vhost's default is '/', name is sourced from list_queues, and target is a config-based optional value with an explicit instruction to omit for the default. This fully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'READ' and the resource 'one queue's full detail', enumerating specific content (counts, rates, consumers, memory, arguments). This distinguishes it from sibling tools like queue_overview and list_queues, which serve different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by noting the name comes from list_queues, suggesting a prerequisite workflow. However, it does not explicitly state when to use this tool versus alternatives like queue_overview, nor does it provide exclusions or comparative guidance.
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 explicitly labels the operation as '[READ]', which discloses that this is a safe, non-mutating call. It also adds ordering semantics with 'most loaded first' and implies the output includes watermark alarms. However, it does not describe the exact return format or potential edge cases, which would push it to a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first line states the purpose and key behavioral details, while the second line explains the single parameter. Every sentence contributes value, and there is no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter and no output schema. The description covers the resource type, the primary outputs (memory/disk/fd posture, watermark alarms), the ordering, and parameter semantics. It omits details like error handling or exact field names, but for a read-only health check this is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only the parameter name and type with zero description coverage. The description compensates by explaining that 'target' is a 'rabbitmq target name from config' and that omitting it uses the default, which gives meaningful context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation type with '[READ]' and specifies the resource: 'Node memory/disk/fd posture + watermark alarms'. It also adds a distinguishing behavioral detail ('most loaded first'), which differentiates it from queue-focused siblings like list_queues or rabbitmq_overview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for checking node health, but it does not explicitly state when to use this tool versus alternatives or when not to use it. No sibling tool is referenced for comparison, and the only guidance is the '[READ]' prefix, which is a general operation class rather than specific usage direction.
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 this is a read operation ('[READ]'), one-shot (no pagination), and platform-dispatched, listing specific metrics for redis and rabbitmq. This is valuable context beyond the schema, though it omits details on error handling and exact return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and front-loaded with the core purpose. It uses clear paragraphing and an Args list, with every sentence contributing useful information. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one optional parameter and no output schema. The description explains the purpose, platform-specific behavior, and parameter semantics. It does not describe the return structure or errors, but given the tool's simplicity and one-shot nature, the description is adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%: the input schema only provides name/type/default. The description compensates by explaining that 'target' is the broker target name from config and that omitting it uses the default, adding meaning not present in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'One-shot summary: platform + version + backlog/memory/client health.' It uses a specific verb (summarize) and resource (queue/broker), and distinguishes itself from siblings by noting it is platform-dispatched across redis and rabbitmq, unlike more targeted tools like list_queues or rabbitmq_overview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a quick high-level overview ('One-shot summary') and notes the default target behavior, but it does not explicitly state when to use this tool versus alternatives or mention exclusions. Sibling tools like RCA or detail tools are not referenced, leaving the choice to the agent's inference.
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?
Although no annotations are provided, the description explicitly marks the operation as [READ], indicating it's a safe, non-mutating call. It also discloses the kind of information returned. However, it doesn't detail any potential limitations or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with a clear one-line summary and a minimal args block. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only overview tool with one optional parameter and no output schema, the description adequately covers the tool's purpose, the parameter, and the type of data returned. It is 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.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains that 'target' is a RabbitMQ target name from config and can be omitted for the default, adding meaning beyond the schema's type/default. This is sufficient for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies this as a read-only broker overview tool, listing specific data (version, queue/message counts, rates, churn). The [READ] tag and 'Broker identity + totals' distinguish it from sibling tools like queue_overview or list_queues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a high-level broker summary but does not explicitly state when to use this tool versus alternatives. It doesn't provide exclusion criteria or compare to sibling 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?
No annotations are present, so the description carries the burden. It discloses the [READ] nature, sorting order, return envelope fields, and the truncation behavior, which is important for correct interpretation. It does not mention potential errors or permissions, but for a read-only list operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, starting with a clear purpose line, followed by an Args section and a Returns section. It avoids unnecessary verbosity and front-loads the key information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only one optional parameter and no output schema, so the description's return envelope is essential. It includes the 'truncated' flag semantics, preventing an agent from treating the result as complete. The description is complete enough for the tool's low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for the 'target' parameter, but the description explains it as the 'rabbitmq target name from config' with instruction to omit for default. This fully compensates for the schema's lack of coverage, clarifying both meaning and usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists channels with unacked/prefetch pressure, ordered by most unacked first. This specific verb+resource+ordering distinguishes it from sibling tools like list_queues. The [READ] prefix reinforces 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool's purpose but does not explicitly state when to use it over alternatives. It provides context about the channel list, but lacks direct comparison to sibling tools. An agent can infer usage from the description but would benefit from explicit guidance.
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 the full burden. It discloses the read-only nature via '[READ]', describes the return envelope structure, and warns about truncation meaning an incomplete set. However, it does not explain how to request the next page when truncated, so it is not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses a clear three-part structure: summary, args, and returns. Every sentence adds value, and it is appropriately sized and front-loaded with the purpose. No fluff or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with 2 optional parameters, and the description covers parameter semantics, the return envelope, and the truncation caveat. The only minor gap is pagination follow-up, but given the lack of an output schema and the tool's simplicity, the description is complete enough for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description fully explains both parameters: vhost (restricts to one vhost, default '/') and target (RabbitMQ target name from config, default). It also clarifies the behavior of omitting each parameter, fully compensating for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as listing policies, optionally restricted to a vhost, and specifies the returned fields (pattern, priority, definition). The '[READ]' prefix and resource focus distinguish it from sibling mutation tools like set_policy and delete_policy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to scope the call (vhost, target) and the default behavior when omitted, but it does not explicitly state when to use this tool versus alternatives. The read-only nature is implied, but no exclusions or alternative tool names are mentioned.
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 the full burden. It discloses the read-only nature, ordering, defaults, and crucially the truncation semantics ('do not treat this as the complete set'). This is valuable beyond simple read/write hints, though it doesn't describe the fields of each queue item.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with purpose, and organized into args and return envelope sections. Every sentence adds meaningful information, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a return envelope and truncation caveat, which is sufficient for a list tool with two optional parameters. It does not enumerate queue object fields, but that is not critical for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, both parameters (vhost, target) are fully explained with their meanings, defaults, and omit behavior. This fully compensates for the bare schema and helps the agent pass correct arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists queues, optionally restricted to one vhost, ordered by deepest backlog first. This is a specific verb+resource and distinguishes it from sibling tools like queue_detail (single queue) or queue_overview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context on how to invoke: optionally restrict to a vhost, omit for all; explains default vhost and target. It doesn't explicitly name alternatives or when-not-to-use cases, but for a listing tool the usage is well implied.
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 the full burden and does well: it declares '[READ]' semantics, describes the classification logic (no consumers, unacked pileup, rate mismatch, residual), mentions global memory/disk alarm detection, and notes that 'every finding carries its numbers.' It doesn't cover error handling or permissions, but the read-only nature and analysis behavior are transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a concise summary sentence, a clarifying paragraph, and a bulleted 'Args' list. There is no redundancy; every sentence contributes essential information about behavior, usage, or parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, this description is surprisingly complete. It explains the return dict structure, the operational modes, and the classification causes. Minor gaps like threshold configuration or error scenarios are not mentioned, but overall the context is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's 'Args' section fully compensates by explaining each parameter: vhost (restrict live pull), top (row count), queues (injected rows), nodes (node health rows), target (RabbitMQ target name). This adds crucial meaning beyond the bare schema names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource+output: 'Rank backlogged queues and map each to a cause + action.' It lists explicit cause categories and mentions flagging queues over a threshold, clearly distinguishing this from sibling tools like list_queues or node_health.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to invoke it in different modes ('Pass queues (and optionally nodes) for pure analysis, or a target to pull live') and mentions vhost/target optionality. It does not explicitly contrast with alternatives or state when not to use it, but the usage 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?
With no annotations, the description carries the full behavioral burden. It explicitly labels the tool as [WRITE][risk=medium], discloses that the inverse runs through its own governed tool with its own risk tier, notes that a token can only be applied once, and explains the dry_run preview behavior. This goes beyond basic purpose, though it omits error handling and return format details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a leading risk marker, a short paragraph on behavior, and a clear Args list. Every sentence adds distinct value, with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter tool with no annotations or output schema, the description covers purpose, usage, parameter semantics, and key behavioral constraints (single-use, dry-run, risk governance). It does not explicitly state return values or failure cases, but these are not critical given the tool's straightforward nature and the availability of sibling tools like undo_list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description fully compensates by explaining each parameter: undo_id (source from undo_list or _undo_id), dry_run (preview behavior), and target (pass-through behavior). This adds essential meaning that the schema alone lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Apply a recorded undo by dispatching its inverse tool,' which clearly states a specific verb and resource. It distinguishes from the sibling undo_list by focusing on application rather than listing, and the mechanism of dispatching an inverse tool adds valuable specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that undo_id comes from undo_list or a write result, and suggests using dry_run=True to preview without executing. This establishes clear usage context, though it doesn't explicitly state when not to use or name alternatives beyond the implicit undo_list. No exclusions are provided, but the context is sufficient for correct use.
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, the description carries the full burden and does an excellent job. It explicitly labels the tool as '[READ]', discloses the grouping/ordering behavior, and details the return envelope including the 'truncated' flag, warning that a truncated result is not the complete set. This goes beyond what the schema provides and fully informs the agent of important 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: a clear '[READ]' label, a one-sentence summary, an Args section, and a Returns section. Every sentence adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter) and the absence of an output schema, the description fully covers the tool's behavior and return format. The explicit envelope with the 'truncated' warning ensures the agent understands pagination limits, making the description complete for safe and correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully by explaining the one parameter 'target' as the RabbitMQ target from config, with the default behavior when omitted. This adds meaningful semantics beyond the bare schema definition, giving the agent everything needed to use the parameter correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists client connections, grouped by peer host and sorted busiest first. This specific verb+resource combination distinguishes it from sibling tools like list_channels or list_queues, which focus on different RabbitMQ resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for inspecting client connections, but it does not provide explicit guidance on when to choose this over alternatives like list_channels or list_queues. There are no exclusion criteria or comparative context, though the '[READ]' prefix signals it is safe for read-only inspection.
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 the full burden. It clearly marks the operation as a read ('[READ]'), explains that it interprets memory metrics (e.g., noeviction means writes OOM, fragmentation ratio high = defrag), mentions the SCAN-budgeted big-key sample (implying potential cost), and states that every finding includes evidence. It stops short of discussing rate limits or performance implications of a live pull, but overall it is highly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a one-line summary, a paragraph with key details, then 'Args:' and 'Returns:' sections. Every sentence contributes meaningful information—thresholds, interpretation hints, and return fields. No unnecessary fluff or repetition of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (RCA with multiple metrics and findings), the description fully covers input modes, parameters, and the return dict structure. Since there is no output schema, the explicit enumeration of return fields (pressure, usedPctOfMax, findings, etc.) makes the tool self-sufficient for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameter descriptions (0% schema coverage), so the description fully compensates. It explains used_pct as the 'used/maxmemory %' threshold, telemetry as an injected object that skips the live pull, and target as the redis target name from config. Each parameter's purpose and default behavior are clearly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] Diagnose redis memory pressure → cause + action, with numbers,' which is a specific verb (diagnose) + resource (redis memory pressure) + outcome (cause and action with numbers). It clearly differentiates from sibling tools like redis_memory_stats (raw stats) and redis_latency_rca (latency) by framing this as the flagship memory RCA.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it's for diagnosing redis memory pressure with actionable findings. It explicitly explains the two invocation modes ('Pass telemetry for pure analysis, or a target to pull live'), but does not explicitly state when not to use it or name alternatives. Since it identifies itself as 'the flagship memory RCA,' the usage context is unambiguous.
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 present, so the description carries the full burden. It discloses the read nature, count cap (128), target resolution, and the return envelope with a truncation warning. This is important behavioral info—especially the truncated flag—that an agent needs to interpret results correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly structured: a one-line purpose, a bulleted args section, and a return envelope description. Every sentence adds value—no fluff, no repetition. It's easy to scan and front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with two optional params and no output schema, the description provides everything needed: purpose, parameter meanings, return format, and truncation semantics. The size and complexity are modest, so this is complete without needing to document alternatives or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and parameters are only typed with defaults. The description fully compensates: 'count' is explained as max entries with a cap, 'target' is described as a Redis target name from config with a default. This adds meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific action: "[READ] Recent SLOWLOG entries, slowest first." This states the tool's verb (read), resource (SLOWLOG), and ordering, distinguishing it from Redis memory, config, and latency tools among its siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: this is for pulling recent slowlog entries, with optional count and target parameters. It doesn't explicitly name alternatives or say when not to use it, but the tool's purpose is self-evident and it's distinct from sibling read-only tools like redis_server_info or redis_memory_stats.
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, the description carries full burden and does an excellent job: it discloses the read-only nature, exact resource limits (10,000 key scan, 200 MEMORY USAGE calls), the avoidance of KEYS *, and the partial-coverage sampling with coveragePct. It also explains the truncation flag, leaving little ambiguity about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a one-line summary, a safety paragraph with limits, and an explicitly labeled Args/Returns section. Every sentence contributes useful information without redundancy, making it concise yet complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the return envelope and the meaning of 'truncated', but it does not detail the structure of each element in 'topKeys' (e.g., key name, type, size). Also, 'coveragePct' is mentioned in the safety section but not shown in the example envelope, leaving a minor gap. Still, overall it is quite complete for a sampling tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description compensates fully by explaining both parameters: 'top' as the number of rows to return with default 20, and 'target' as the Redis target from config with an omit-for-default instruction. This adds exactly the meaning the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a read operation that samples big keys using a SCAN budget and returns largest keys first. The '[READ]' prefix and detailed resource-specific actions ('Walks at most 10,000 keys with SCAN and sizes at most 200') distinguish it from sibling monitoring tools like redis_memory_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context for production safety by stating that KEYS * is never used and limits are explicit. It implies when to use this tool (sampling big keys) but does not explicitly contrast it with alternatives like redis_memory_pressure_rca or redis_slowlog.
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?
No annotations are provided, so the description carries the full burden. It declares '[READ]', explains platform-specific behavior (reconnect-per-operation, maxclients, channels-per-connection ratio), notes grouping by source for attribution, and discloses the snapshot/history reuse pattern. This is substantive behavioral context beyond what schema or annotations could add.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently organized: a one-line purpose, platform breakdown, workflow note, Args list, and return shape. Every sentence earns its place, and the structured layout makes it easy to scan. Despite covering a complex tool, it remains under ~150 words with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (two platforms, three parameter modes, no output schema) the description is remarkably complete. It covers both platform behaviors, parameter semantics, the snapshot/history workflow, and the exact return dict shape including findings with cause/action/evidence. An agent can select and invoke this tool correctly with no missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema properties have no descriptions (0% coverage), but the Args section adds meaningful semantics: snapshot is 'Injected snapshot (from a prior call's live pull shape); skips the live pull', history is 'A prior snapshot for delta analysis (optional)', and target is 'Broker target name from config; omit for the default.' This fully compensates for the schema's lack of property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with '[READ] Connection/channel churn → cause + action; works on both platforms,' which names a specific resource and clear analytical purpose. It distinguishes itself from sibling tools by calling it the 'flagship churn analysis' and covering both redis and rabbitmq, whereas siblings target platform-specific metrics like memory or latency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear workflow guidance: 'Call it once, keep the returned snapshot fields, and pass them back later as history for delta-based churn' and distinguishes modes: 'Pass snapshot for pure analysis, or a target to pull live.' This gives clear context for usage but does not explicitly name when not to use or alternative tools, so it stops short of a 5.
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?
No annotations are provided, so the description carries the full burden. It opens with [WRITE][risk=medium], explicitly discloses the read-first behavior for undo, and explains the dry_run parameter. This provides strong safety and reversibility context beyond what the schema shows.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the essential purpose and risk, followed by a single explanatory sentence and a clean Args list. There is no fluff or redundancy; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations and an output schema, the description covers the tool's purpose, undo mechanics, dry-run behavior, and all parameters. This is fully sufficient for an agent to select and invoke the tool correctly, especially with sibling tools like undo_list and list_policies in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates thoroughly: it gives vhost's default, notes that name should come from list_policies, explains dry_run as a preview, and identifies target as the rabbitmq config name. Each parameter gets meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Delete') with a clear resource ('a rabbitmq policy') and notes the undo behavior, distinguishing it from siblings like set_policy and delete_queue. The phrase 'the undo re-creates it' adds a unique functional trait.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly implies when to use the tool (to delete a policy) and even provides a dry-run option for preview before committing. It references list_policies for obtaining names, but does not explicitly state when not to use it or compare to alternatives explicitly, so it stops short of a 5.
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, the description carries full burden and does so thoroughly. It discloses WRITE with high risk, reads before deletion, records priorState for undo, and explicitly states messages are NOT restored. Dry-run preview is also noted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a summary line, behavioral detail, and an Args block. Every sentence adds critical information, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description covers the operation lifecycle, undo semantics, dry-run, parameter nuances, and risk. The only minor gap is not mentioning what the return value looks like, but the detail is otherwise comprehensive for a delete operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description's 'Args' section explains every parameter: vhost (default '/'), name (from list_queues), dry_run (preview), and target (config default). This goes well beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: "Delete a rabbitmq queue" and adds the undo behavior, distinguishing it from siblings like purge_queue and declare_queue. It clearly states what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it can preview with dry_run, reads the queue first, and the undo re-declares the queue. It does not explicitly name alternative tools or say when not to use it, but the behavior is well-enough specified to infer appropriate use.
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 carries full burden. It discloses irreversibility, reads queue first for audit evidence (priorState), excludes unacked messages, and supports dry_run preview. This goes far beyond basic expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the purpose and risk warning. Every sentence earns its place: purpose, behavior, dry_run, and parameter semantics. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema and no annotations, the description covers all critical aspects: what it does, side effects, irreversibility, parameter meanings, and safety preview. It is fully sufficient for an AI agent to invoke correctly and avoid unintended damage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameter descriptions, but the description's Args section explains every parameter: vhost (including default '/'), name (from list_queues), dry_run (preview), and target (default). This fully compensates for the schema's lack of semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Purge all ready messages from a rabbitmq queue', which is a specific verb+resource. It clearly distinguishes from siblings like delete_queue (which removes the entire queue) and list_queues (which only lists). The IRREVERSIBLE warning reinforces the destructive scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: irreversible purge, dry_run to preview, unacked messages not purged. It does not explicitly name alternatives (e.g., delete_queue) but the meaning is implicit. The '[WRITE][risk=high]' header and 'No undo' guidance help the agent decide.
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?
No annotations are provided, so the description fully carries the behavioral disclosure burden. It explicitly declares the operation as read-only with the '[READ]' tag, explains the grouping and ordering (by source address, busiest first), and details the return envelope including the 'truncated' flag and its meaning ('do not treat this as the complete set'). This is genuine transparency beyond basic expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly structured: a two-line summary with a useful '[READ]' prefix, then short 'Args' and 'Returns' sections. Every sentence adds value—no fluff, no repetition. It is front-loaded with the most important information and remains concise despite covering parameter and return semantics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only one optional parameter and no output schema, the description covers all essential aspects: what the tool does, the parameter meaning, the exact return envelope structure, and the truncation behavior. It is complete for an agent to select and correctly invoke the tool, with no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only a parameter named 'target' with a default of null and no description (0% schema coverage). The description compensates fully by explaining: 'target: redis target name from config; omit for the default.' This tells the agent exactly what the parameter means and how to use it, which is critical given the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific action: '[READ] Connected redis clients grouped by source address, busiest first.' This states exactly what the tool does (lists connected Redis clients) and how results are organized, distinguishing it from siblings like redis_server_info or redis_slowlog. The resource (redis clients) and verb (list/read) are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: it is a read-only listing of connected Redis clients, with a truncation warning that guides interpretation of partial results. It does not explicitly name alternative tools or state 'use this instead of X,' but the read-only nature and the contrast with sibling write tools like redis_kill_client are implicit. The truncation note is a practical usage guideline.
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 carries the full burden. It discloses irreversibility, priorState capture, that no undo is recorded, client reconnection behavior, and the refusal to kill its own connection even under dry_run. This is rich, non-obvious 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the critical warning ('[WRITE][risk=medium]', 'IRREVERSIBLE'), followed by concise paragraphs and a clean Args list. Every sentence adds value; no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description covers purpose, parameters, side effects, safety measures, and edge-case refusal behavior. It is sufficient for an agent to select and invoke the tool correctly, including using dry_run and avoiding self-kills.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does 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 each parameter in the Args block: 'client_id' (preferred), 'addr' (alternative), 'dry_run' (preview), and 'target' (default behavior). This goes beyond the schema's type/default info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Disconnect') and the resource ('one redis client by id or addr'), with explicit scope. It distinguishes itself from sibling tools like redis_clients (listing) and redis_config_set (config) by focusing on the kill operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context, such as preferring client_id from redis_clients and the dry_run preview option. However, it does not explicitly state when to use this tool instead of alternatives or list exclusions (e.g., don't use on cluster-wide operations).
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, the description carries the full burden and delivers extensively: it clearly states it's a read operation ('[READ]'), describes the exact data sources (SLOWLOG, INFO stall signals), how it flags patterns (O(N)/blocking commands), and what output to expect (every finding carries its numbers). It also discloses the telemetry vs. live-pull behavior, which is crucial for an agent to predict runtime effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose, then organized into a behavior paragraph, Args, and Returns. Each sentence contributes unique information—no fluff. While longer than simple tool descriptions, the complexity justifies the length, and the structure makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description documents the return dict structure. It covers all three parameters, the analysis scope, and the two operational modes. For a diagnostic tool with moderate complexity, this is complete enough for an agent to invoke correctly without needing external documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does so thoroughly: slow_us is explained with a default and example, telemetry is described with a detailed injected structure and side effect ('skips the live pull'), and target is clarified as a config reference with 'omit for default'. This adds rich meaning beyond the bare schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description immediately states 'Diagnose redis latency → slowlog digest + stall causes + actions', clearly identifying the tool's purpose as a latency root-cause analysis. It distinguishes itself from sibling tools like redis_slowlog (raw slowlog) and redis_server_info (general info) by positioning itself as 'The flagship latency RCA' and describing a comprehensive analysis pipeline.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly explains the two usage modes: pass 'telemetry' for pure analysis or a target to pull live. It identifies this as the flagship latency RCA, implying it should be used for latency diagnosis. However, it does not explicitly mention when NOT to use it or name alternative tools for simpler cases, so it stops short of full exclusion guidance.
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 discloses that the tool reads the policy first, records an undo, restores prior fields or deletes the policy if newly created, and supports dry_run. This is rich behavioral transparency, especially given no formal annotations exist to provide this context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a summary line, behavior notes, and a clear Args list. It is appropriately sized for the tool's complexity and contains no unnecessary sentences; every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's purpose, behavior, parameters, and edge cases such as new vs existing policies and dry_run. Given the lack of an output schema and annotations, it provides all essential context an agent needs to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Every parameter is explained with semantics, defaults, examples, and the special meaning of the target parameter. The description fully compensates for the 0% schema coverage by providing essential details beyond the raw schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates or updates a RabbitMQ policy, using a specific verb and resource. It also explains the reversibility and the difference from deletion, effectively distinguishing it from sibling tools like delete_policy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool is for creating/updating policies and mentions dry_run for previewing, which gives solid usage context. It does not explicitly mention alternative tools or when-not-to-use, though the clarity of the purpose largely compensates.
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, the description carries the full burden and excels. It reveals the exact return shape, explains that `truncated` is *measured* (one extra row fetched) rather than inferred, and defines `effectVerified` semantics (PROBABLE vs confirmed). It also discloses that `target` is unused and state is host-local. This is exceptionally transparent behavior beyond basic schema info.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a concise summary line, followed by return format and edge-case explanations, then a clean Args list. Every sentence adds value; no fluff or repetition. The length is justified by the technical nuance it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no annotations or output schema, the description covers purpose, parameters, return values, edge cases (`truncated`, `effectVerified`), and usage workflow. It is fully self-contained for an agent to select and call the tool correctly, and even explains how to interpret results for downstream actions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% in the structured schema, but the description's Args section fully compensates: `limit` is described as max rows with default 50 and cap 500, and `target` is explicitly documented as unused/accepted for CLI uniformity. This adds crucial meaning that the bare schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific verb and resource: '[READ] List recorded, not-yet-applied undo tokens (most recent first).' It distinguishes itself from sibling `undo_apply` by stating it lists tokens for later application, and it names the inverse tool behavior. The purpose is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides practical usage guidance: tells the agent to use `undoId` with `undo_apply`, explains the `truncated` flag ('re-run with a higher `limit`'), and warns about `effectVerified` false (check live state before applying). It does not explicitly state when not to use the tool, but the context and details imply appropriate usage clearly.
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 behavior: it states the write nature, risk level, reversibility, read-first behavior, persistence semantics, dry-run behavior, and a specific list of refused parameters. It even notes that refusals apply under dry_run, a subtle but important behavioral trait.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a clear one-line summary, then necessary behavioral details in short paragraphs, followed by a compact args list. Every sentence provides unique value; the length is justified by the tool's complexity and the absence of annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema and no annotations, the description covers operational context, restrictions, dry-run behavior, and parameter provenance. It gives enough information for an agent to invoke the tool correctly and understand side effects. The refusal list is a critical detail that makes the description feel complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description compensates with an Args block that explains each parameter: 'parameter' gains source and example, 'value' gains 'New value', 'dry_run' gains 'preview without changing', and 'target' gains 'redis target name from config; omit for the default.' This adds significant meaning beyond the sparse schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[WRITE][risk=medium] Set one redis config parameter; reversible,' clearly stating a specific action on a specific resource. It distinguishes from siblings like redis_config_get and other redis tools, and even references redis_config_get as the source for parameter names.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: it mentions the undo mechanism via CONFIG GET, notes that changes are runtime-only, and instructs to change restricted parameters in redis.conf and restart. It also explains dry_run behavior and refusal conditions, giving clear context for when the tool is appropriate versus when to use alternative approaches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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