SmartBear MCP server

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

The description says the QA lead 'can list, create, and update test cases, manage functional areas, and read the application model,' implying potentially mutating behavior. However, annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. This directly contradicts the described create/update capabilities, so the behavioral disclosure is not just incomplete but inconsistent.

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

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

The description is compact and front-loaded with the action and main usage directive. The capabilities sentence is informative, and the structured parameter section is easy to scan. Minor duplication exists because the parameter line repeats the schema, but overall it is appropriately sized.

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

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

The description does not explain what happens after the instruction is sent, whether the work is performed synchronously, or what the return value is. The 'Toolset: Tasks' hint and sibling tools like bearq_get_task and bearq_wait_for_task suggest an asynchronous task flow, but the description leaves that to inference. Combined with the annotation contradiction, this is incomplete for an open-ended, potentially effectful tool.

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

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

Schema description coverage is 100%, and the description repeats the same parameter meaning: 'Natural language instruction to send to the BearQ QA lead agent.' It adds no extra detail about format, length, examples, or what kinds of instructions work best. With full schema coverage, baseline 3 is appropriate.

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

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

The description opens with a specific verb and resource: 'Sends an open-ended instruction to BearQ's QA lead agent.' It then clarifies the tool's role as a general-purpose escape hatch when no other BearQ tool fits, which clearly distinguishes it from the many sibling BearQ tools. The list of capabilities (list/create/update test cases, manage functional areas, read the application model) adds concreteness.

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

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

The description explicitly states when to use this tool: 'Use this when no other BearQ tool fits.' This also implies a when-not: if a more specific BearQ tool applies, use that instead. The capability list gives the agent a sense of what kinds of requests are appropriate, making the usage guidance strong.

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

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

Annotations already mark the operation as destructive and non-read-only, but the description adds meaningful nuance: deletion is reversible, test cases are archived and restorable, and protected tests are rejected. This goes well beyond what annotations provide.

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

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

The description is compact and front-loaded: first the action, then the reversibility nuance, then the constraint. Every sentence carries useful information with no filler or redundancy.

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

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

For a single-parameter tool with rich annotations and full schema coverage, the description provides everything needed to invoke it correctly. No output schema exists, but return details are not essential for a delete operation with clearly stated behavior.

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

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

The input schema covers 100% of parameters and fully describes testCaseIds. The description only paraphrases the schema by saying deletion is by ID, so it adds no meaningful new parameter-level meaning. Baseline 3 applies.

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

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

States a specific verb ('Deletes'), a specific resource ('BearQ test cases'), and a specific selection method ('by ID'). It also clarifies the behavior for protected versus unprotected tests, making the tool's purpose unambiguous and distinct from sibling run/expand tools.

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

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

Clearly indicates that this tool works on unprotected tests and that protected tests are rejected, which gives an explicit when-to-use condition. It does not name an alternative tool, but none of the siblings appear to offer the same delete operation, so this is sufficient context.

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

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

The description says the tool will 'discover or update' pages and elements, implying a state change, while annotations declare readOnlyHint=true. This is a direct contradiction unless 'update' refers only to an internal cache, which the description does not clarify.

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

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

The description is compact and front-loaded with the core purpose, followed by a concise parameter note. The 'Toolset: Tasks' line adds marginal context but does not make the description bloated.

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

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

The description does not mention return values, whether the tool starts an asynchronous task, or how to monitor progress—especially relevant given the 'Toolset: Tasks' hint and sibling task-status tools. The read/update ambiguity also leaves an important side-effect question unresolved.

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

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

Schema coverage is 100%; the schema already documents that functionalArea is an optional ID or name and that omitting it explores the entire application. The description restates this without adding meaningful detail beyond the schema.

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

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

The description identifies a specific action and resource: exploring the live application to discover or update pages and elements in BearQ's application model. This is clearly distinct from the test-execution and test-management siblings, though it does not explicitly contrast with any sibling tool.

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

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

There is no guidance on when to use this tool versus alternatives such as bearq_run_test_cases or bearq_get_task. The only usage hint is parameter-scoping ('Omit to explore the entire application'), which does not help an agent choose this tool over others.

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

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds valuable behavioral context by disclosing that the call returns immediately and does not block on task completion, which is important for agents deciding between this and a waiting/blocking tool.

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

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

The core description is concise, front-loaded, and contains only useful information. The separate 'Parameters' section adds minor redundancy since the schema already documents taskId, but the overall structure is clean and quick to scan.

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

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

For a simple, read-only, single-parameter tool, the description is sufficiently complete: it states what is returned, highlights non-blocking behavior, and the schema covers the parameter. No output schema exists, but the description gives a reasonable high-level view of the response contents.

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

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

Schema coverage is 100% and the single parameter taskId is fully described in the schema. The description repeats this information without adding new meaning, so it stays at the baseline 3 for high schema coverage.

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

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

The description uses a specific verb ('Retrieves') with a clear resource: a task's current state, metadata, and activity log. It also differentiates itself from sibling tools by explicitly stating it returns immediately and does not block on completion, distinguishing it from bearq_wait_for_task and bearq_get_task_status.

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

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

The description clearly implies when to use this tool: when you want the currently available snapshot of a task without waiting. However, it does not explicitly name alternatives or state when not to use them, so the guidance is clear but not fully explicit.

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

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds value by disclosing the set of possible statuses (running/complete/error/cancelled) and signaling a lightweight response relative to full task details. There is no contradiction with annotations.

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

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

The core message is two front-loaded sentences with statuses and the cost trade-off first. Some space is spent restating the parameter in a manual Parameters section that duplicates the schema, so it is not maximally lean.

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

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

For a one-parameter read-only lookup, the annotations carry the safety profile and the description supplies the meaningful output domain (statuses) and a cost rationale. An explicit note on the exact return shape or a pointer to bearq_get_task when full details are needed would make it more complete, but nothing essential for a basic call is missing.

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

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

Schema already covers taskId with description and constraints, and schema_description_coverage is 100%. The description only repeats the parameter name and 'BearQ task ID', adding no new semantics or format guidance, which fits the baseline of 3.

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

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

States a specific action ('Retrieves the status of a task') and enumerates the possible status values. The phrase 'Cheaper than fetching full task details' distinguishes it from the full-task retrieval sibling without relying on the title alone. This clearly separates it from run/stop/wait sibling tools.

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

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

The cost note ('Cheaper than fetching full task details') tells an agent to prefer this tool when only status is needed. It does not explicitly name the alternative tool (e.g., bearq_get_task) or spell out when not to use it, so it stops short of full routing guidance.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description only needs to add non-obvious context. It does so by explaining the output's intended role: supplying valid environment names to test-running tools and revealing the workspace default. There is no contradiction with the annotations.

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

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

Two front-loaded sentences deliver the core message with no filler. The optional 'Toolset' and 'Parameters' sections are compact and don't repeat schema details excessively. Every sentence in the description earns its place.

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

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

For a simple read-only, idempotent, parameterless listing tool, this description is complete. It states what is listed, how the information should be used, and that the workspace default is included. No output schema exists, but the description's promise of 'valid environment names' and 'workspace default' gives the agent enough to call and interpret the result correctly.

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

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

The tool has zero parameters and the input schema is an empty object with 100% coverage, so there is no parameter meaning for the description to add. The description explicitly states 'Parameters: None,' which is accurate and harmless. The baseline of 4 for parameterless tools applies here.

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

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

The description opens with a specific verb-resource pair: 'Lists the environments configured in the workspace.' This clearly identifies what the tool does and distinguishes it from the many BearQ test-running and task-management siblings. The added detail about discovering environment names and the workspace default reinforces its unique role.

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

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

The description explicitly tells the agent when to use this tool: 'Use this to discover valid environment names to pass to the test-running tools, and to identify the workspace default.' This provides clear context and a concrete purpose. It does not list alternatives or state when not to use it, but for a unique zero-parameter listing tool, the guidance is sufficient.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the scope of 'every regression-ready test case' and the CI/CD context, but it does not disclose async behavior, how results are returned, or whether a task object is created—information an agent may need for long-running suites.

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

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

The core purpose is front-loaded in one clear sentence, followed by a concise usage hint. The 'Parameters' section duplicates the schema and could be trimmed, but overall the description is compact and well-structured.

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

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

With no output schema, the description does not explain what the tool returns, whether the run is synchronous or asynchronous, or how to retrieve test results. Sibling tools like bearq_get_task_status and bearq_wait_for_task imply a task-based flow, but the description leaves this important behavioral detail implicit.

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

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

Schema description coverage is 100% for the single optional environment parameter. The description repeats the same parameter text verbatim without adding syntax, defaults, or examples beyond what the schema already provides.

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

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

Description uses a specific verb and resource: 'Runs the full BearQ regression suite — every regression-ready test case in the workspace.' This clearly distinguishes it from sibling tools like bearq_run_test_cases and bearq_run_tests_in_functional_areas by emphasizing the full suite scope.

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

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

States clear usage context: 'Use for CI/CD or pre-release smoke.' This tells the agent when to invoke the tool, though it does not explicitly mention alternatives or when not to use it, such as pointing to bearq_run_test_cases for targeted runs.

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

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

Annotations already signal read-only, idempotent, non-destructive behavior, lowering the burden on the description. It adds the draft-rejection constraint and workspace-default environment context, but it doesn't disclose whether execution is asynchronous, whether results are returned immediately, or whether re-running the same IDs has side effects. 'Runs' sits somewhat uneasily with readOnlyHint but is not a direct contradiction.

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

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

The main action is front-loaded and the important draft-rejection behavior is prominent. The explicit Parameters block repeats schema descriptions, creating minor redundancy, but the overall length remains compact and scannable.

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

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

For a 2-parameter tool with strong annotations and fully documented parameters, an agent has enough information to select and invoke it correctly. It could be more complete by noting how results or task status are retrieved and how it compares with nearby bearq_run_* siblings, but these are not blocking for correct use.

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

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

Schema description coverage is 100%, and the Description's Parameters block largely duplicates the schema text verbatim ('IDs of BearQ regression test cases to run', 'Omit to use the workspace default'). The description adds no meaningful semantic value beyond what the schema already provides.

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

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

States a specific action ('Runs specific BearQ regression test cases') with the resource (test cases) and a clear selection mechanism (by ID). The qualifiers 'specific... by ID' and 'regression-ready cases — drafts will be rejected' distinguish it from sibling run tools like bearq_run_regression_tests and bearq_run_tests_in_functional_areas.

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

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

Gives clear context: use for specific BearQ regression test cases by ID, and do not pass drafts since they will be rejected. It stops short of a 5 because it does not explicitly name sibling alternatives or state when those should be used instead.

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

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

Annotations already cover read-only/idempotent/destructive safety, so the description's burden is mainly behavior beyond that. It does not mention that this appears to create or run a task, return a task identifier, or require polling with sibling task tools. 'Runs every regression test case' communicates the core action but adds no execution-lifecycle context.

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

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

The opening sentence is efficient and front-loaded. However, the parameter list duplicates the schema descriptions and the 'Toolset: Tasks' line contributes little functional value, so not every line earns its place.

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

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

No output schema and no return-value description, and no mention of the task lifecycle despite sibling get_task_status/wait_for_task/stop_task tools. An agent can invoke it with functionalAreas, but cannot know what to do with the result or how to monitor completion. With no output schema, the description should bridge that gap.

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

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

Schema coverage is 100%: both functionalAreas and environment already have descriptions in the schema. The description repeats them verbatim, adding no new meaning beyond saying that functional areas may be IDs or names, which the schema's anyOf already implies. Baseline 3 is appropriate.

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

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

The first sentence states a specific action and scope: it 'Runs every regression test case tagged with one or more functional areas.' This clearly identifies the resource and distinguishes it from broader runners like bearq_run_regression_tests, though it does not explicitly name siblings or say what it is not.

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

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

Usage context is implied by scope: choose this tool when regression tests need to be filtered by functional areas. There is no explicit when-to-use/when-not-to-use guidance or comparison with bearq_run_regression_tests and bearq_run_test_cases, leaving some routing to inference.

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

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

The description says 'Cancels a running task,' which is a state-changing operation, while annotations declare readOnlyHint=true and destructiveHint=false. This directly contradicts the tool's actual semantics and gives an agent conflicting safety signals.

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

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

The definition is short and front-loaded with the core action. The 'Toolset' and 'Parameters' sections are mildly redundant with metadata already present in the schema, but they do not significantly bloat the definition.

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

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

For a single-parameter tool without an output schema, complete coverage should be easy, but the description omits side effects, reversibility, and behavior on already-finished tasks. More importantly, the readOnlyHint contradiction makes the overall context unreliable for an agent.

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

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

Schema description coverage is 100%, and the schema already documents taskId with type, bounds, required flag, and the same description as the tool description's parameter line. The description adds no meaning beyond what the schema provides, so the baseline of 3 applies.

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

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

The description uses a specific verb ('Cancels') and a clear object ('a running task'), making the operation unmistakable. It also differentiates this tool from siblings like bearq_get_task, bearq_get_task_status, and bearq_wait_for_task, which are read/wait operations, and bearq_run_* tools, which start tasks.

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

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

The description implies the tool is for running tasks, but it gives no explicit guidance on when to use it versus alternatives, whether completed tasks can be cancelled, or whether a status check should precede cancellation. No exclusions or preconditions are mentioned.

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

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

Beyond the readOnly/idempotent annotations, the description reveals the blocking nature, the terminal-state conditions, the timeout possibility, and the verbatim SSE event sequence returned. This is meaningful behavioral context an agent needs to decide if calling this tool is appropriate.

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

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

Two tightly packed sentences deliver the core behavior, the trigger conditions, the return shape, and the sibling alternative. The parameter listing is minimal and redundant but harmless. No wasted words.

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

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

Given a single parameter, clear blocking semantics, stated return content, and a sibling pointer, the description covers everything an agent needs to decide whether to invoke it and what to expect in response. The lack of an output schema is mitigated by the explicit SSE event description.

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

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

Schema coverage is 100% and the description repeats the schema's parameter text ('BearQ task ID') without adding new meaning. No additional format, constraints, or usage nuance is provided beyond what the JSON schema already documents.

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

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

The description states a specific verb ('Blocks') and resource ('BearQ task'), plus the exact return payload ('full ordered sequence of SSE events... verbatim'). It clearly distinguishes this from sibling bearq_get_task_status by framing it as the blocking/long-polling counterpart.

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

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

It explicitly explains when to use the tool ('Blocks for the lifetime of the task') and when not to, recommending 'bearq_get_task_status' for a quick check. This gives an agent actionable routing guidance without ambiguity.

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

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), and the description adds useful output expectations: a JSON object with build details, stability metrics, and whether project targets are met. This goes beyond the schema and enriches the behavioral picture without contradicting the annotations.

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

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

The description is well-structured with clear sections for Parameters, Output Description, Use Cases, Examples, and Hints. While it is somewhat verbose and duplicates schema parameter text, every section earns its place with actionable guidance (e.g., examples, expected output, hints). It is not as terse as ideal but remains effective.

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

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

For a simple read-only get-by-ID tool, the definition covers the required and optional params, provides output shape, and offers concrete use cases plus a hint on locating build IDs. It lacks error-handling details, but given the annotations, simple interface, and 100% schema coverage, it is sufficiently complete for an agent to invoke correctly.

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

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

Both parameters have thorough descriptions in the input schema (100% schema description coverage). The tool description repeats these parameter descriptions but does not add new semantic details such as formats, allowed values, or default behaviors, so it stays at the baseline of 3.

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

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

The description opens with 'Get more details for a specific build by its ID' – a clear verb+object statement that names the resource (build) and the lookup mechanism (by ID). It distinguishes itself from sibling tools like bugsnag_get_release by focusing on builds, and the title reinforces the purpose.

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

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

The Use Cases section gives explicit scenarios (view build metadata, analyze error spikes, check stability targets) and the hint references the 'List builds' tool as a prerequisite for obtaining build IDs. However, it does not explicitly state when not to use this tool or compare it to alternatives like get_release, so it stops short of a perfect score.

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

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

Annotations already mark the tool read-only and idempotent. The description adds valuable context beyond those annotations: the tool allows other BugSnag tools to be called without projectId, and the distinction between returning a project vs. returning nothing changes how subsequent tools must be invoked.

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

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

The description is front-loaded with the core purpose and then organized into Toolset, Parameters, Use Cases, and Hints. It is longer than strictly necessary, but each section earns its place by helping an agent decide when and how to use the tool.

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

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

For a parameterless tool with comprehensive hover annotations and no output schema, the description fully covers what the agent needs: what the tool does, what return scenarios mean, and what alternative to call if no current project is set. Nothing important is missing.

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

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

With zero parameters and 100% schema description coverage, there is nothing for the description to add about parameter meaning. The description confirms 'Parameters: None' and focuses on behavioral context, which is appropriate.

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

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

The description states a specific verb and resource: 'Retrieve the current project on which tools should operate by default.' It clearly distinguishes this from the sibling bugsnag_list_projects by focusing on the 'current' default project rather than all accessible projects.

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

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

The Use Cases and Hints sections give explicit guidance: call this to understand whether a current project has been set, expect other BugSnag tools to use that project if one is returned, and fall back to listing projects if none is returned. It also explains when an explicit project ID will be required instead.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it specifies the returned fields (error_details, latest_event, pivots, url), notes that filters narrow summaries further, and instructs the agent to show the dashboard URL to the user. No annotation contradiction exists.

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

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

The description is front-loaded with a clear purpose sentence and uses well-labeled sections for parameters, output, use cases, examples, and hints. It is longer than strictly necessary because the parameter section largely duplicates the input schema and the example is generic, but the extra sections provide actionable agent guidance overall.

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

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

The description is complete for a read-only retrieval tool: it enumerates output fields despite no output schema, gives concrete workflows for error investigation, explains how to get error IDs, names the event-detail alternative, and tells the agent to surface the dashboard URL. Nothing critical for correct invocation is missing.

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

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

Input schema coverage is 100%, and the description largely restates schema text, which establishes the baseline of 3. It goes slightly further by clarifying that filters narrow 'summaries further', explaining when to reuse filters, directing users to the List Project Event Filters tool for available filter fields, and documenting time format options.

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

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

States a specific verb and resource — 'Get full details on an error' — and clarifies the scope: aggregated data across all events plus details of the latest event. This clearly distinguishes it from event-level or error-list siblings like bugsnag_get_event and bugsnag_list_project_errors.

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

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

Provides explicit when-to-use guidance: investigate errors found via List Project Errors, use after filtering, and pass the same filters to restrict results. It also names the alternative — 'Use Get Event Details tool if you need detailed information about a specific event rather than the aggregated error' — making the choice unambiguous.

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

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

Annotations already cover the safe read-only, idempotent, non-destructive profile, and the description is consistent with that profile. It adds some return-content context (stack traces, metadata, context) but does not disclose anything else such as authentication requirements, rate limits, or side effects.

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

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

The description is front-loaded with the purpose and uses concise sections and a JSON example. The explicit parameter list is redundant with the schema, but the overall size is acceptable.

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

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

For a simple two-parameter read with no output schema, the description supplies the essential details: required eventId, optional projectId behavior, an example, and expected response contents. It is nearly complete, only lacking guidance about how to discover eventId or how this tool differs from similar event/error tools.

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

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

Schema coverage is 100%, so the parameter section mostly duplicates the schema. The example adds a concrete eventId format ('6863e2af012caf1d5c320000') and the expected-output description clarifies what the response contains, which goes beyond the schema.

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

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

The first sentence names a specific verb and resource ('Get detailed information about a specific event'), and the Use Cases section clarifies that this returns full event details including stack traces. It is clear, but it does not explicitly differentiate itself from sibling tools like bugsnag_get_event_details_from_dashboard_url or bugsnag_get_events_on_an_error.

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

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

The use case implies the tool is for retrieving a single event's full details, and the example encodes the expected input. However, there is no guidance on when to prefer this over nearby siblings, no exclusions, and no relationship to list-events or error-detail tools.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value beyond annotations by specifying the required URL structure (project slug in path, event_id in query) and what the expected output contains (stack trace, metadata, context). No contradiction with annotations.

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

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

The description is well-structured with clear sections (Toolset, Parameters, Use Cases, Examples, Hints) and the core purpose is front-loaded. Some redundancy exists between Use Cases and Hints, and the parameter section repeats the schema verbatim, but overall it remains focused and scannable.

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

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

For a low-complexity tool with one parameter and strong annotations, the description is sufficiently complete. It explains expected output, input requirements, and common use cases. It could be more thorough about error behavior or exact parsing rules, but nothing critical is missing for an agent to invoke the tool correctly.

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

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

Schema coverage is 100% for the single 'link' parameter, so baseline is 3. The description adds meaning beyond the schema with a concrete example URL and hints about the necessary components, which helps an agent construct a valid input. This extra guidance justifies a score above baseline.

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

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

The description uses a specific verb ('Get detailed information') and a precise resource ('specific event using its dashboard URL'). It clearly differentiates from sibling tools like bugsnag_get_event by emphasizing the URL-based access path and explicitly noting this avoids needing separate project/event IDs.

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

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

The description provides clear context through Use Cases and Hints: it is intended for dashboard URLs from users/notifications, shared links, or quick lookups. It implies alternatives (separate project/event ID tools) by saying this works 'without needing separate project and event IDs', but does not explicitly name when-not-to-use alternatives.

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

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

The description adds meaningful behavioral details beyond the annotations: default filters (event.since=30d, error.status=open), pagination via nextUrl with a warning not to construct it manually, and the expected output (ordered by timestamp with stack traces, breadcrumbs, metadata, and context).

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

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

The opening sentence is direct and useful, and the Use Cases/Expected Output sections add value. However, the Parameters section duplicates the schema descriptions almost verbatim, making the definition longer than necessary.

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

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

Despite lacking an output schema, the description provides expected output format, default filters, pagination guidance, filter discovery advice, and a realistic example. It is largely complete for correct invocation, though it could better differentiate this list endpoint from single-event retrieval tools.

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

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

Schema description coverage is 100%, so the baseline is 3. The Parameters section largely repeats the schema's descriptions verbatim and does not add substantial new meaning beyond the example call and expected output.

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

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

The description states a specific verb and resource: 'Gets a list of events that have grouped into the specified error.' This clearly distinguishes it from tools like bugsnag_get_error or bugsnag_get_event, though it does not explicitly name those siblings.

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

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

The Use Cases section provides a concrete scenario: retrieving all events for comparison of stack traces, breadcrumbs, and metadata. This gives clear context for when the tool is appropriate, though it does not explicitly describe when-not-to-use it or name alternatives.

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

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

Annotations already cover readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds useful behavioral context: projectId is used to set the current project for BugSnag tools, the expected output is an array of endpoint URL patterns, and hints explain OpenAPI templating and wildcard syntax. No contradictions with annotations.

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

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

The description is well-organized into sections with the core purpose front-loaded. The parameter section duplicates the schema but the use cases, example, and hints all add value. Slightly verbose, but every section serves a clear function.

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

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

For a single-optional-parameter read tool with no output schema, the description covers the essentials: an example call, expected output shape, and interpretation hints. The only notable gap is what happens if no current project is set and no projectId is supplied, but the optionality note partially addresses this.

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

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

Schema coverage is 100%, and the parameter description in the tool mirrors the schema description exactly. No additional parameter-level semantics are provided, so the baseline of 3 applies. The grouping-pattern hints relate to the returned data, not to the parameter.

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

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

The description states a specific verb ('Get') and resource ('network endpoint grouping rules'), scoped to 'a project'. It clearly differentiates from the sibling bugsnag_set_network_endpoint_groupings by verb and from other BugSnag getters by resource, so an agent can tell what it does without opening the schema.

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

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

The Use Cases section gives three explicit scenarios: viewing current configuration, understanding grouping, and checking patterns before making updates. This clearly implies when to use the tool, e.g. before calling the set tool, but it does not explicitly name alternatives or state when not to use it. That prevents a top score.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate safety. It adds value by describing the output contents (stability metrics, project targets) and notes that projectId can set the current project for BugSnag tools, which is useful behavioral context.

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

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

The description is well-structured with clear sections and front-loads the core purpose. It is somewhat redundant, repeating the JSON output description in both the Output Description and Expected Output, but the overall organization helps an agent parse the information efficiently.

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

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

For a simple get-by-ID tool with one required parameter and no output schema, the description is complete: it explains what the output contains, gives concrete use cases, provides an example, and tells the agent where to find release IDs. Nothing essential for calling this tool correctly is missing.

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

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

Schema description coverage is 100%, and the parameter descriptions in the tool description are near-verbatim copies of the schema descriptions. The example and hint add usability value, but the description does not meaningfully expand on the schema's parameter semantics.

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

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

The description opens with a specific verb and resource: "Get more details for a specific release by its ID," and names what is included (source control information, associated builds). This clearly distinguishes it from siblings like bugsnag_list_releases and bugsnag_get_build.

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

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

The description provides use cases and explicitly hints that "Release IDs can be found using the List releases tool," which gives clear routing context. It does not explicitly state when not to use this tool versus siblings, but the ID-based scope and sibling naming make the intended usage clear.

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

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

Annotations already declare readOnly and idempotent, and the description adds meaningful behavioral detail: it specifies that statistics include p50/p75/p90/p95/p99, that the response provides category and performance target info, and that span group IDs are automatically URL-encoded. This goes beyond the annotation safety profile without contradicting it.

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

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

The description is well-structured and front-loaded: purpose first, then parameters, use cases, examples, and hints. It is somewhat long and repeats some schema parameter descriptions, but each section serves a practical purpose and the examples are directly actionable. It earns its length for a tool with no output schema.

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

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

Given the absence of an output schema, the description does an excellent job of explaining what the agent will receive: statistics, category, performance target info, and filtered results. It also covers the workflow (discover span groups first), filter discovery, parameter defaults, and URL-encoding behavior. Nothing critical is missing for successful invocation.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds genuine value with the URL-encoding hint for spanGroupId, a concrete default filter value, an example of device.browser_name filtering, and a pointer to List Trace Fields for discovering filter fields. These details help agents use the parameters correctly beyond the schema text.

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

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

The description opens with a specific verb+resource: 'Get detailed performance metrics for a specific span group.' The word 'specific' distinguishes it from bugsnag_list_span_groups, and the performance-metrics focus separates it from other get tools like bugsnag_get_trace or bugsnag_get_error. This is clear and unambiguous.

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

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

The 'Use Cases' section clearly states when to use the tool (view percentiles, check performance targets, monitor span count). Hints provide routing guidance: use List Span Groups first to discover IDs and List Trace Fields to discover filters. It does not explicitly enumerate when-not-to-use alternatives, but the context is clear enough.

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

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

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail beyond that: pagination via nextUrl with an explicit warning not to construct the URL manually, default page size, target-span focusing, and the return shape (array of spans with timing and hierarchy). This exceeds what the annotations alone provide.

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

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

The description is well-structured with headings, use cases, examples, and hints, and the core action is front-loaded. However, it contains a full parameter list that duplicates the input schema and several hints that restate the examples, making it longer than necessary.

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

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

For a tool with no output schema, the description provides enough context: required parameters, optional pagination and target-span behavior, example invocations, and expected response shape. It could be more precise about the response structure, but an agent has the information needed to select and call the tool.

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

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

Schema description coverage is 100%, so the schema already documents every parameter. The description repeats those definitions and adds illustrative examples, but it does not materially expand on the schema's parameter explanations.

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

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

The opening line 'Get all spans within a specific trace' names a specific verb and resource, so it is immediately clear what the tool returns. It does not explicitly distinguish itself from sibling BugSnag span tools such as bugsnag_list_spans, though 'specific trace' narrows the scope.

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

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

The description provides clear use cases (debugging slow requests, understanding request flow, identifying bottlenecks) and hints about narrowing the time window and focusing on a target span. It does not name sibling alternatives or state when not to use it, but the context is strong enough for an agent to decide.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds substantial behavioral detail: default filters, pagination mechanics, nextUrl usage rules, the requirement not to modify the URL, the meaning of output fields, and the possibility of an empty result set. This goes well beyond the annotations and schema.

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

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

The description is long but well-structured into Parameters, Use Cases, Examples, and Hints. Each section earns its place: examples illustrate complex filter syntax, hints cover pagination pitfalls and empty results, and the structure is scannable. There is minor duplication of schema details, but it is purposeful reinforcement rather than filler.

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

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

For a tool with 6 parameters, nested filter objects, no output schema, and non-obvious pagination behavior, the description is remarkably complete. It covers all parameters, defaults, filter discovery, time format options, AND logic, output structure, next-page handling, and even the no-results case. An agent has everything needed to invoke and paginate correctly.

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

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

Although schema coverage is 100%, the description adds real semantic value to every parameter: projectId's optionality and current-project behavior, filter format and time syntax, sort/direction/perPage defaults, and the strict rules around nextUrl. The examples demonstrate exact filter JSON structures, making parameter usage far clearer than the schema alone.

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

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

The description opens with a specific verb-resource pair: 'List and search errors in a project using customizable filters and pagination.' It clearly identifies what the tool does, but it does not explicitly differentiate itself from sibling tools like bugsnag_get_error or bugsnag_list_events_on_an_error, so the distinction is implied rather than stated.

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

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

The description provides concrete use cases (debugging recent errors, generating reports, monitoring trends) and explicitly instructs to use the List Project Event Filters tool first to discover valid filters. It does not state when to prefer another error-related tool instead, so no explicit exclusions or sibling selection guidance is present.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description is consistent with them. It adds useful behavioral context beyond annotations by noting that an optional projectId is 'used to set the current project for BugSnag tools' and by describing the expected EventField response shape with display_id and filter/pivot options.

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

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

The one-sentence summary is front-loaded and the use cases, example, expected output, and hints are organized in scannable sections. The Parameters section duplicates the schema's projectId description, which adds some redundancy, but the overall structure remains efficient.

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

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

There is no output schema, so the description compensates by stating the expected response ('JSON array of EventField objects') and the key output fields. It also explains the optional parameter semantics, provides an empty-input example, and connects the result to the next step via the display_id hint, making the tool fully actionable.

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

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

Schema coverage is 100% and the description's Parameters section restates the same projectId explanation already present in the input schema without adding new meaning. With full schema coverage, the baseline of 3 applies because the description offers no additional parameter nuance.

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

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

The description opens with 'Get available event filter fields for a project,' a specific verb-object-resource statement that matches the tool's name and makes its scope obvious. It further distinguishes itself by framing the output as filter fields to be used before querying errors, which separates it from sibling error/event query tools.

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

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

The description gives explicit guidance: 'Use this tool before the List Errors or Get Error tools to understand available filters' and lists discovery use cases. It does not state when not to use it or mention direct alternatives such as bugsnag_list_trace_fields, so it stops short of a full when/when-not matrix.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavior beyond that: access is scoped to projects the current user can see, the apiKey acts as a lookup filter, and returned project IDs can be passed to other BugSnag tools. Pagination and response shape are not disclosed, but this is a minor gap for a simple read-only list.

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

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

The main sentence is front-loaded and the rest is organized into short, scannable sections. The 'Parameters' bullet mostly duplicates the schema, and 'Toolset' adds little, but the overall length is reasonable and each remaining section contributes useful context.

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

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

For a one-parameter, read-only list tool with strong annotations, the description is largely complete: it states scope, the optional filter, use cases, and how results can be consumed by other tools. It does not describe pagination or the exact response fields, but the hint about project IDs covers the most important downstream need.

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

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

Schema description coverage is 100%, so the schema already fully documents the optional apiKey parameter. The description adds minor context by linking the key to 'the user's code,' but it repeats the schema text and does not introduce format, constraints, or examples.

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

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

The description opens with a specific verb and resource: 'List all projects in the organization that the current user has access to.' It also clearly distinguishes the alternate API-key-based lookup behavior, so an agent understands both the default action and the optional filter.

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

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

The 'Use Cases' section gives explicit scenarios: getting an overview of all projects and locating a project by API key from user code. The 'Hints' section adds downstream guidance that project IDs can be reused with other tools, but it does not explicitly contrast this tool with siblings like bugsnag_get_current_project.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context beyond these: pagination semantics for nextUrl, default values for releaseStage and visibleOnly, the projectId side effect of setting the current project, and the output shape with next-page URL. All behavior is disclosed consistently.

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

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

The description is well-organized with clear sections (Toolset, Parameters, Output, Use Cases, Examples, Hints). It is longer than necessary, but each section earns its place and the key information is front-loaded in the first sentence.

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

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

For a read-only listing tool with five all-optional parameters, no output schema, and rich annotations, the description is fully sufficient. It documents every parameter, provides three worked examples, describes the output format, and gives hints for follow-up tools—nothing an agent needs to call it correctly is missing.

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

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

Schema description coverage is 100%, so the baseline is 3. The description goes beyond the schema by providing concrete examples (staging filter, nextUrl usage) and restating defaults and constraints in context, which helps an agent apply parameters correctly without opening the schema.

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

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

The description clearly states the action ('List releases for a project') with a specific verb and resource. The 'Toolset: Releases' label and the hint pointing to the 'Get Release tool' for more details help distinguish this listing tool from its sibling bugsnag_get_release.

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

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

The description provides explicit use cases ('View recent releases to correlate with error spikes', 'Filter releases by stage') and a hint to use the Get Release tool when more detail on a specific release is needed. This gives clear when-to-use guidance and names an alternative.

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

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

Annotations already mark this as read-only, idempotent, and non-destructive, so the description mainly adds value with behavioral caveats: the default span.since=7d filter, the nextUrl restriction that only prior output values are valid and must not be hand-constructed, and the projectId side effect of setting the current BugSnag project. These go beyond the structured annotations.

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

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

The description is well organized with headings, a front-loaded purpose, use cases, examples, and hints, making it easy to scan. However, the Parameters section duplicates the schema verbatim, adding length without new information; the same content could be tighter.

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

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

For a list tool with no output schema, the description covers invocation-relevant context well: defaults, pagination through nextUrl, filter format, example payloads, and expected array output. It does not enumerate response fields, but it provides enough for an agent to call the tool correctly.

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

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

Schema coverage is 100%, and the description largely restates the schema's parameter descriptions for sort, direction, perPage, filters, and nextUrl rather than adding new semantic detail. It does add working examples and sorting hints, which are useful, but they are supplements rather than necessary compensation for missing schema coverage.

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

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

The description opens with a specific verb and resource: 'List span groups (operations) tracked for performance monitoring'. This clearly identifies the tool as a list operation over span groups and distinguishes it from sibling tools like bugsnag_get_span_group or bugsnag_list_spans.

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

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

The Use Cases enumerate concrete scenarios: viewing all operations, finding slow operations via duration sorts, and filtering starred groups. Hints recommend duration_p95/duration_p99 for slowest operations, and the description points to List Trace Fields as the place to discover filter fields. It does not explicitly contrast with bugsnag_list_spans or bugsnag_get_span_group, 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.

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond the annotations, such as how nextUrl pagination works, the default span.since=7d filter, and expected output examples. There is no contradiction with the annotations.

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

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

The description is well-structured with clear sections: Toolset, Parameters, Use Cases, Examples, and Hints. It is somewhat longer than necessary because the Parameters section largely repeats the input schema, but each remaining section contributes practical value for an agent.

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

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

For a tool with 7 parameters, nested filter objects, and no output schema, the description provides sufficient guidance for correct invocation: concrete examples, expected output descriptions, pagination behavior, and a pointer to List Trace Fields for filter discovery. Nothing that would block selection or calling is missing.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaning through concrete example payloads, explains the pagination contract for nextUrl, and offers practical hints like sorting by duration descending to find the slowest instances. This goes beyond simply restating parameter names.

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

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

The opening sentence, 'Get individual spans belonging to a span group,' names a specific verb and resource, and the modifier 'individual' distinguishes this from sibling tools like bugsnag_list_span_groups and bugsnag_get_span_group. An agent can identify the target resource without needing to inspect other tool definitions.

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

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

The Use Cases section provides explicit scenarios for when this tool is appropriate: analyzing individual slow operations, debugging performance issues via specific traces, and finding patterns in operation attributes. It does not explicitly state exclusions or alternatives, so it falls just 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.

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context by specifying the expected output as an array of field names and types and clarifying that trace fields are custom attributes added to spans. No contradiction with annotations.

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

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

The description is well-structured with sections and a front-loaded summary, making it scannable. However, it contains redundancy: the parameter bullet duplicates the schema, and the use cases and hints overlap with the opening sentence. It could be tighter without losing value.

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

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

For a simple optional-parameter, read-only list tool with no output schema, the description covers the core purpose, usage scenarios, and expected output format. It is complete enough for an agent to select and call the tool correctly, though it does not discuss edge cases such as behavior when no project is set.

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

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

Schema description coverage is 100%, and the description's Parameters section essentially restates the same projectId text already present in the schema. The description adds no new meaning about the parameter, so the baseline of 3 is appropriate.

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

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

The description opens with 'Get available trace fields/attributes for filtering', which names a specific verb and resource and states the purpose. It is distinguishable from sibling list tools because it targets trace fields specifically, though it does not explicitly contrast itself with alternatives like bugsnag_list_project_event_filters.

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

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

Use Cases explicitly state when to use the tool: finding custom attributes for performance filtering, understanding trace metadata, and building dynamic filters. The Hints section reinforces that the returned fields should be reused in other performance queries, but it does not mention when not to use this tool or name an alternative.

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

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

Beyond the annotations, the description explicitly states a critical behavioral trait: 'This replaces all existing patterns - include all patterns you want to keep.' This warns the agent about the overwrite semantic, which is exactly the kind of behavioral context that matters at invocation time. The idempotentHint and destructiveHint annotations are not contradicted; the description strengthens the agent's understanding of side effects.

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

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

The description is long but well-structured with clear sections: Toolset, Parameters, Use Cases, Examples, and Hints. The front-loaded summary sentence immediately conveys the core action. Some content is redundant with the schema and the repeated 'Expected Output' lines add bulk, but given the syntax complexity, the length is justified.

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

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

For a tool with no output schema, the description provides expected outputs in examples and covers the essential operational concern of pattern replacement. It also includes syntax rules, examples, and workflow hints. It stops short of specifying error cases or exact response structure, but the agent has enough context to invoke the tool correctly.

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

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

Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds value by providing concrete examples, colon-to-brace conversion guidance, wildcard usage, and hints about project context. It does not introduce new parameter semantics beyond the schema, but the examples significantly improve practical understanding.

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

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

The description states a clear, specific operation: 'Set the network endpoint grouping rules for a project.' This immediately differentiates the tool from the sibling bugsnag_get_network_endpoint_groupings and clarifies the resource being acted upon. The title and Toolset label additionally anchor it in BugSnag performance monitoring.

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

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

The description provides explicit use cases and hints that explain when to apply the tool, such as consolidating API endpoints and grouping dynamic URLs. It also advises using 'Get Network Grouping' first, which orients the agent toward the read-before-write workflow. It does not give formal when-not-to-use guidance, but the context is clear.

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

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

Annotations already signal readOnlyHint=false; the description adds meaningful behavior such as 'Snoozing temporarily silences an error until the specified reopen condition is met' and warns that invalid operations may be rejected. It doesn't cover auth/rate limits, but the mutation semantics are disclosed.

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

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

Well-structured with a one-line summary, Use Cases, Examples, and Hints, and front-loaded purpose. The Parameters section largely duplicates the schema, adding some redundancy, but the examples and hints justify the length.

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

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

For a nested-parameter, nine-operation mutation tool with no output schema, the description is thorough: every operation is covered by an example, conditional requirements are spelled out, and expected outputs are stated. An agent has enough to construct valid calls.

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

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

Schema description coverage is 100%, so baseline is 3; the description pulls ahead with examples showing exact JSON payloads for every operation class and Hints that map each reopenIf variant to its required fields (seconds, additionalUsers, occurrences+hours, additionalOccurrences). This adds compositional knowledge beyond the schema.

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

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

Opens with a specific verb+resource ('Update the status of an error') and immediately enumerates exact operations in Use Cases (open/fixed/ignored, discard, severity, snooze, link issue). The tool name and BugSnag sibling set make it the clear mutation counterpart to read-only tools like bugsnag_get_error and bugsnag_list_project_errors.

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

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

Explicit 'Use Cases' list gives concrete scenarios (mark fixed, snooze, discard) that tell an agent when to invoke it. It does not name alternatives or state when not to use it, which would be the next step up.

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

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

The description says the tool 'Creates' a configuration, while the annotations declare readOnlyHint: true. This is a direct contradiction about whether the operation mutates state. The description also provides no additional behavioral context such as authorization requirements, idempotency implications, or response behavior.

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

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

The purpose sentence is front-loaded and concise, but the parameter section duplicates the input schema's descriptions, which is redundant. The toolset line provides marginal context, yet several lines add little information beyond what an agent already has from the schema.

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

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

For a create operation with four parameters and no output schema, the description leaves out when to use it, what effects occur, and any details about the JSON config structure or token format beyond the schema. The readOnlyHint contradiction further undermines an agent's ability to understand the operation's true behavior.

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

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

Schema description coverage is 100%, and the parameter list only repeats the schema's own descriptions without adding syntax, format examples, or constraints. The description adds no semantic value beyond the structured schema, so the baseline 3 applies.

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

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

The description opens with 'Creates a remote system configuration in Collaborator', a specific verb plus resource, and gives concrete examples (Bitbucket, GitHub). The create action is implicitly distinct from sibling tools like edit, delete, update, and test-connection for remote system configurations.

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

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

There is no guidance on when to choose this tool over alternatives such as collaborator_edit_remote_system_configuration or collaborator_test_remote_system_configuration_connection. The 'Toolset' label provides weak context but no conditions, prerequisites, or exclusions.

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

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

The description states a state-changing action ('Creates a new review'), while annotations declare readOnlyHint=true and idempotentHint=true. This is a direct contradiction: readOnlyHint indicates no side effects, but creation is a side effect. The description also does not explain creation results, return values, or required permissions, but the contradiction alone forces a minimum score.

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

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

The purpose statement is front-loaded and the layout is scannable, but the Parameter section unnecessarily repeats the full schema content, including each default. This duplication adds bulk without informational value, though the overall length is still modest. Around half the sentences could be removed without loss.

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

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

For a tool with zero required parameters and simple string inputs, the description covers the invocation surface: purpose, toolset, and all parameter defaults. However, it omits any return/output description and, due to the annotation conflict, the side-effect profile is ambiguous. This is minimally viable but not fully complete for an agent.

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

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

Schema description coverage is 100%, and the description's parameter list duplicates the schema's names, descriptions, optionality, and defaults almost verbatim. It adds no new meaning beyond the schema; 'All parameters are optional' is already encoded by required: [] and each field's Optional note. Therefore baseline 3 applies.

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

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

The description opens with a concrete verb-object phrase, 'Creates a new review in Collaborator,' which directly states the tool's action and resource. The toolset tag and optional-parameter note reinforce that this is a creation operation, distinguishing it from sibling read/reject tools like collaborator_get_reviews or collaborator_reject_review.

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

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

There is no explicit when-to-use or when-not-to-use guidance and no named alternatives. The phrase 'Creates a new review' implies the intended use, and 'All parameters are optional' clarifies there are no prerequisites, but the description never tells the agent when to prefer this over collaborator_reviewservice_action or find/get operations. This is implied usage rather than explicit direction.

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

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

The description states the tool 'Deletes' a configuration, which is a mutating and destructive operation, but the annotations declare readOnlyHint=true and destructiveHint=false. This is a direct contradiction that makes the tool's actual behavior unreliable for an agent.

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

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

The core action is stated in one clear, front-loaded sentence. The additional Toolset and Parameters blocks are somewhat redundant with the structured data but do not make the description excessively long.

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

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

Even though the tool has only one parameter, the description omits important behavioral context such as whether deletion is reversible, what happens to dependent data, or required permissions. The annotations further mislabel the operation as read-only, making the overall definition unreliable.

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

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

Schema description coverage is 100%, and the description merely repeats the schema text: 'ID of the remote system Configuration to delete.' The parameter is already fully documented in the schema, so the description adds little semantic value.

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

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

The description uses a specific verb 'Deletes' and identifies the exact resource, 'remote system configuration in Collaborator', with the key selector 'by its ID'. This clearly differentiates it from sibling tools like create, edit, or test remote system configuration.

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

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

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The 'Toolset' label only names a category without explaining when deletion is appropriate.

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

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

Annotation Contradiction: the description says 'Edits parameters' and the tool is an edit operation, but the annotations declare readOnlyHint=true, implying the tool does not modify state. This is a direct and serious inconsistency.

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

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

The opening sentence is clear and front-loaded, and the post-creation constraint is useful. But the description then duplicates the entire parameter schema verbatim, which adds length without adding information and contributes to the reviewTemplateId inconsistency.

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

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

The definition omits return behavior and gives no guidance on what the response looks like. More importantly, the contradictory 'only title and config are editable' note versus the reviewTemplateId parameter leaves a critical ambiguity, and no detail is given about what the config JSON should contain. This is not sufficient for reliable agent invocation.

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

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

Schema description coverage is 100%, so the schema already documents all four parameters. However, the description's statement that 'Only title and config are editable after creation' directly conflicts with its own parameter list, which includes reviewTemplateId as an editable parameter, leaving the agent uncertain about valid inputs. It also provides no extra detail about the JSON config format.

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

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

The description uses a specific verb ('Edits') and identifies the exact resource ('parameters of an existing remote system configuration in Collaborator'). It is clearly distinct from creating, deleting, or testing a configuration, though it does not explicitly name sibling alternatives.

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

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

The description establishes that this tool is for editing an existing configuration and notes a key constraint: only title and config are editable after creation. However, it does not explicitly guide the agent to create/delete/test siblings when those operations are more appropriate, relying instead on the tool name and context.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond that: it does not mention return format, not-found behavior, or any operational caveats, so it provides little transparency beyond the annotations.

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

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

The description is short and front-loaded, with a single clear purpose statement followed by a small toolset label and parameter list. The parameter list is somewhat redundant with the schema, but it is compact and does not introduce bloat.

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

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

For a one-parameter lookup with rich safety annotations, the description is mostly complete. It lacks an explicit statement of the return value (relevant since there is no output schema) and any error/not-found behavior, but given the tool's simplicity, these omissions are minor.

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

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

The input schema has 100% description coverage for reviewId, and the description repeats the exact phrase 'The Collaborator review ID to find.' No additional meaning is added, so the baseline score of 3 applies.

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

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

The description opens with a specific verb ('Finds') and resource ('a review in Collaborator') and clearly identifies the selection criterion ('by its review ID'). This is immediately distinct from the list-oriented sibling collaborator_get_reviews and other review actions, so an agent can tell what it does.

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

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

The 'by its review ID' phrasing implies this is for looking up a single known review, but the description never explicitly contrasts it with collaborator_get_reviews or states that it should be used when an ID is already known. Usage context is implied, not spelled out.

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

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

Annotations already establish that this is read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds one useful behavioral nuance: all parameters are optional and only provided ones are sent. It does not disclose return shape, pagination, default behavior, or authentication requirements, but the annotation coverage lowers the burden.

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

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

The opening sentence is clear and front-loaded, but the description then duplicates every parameter already present in the input schema. The 'Toolset: Review Management' line adds slight structure, but the repeated parameter listing is redundant and makes the description longer than necessary.

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

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

For a read-only list/filter tool with 7 optional parameters and no output schema, the description covers the filtering semantics adequately via schema descriptions. However, it does not explain what fullInfo changes, what values reviewPhase accepts, how the filters combine, or what the returned review objects look like. This incomplete context may leave an agent uncertain about invocation side effects.

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

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

Input schema description coverage is 100%, so the schema already documents every parameter. The description repeats the parameter list but adds little beyond the sentence that all parameters are optional and only provided ones are sent, which is already implied by zero required parameters. Baseline 3 is appropriate.

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

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

The description states a specific action ('Retrieves reviews from Collaborator') and names the underlying service method. The plural 'reviews' and tool name distinguish it from the sibling find_review_by_id, but it does not explicitly contrast itself with that sibling.

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

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

There is no guidance on when to use this tool versus collaborator_find_review_by_id, collaborator_reviewservice_action, or any other sibling. The description does not mention exclusions or alternatives, leaving the agent to infer selection criteria from the name alone.

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

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

The description states 'Rejects a review,' which implies a state-changing action, but the annotations declare readOnlyHint=true and idempotentHint=true. Rejecting a review is not read-only, so the description directly contradicts the annotation metadata. No additional behavioral context such as side effects, permissions, or irreversibility is provided.

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

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

The core description is one concise, front-loaded sentence that clearly states the action and key inputs. The subsequent parameter block and toolset line add some redundancy with the schema but do not make the description bloated or hard to parse.

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

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

This is a mutation-like operation with no output schema and no explanation of the result or side effects of rejecting a review. The annotation contradiction makes the behavioral model unreliable, leaving an agent unsure whether the tool modifies state. A simple 2-parameter schema does not compensate for the missing usage and behavioral context.

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

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

Schema description coverage is 100%, and the description's parameter list simply duplicates the schema's field names and descriptions. It adds no new semantic detail such as value formats, constraints, or relationships between reviewId and reason. The baseline of 3 is appropriate because the schema already documents both parameters.

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

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

The description opens with a specific verb and resource: 'Rejects a review in Collaborator'. It also names the required inputs, 'by its review ID and reason', making the operation unambiguous. Among many sibling tools, this is clearly the reject-review operation rather than create, find, or get reviews.

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

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

The description gives no guidance on when to use this tool versus alternatives such as collaborator_reviewservice_action, collaborator_get_reviews, or collaborator_find_review_by_id. The 'Toolset: Review Management' line only categorizes the tool; it does not explain conditions for use or exclusions.

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

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

The description contradicts the annotations: readOnlyHint=true while the described generic invocation plus schema actions such as cancel, reopen, and uncancel imply state-changing behavior. It also fails to disclose side effects, preconditions, or failures for the supported action enum.

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

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

The text is short and the core purpose is front-loaded, but it wastes space repeating parameter metadata from the schema and the Toolset line, and it front-loads an inaccurate sentence. The structure is neat but the content is not reliable.

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

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

For a generic dispatcher with a nested free-form args object and no output schema, the description is severely incomplete: it omits valid action semantics, return values, error behavior, and examples. An agent cannot determine how to construct args for any of the four actual enum values.

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

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

Schema description coverage is 0% and the description does not compensate for the actual enum actions. It only documents reviewId/until for finishReviewPhase and waitOnPhase, which are not valid action values, leaving args for moveReviewToAnnotatePhase, cancel, reopen, and uncancel completely unspecified.

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

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

The description says it can 'Invoke any ReviewService method by name and arguments,' which identifies a generic dispatch tool on a specific service, but 'any method' is contradicted by the action enum and by mentioning finishReviewPhase/waitOnPhase that are not in that enum. It does not distinguish this generic action from the dedicated collaborator_* review tools.

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

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

No explicit when-to-use or alternative selection guidance is provided. The only usage detail is for two methods absent from the schema enum, and there is no indication that dedicated tools should be preferred for common operations such as creating or rejecting a review.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only the connection-testing action and does not disclose response/outcome behavior, potential network dependencies, or whether credentials are validated.

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

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

The core definition is one clear sentence, and the toolset/parameter sections are compact. The parameter block is redundant with the schema but does not bloat the text enough to reduce usability.

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

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

For a one-parameter, safely annotated operation this is largely sufficient to invoke correctly. Still, with no output schema, the description does not explain what a successful/failed connection test returns or how the result is expressed.

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

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

Schema description coverage is 100% and the description repeats the id meaning verbatim without adding additional type, format, or source guidance. Baseline 3 is appropriate because the schema does all the explanatory work.

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

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

The description uses a specific verb ('Tests') and precise resource ('the connection for a remote system configuration in Collaborator by its ID'). This clearly differentiates it from sibling create/edit/delete/config-webhook operations even though it does not name them.

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

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

The 'Remote System Configuration Management' toolset heading loosely positions this as the connectivity-check operation among related configuration tools. However, there is no explicit statement of when to use this versus creating, editing, or deleting a configuration, and no alternative tools are named.

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

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

The description says 'Updates the webhook,' which is a write operation, while the annotations declare readOnlyHint: true. This directly contradicts the annotation and could cause an agent to treat this as a non-mutating call. No additional behavioral context is provided beyond the conflicting action verb.

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

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

The opening sentence is clear and front-loaded, but the description includes a 'Parameters:' block that duplicates the schema verbatim. The 'Toolset' line adds mild context, so the description is short but contains redundant content.

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

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

For a mutation tool with one parameter and no output schema, the description provides the minimum callable information. However, it leaves the annotation contradiction unaddressed and omits any detail about the webhook payload, required permissions, or response, making it insufficient for fully reliable invocation.

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

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

Schema description coverage is 100%, and the description repeats the id parameter's purpose without adding new details such as ID format, source, or prerequisites. The baseline of 3 applies because the schema already fully documents the parameter.

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

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

States a specific verb and resource: 'Updates the webhook for a remote system configuration in Collaborator by its ID.' This distinguishes it from sibling configuration-management tools like collaborator_edit_remote_system_configuration, though it does not clarify what webhook fields can be updated.

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

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

No guidance is provided on when to use this tool versus alternatives such as collaborator_edit_remote_system_configuration or webhook-related operations. There are no prerequisites, exclusions, or conditions that would help an agent choose between this and competing tools.

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

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

Annotations already indicate this is a mutation (readOnlyHint=false), but the description adds no behavioral context beyond the basic action. It does not disclose whether applying an existing label is idempotent, whether duplicate labels can occur, or what side effects or errors should be expected.

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

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

The definition is compact and front-loaded with the core action. The parameter list is somewhat redundant because it duplicates the schema, but it does not significantly bloat the description and the overall structure is clear.

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

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

For a simple two-parameter mutation, the description plus schema is generally sufficient to invoke the tool. However, key operational context is missing, such as whether adding the same label twice has any effect, whether the label must already exist, and any constraints around the pacticipant name.

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

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

Schema description coverage is 100%, so the input schema already documents both parameters. The description repeats the schema's parameter names and descriptions without adding extra semantics such as value formats, label existence requirements, or relationships between the parameters.

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

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

The description uses a specific verb ('Apply') and a clear resource ('label to a pacticipant'), making the operation unambiguous. It also distinguishes naturally from the sibling tool contract-testing_remove_label_from_pacticipant, so an agent can tell addition from removal without opening the schema.

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

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

No guidance is provided on when to use this tool versus alternatives, nor are prerequisites mentioned such as whether the pacticipant or label must already exist. The 'Toolset: Labels' label provides minimal grouping context but no explicit decision guidance.

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

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

Annotations already establish the tool is not read-only, not idempotent, and not destructive. The description adds the admin context and single-role semantics, but it does not disclose what happens on duplicate assignment, whether the user or role must already exist, or any side effects beyond the role addition.

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

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

The description is short and front-loaded with the core action. However, the 'Parameters' block duplicates the schema verbatim, and 'Toolset: Admin' repeats title information, so some lines do not add new value.

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

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

For a simple two-parameter mutation with annotations and full schema coverage, the description is nearly sufficient: an agent can determine the operation, required parameters, and admin context. The main gap is explicit routing guidance versus admin_set_user_roles, but that is more a selection concern than an invocation blocker.

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

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

The input schema has 100% description coverage for both parameters, and the description restates the exact schema text for userId and roleId. It adds no new meaning beyond the parameter names, types, required flags, and UUID format already present in the schema.

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

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

The description states a specific verb ('Add'), resource ('a single role'), and target ('to a user'), plus the admin qualifier. The phrase 'single role' helps distinguish it from sibling admin_set_user_roles, which would set or replace multiple roles.

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

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

There is no guidance on when to use this tool versus admin_set_user_roles or admin_remove_role_from_user. No preconditions, exclusions, or alternative-selection hints are given; only 'admin' is mentioned, which already appears in the title.

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

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

The description only restates the create action, which is already captured by annotations (readOnlyHint=false). It adds no unique behavioral context—no mention of idempotency, required admin privileges, uniqueness constraints, or what happens after creation. With annotations present, the description contributes no additional disclosure.

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

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

The core first sentence is concise and front-loaded with the operation. However, the following parameter list fully duplicates the input schema, adding redundancy without new information. The structure is adequate but not tightly edited.

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

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

For a create operation with no output schema, the description does not state response details, name uniqueness, or admin-level authorization requirements. The full parameter schema does allow an agent to construct a valid request, so it is minimally adequate, but several contextual gaps remain.

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

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

Schema description coverage is 100%, including the permissions item's scope property. The description repeats the parameter names and descriptions verbatim without adding examples, constraints, or relationships beyond the schema. This meets the baseline for high schema coverage but adds no extra value.

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

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

The description clearly states the operation: 'Create a new role with specific permissions.' The verb 'Create' and resource 'role' are unambiguous, and the sibling tools (admin_update_role, admin_delete_role) are distinguished by verb. However, the parenthetical '(admin)' is ambiguous—it likely refers to the toolset but could be misread as a permission modifier.

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

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

No guidance is provided on when to use this tool versus alternatives like admin_update_role, admin_set_user_roles, or admin_add_role_to_user. The 'Toolset: Admin' label gives only a category, not selection criteria. There are no stated exclusions or conditions.

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

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

Annotations already indicate a mutating, non-idempotent operation (readOnlyHint=false, idempotentHint=false), so the description's 'Create' confirms the action type rather than contradicting it. It adds little beyond that—no mention of auth requirements, uniqueness, side effects, or return behavior—though 'Toolset: Admin' hints at privilege.

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

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

The description is short and front-loads the primary action, and the Toolset/Parameters layout is scannable. However, the Parameters block duplicates the schema, so not every part of the description earns its place.

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

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

For a one-parameter creation tool, the minimum required to invoke it—action and required field—is present. Missing context about output, naming constraints, or admin permissions keeps it from being complete, but the low complexity and annotation coverage make it adequately usable.

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

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

The input schema already fully documents the single required `name` parameter with 100% coverage. The description's Parameters section repeats that information without adding constraints, defaults, or examples, so it meets the baseline but adds no extra semantic value.

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

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

The description uses a specific verb ('Create') and identifies the resource ('a new system account'), and the 'Toolset: Admin' heading clarifies the administrative scope. The parenthetical '(admin)' is slightly ambiguous, but the action and object are clear enough to distinguish this from most sibling tools.

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

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

There is no explicit when-to-use or alternative guidance; an agent must infer that this tool is for creating system accounts. 'Toolset: Admin' provides loose context, but it doesn't differentiate this from admin_create_user or admin_create_team or state prerequisites.

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

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

Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the description is consistent with a non-read-only, non-idempotent mutation. The description adds the 'admin' scope, which hints at privilege requirements, but does not disclose side effects, return values, or any pitfalls. This is adequate 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.

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

The core statement is front-loaded and clear: 'Create a new team (admin).' However, the subsequent parameter list duplicates information already present in the input schema, adding unneeded length. The structure is clean and readable, but not every sentence earns its place.

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

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

For a simple create operation with a fully documented schema, the description provides enough to invoke the tool with required parameters. However, there is no output schema and the description does not mention what response to expect, whether referenced UUIDs must already exist, or how this fits into team management workflows. Additional behavioral context would improve completeness.

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

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

Schema description coverage is 100%, so the schema fully documents name, administratorUuids, environmentUuids, and pacticipantNames. The description merely duplicates these parameter definitions without adding new semantics like relationships, validation rules, or usage examples. Baseline 3 is appropriate because the schema carries the descriptive burden.

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

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

The description states a specific verb and resource: 'Create a new team (admin).' The action is unambiguous and the 'admin' qualifier distinguishes this from non-admin team operations. Among siblings like admin_update_team, admin_delete_team, and admin_list_teams, the 'create' verb clearly identifies this tool's role.

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

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

The description gives no guidance on when to use this tool versus alternatives. It does not mention that admin_update_team should be used for modifying existing teams, admin_delete_team for removal, or that this requires admin privileges beyond the word '(admin)' in the description. The usage context is only implied by the action itself, not explicitly stated.

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

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

Annotations already indicate this is not read-only, not idempotent, and not destructive, so the agent knows it is a write operation. However, the description adds little beyond the tool name: it does not disclose whether the created user receives an invitation, whether it can be used with external IdP accounts, or how conflicts or duplicate emails are handled.

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

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

The description is short and fronts the core purpose, but it spends several lines repeating parameter information already present in the input schema. The 'Toolset: Admin' line and the full parameter list add little marginal value.

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

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

For a mutating admin operation with no output schema and no behavioral disclaimers, the description is thin. An agent is left without knowing what the response will be, whether an email is sent, whether the user is active immediately, or what admin permissions are required.

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

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

Schema description coverage is 100%, so the schema fully documents all six parameters. The description duplicates those same descriptions without adding additional meaning or clarifying relationships between fields such as externalIdpId and externalIdpUsername.

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

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

The description states a specific action ('Create a new user account') on a clear resource and scopes it as an admin operation. It is distinct from nearby siblings like admin_update_user or admin_invite_users, though it does not explicitly call out those distinctions.

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

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

No guidance is given on when to use this tool versus alternatives like admin_invite_users, admin_create_system_account, or admin_set_user_roles. The 'Toolset: Admin' label is generic and does not help an agent choose among the many admin siblings.

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

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

Annotations already declare destructiveHint=true and idempotentHint=true. The description adds no additional behavioral context such as irreversibility, cascading effects, permissions, or what happens to related data. It merely restates the delete action already obvious from the name.

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

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

The description is short and front-loaded with the core action. The toolset and parameter listing are useful, though the parameter block is partially redundant with the input schema, preventing a perfect score.

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

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

The tool is simple with one parameter and annotations cover its destructive nature. However, the description omits any details about deletion consequences, success response, or required permissions, leaving some ambiguity for a mutating operation.

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

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

Schema description coverage is 100%, and the description's parameter section simply duplicates the schema's own roleId description. No extra meaning, format constraints, or relationships are added, so the baseline of 3 applies.

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

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

The description states a precise action ('Delete') and resource ('role'), with '(admin)' clarifying the toolset. It is unambiguous and distinguishable from sibling tools like admin_delete_user or admin_update_role.

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

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

There is no guidance on when to use this tool versus alternatives like admin_reset_roles, admin_update_role, or other admin deletes. The toolset label is helpful but does not convey usage context, prerequisites, or exclusions.

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

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=true, so the core safety profile is known. The description adds the 'admin' scope but does not disclose whether deletion is permanent, whether it cascades to related resources, or what side effects may occur. No contradiction with annotations.

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

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

The description is short and front-loaded with the core purpose. The parameter section is redundant with the input schema but is minimal and does not significantly harm readability. A slightly leaner version could drop the repeated parameter details.

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

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

Given the single parameter and existing annotations, the description is mostly adequate for invoking the tool. However, for a destructive admin operation, it does not explicitly state that the deletion is irreversible, whether it affects team members or dependencies, or what success/failure looks like since there is no output schema.

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

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

Schema description coverage is 100%, and the description only repeats exactly what the schema already says: teamId is a required UUID string. No additional meaning, formatting guidance, or value constraints are provided beyond the schema.

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

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

The description uses a specific verb and resource: 'Delete a team (admin).' It clearly identifies the operation and distinguishes it from sibling admin team operations by the delete action. However, it largely restates the tool name and does not add any differentiating context beyond the action.

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

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

There is no guidance on when to use this tool versus alternatives like admin_update_team or admin_get_team. The description implies the obvious use case—deleting a team—but provides no exclusions, prerequisites, or decision context.

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

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=true, so the description adds little beyond what is already structured. It does not disclose irreversibility, cascading effects on related data, or any security/permission requirements beyond the already present '(admin)' label.

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

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

The description is short and front-loaded with the core action, followed by a minimal parameter list. It contains no filler, though the parameter list duplicates the schema; still, it remains appropriately sized for a simple one-parameter tool.

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

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

For a single-parameter admin delete with no output schema, the description covers the essential action and parameter. However, it omits any mention of error cases, what happens to the deleted user's data, or how this interacts with team memberships and roles, leaving some ambiguity in a destructive Admin operation.

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

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

Schema description coverage is 100% with a single parameter userId, and the schema itself provides the description 'UUID of the user'. The description only repeats this information without adding meaning such as format, examples, or how to obtain the UUID.

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

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

The description states a specific verb and resource: 'Delete a user account (admin).' This clearly distinguishes it from sibling tools like admin_update_user, admin_create_user, and admin_invite_users, so an agent can identify the correct operation without opening the schema.

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

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

The description provides no explicit guidance about when to use this tool versus alternatives, nor does it mention prerequisites or conditions. The 'admin' qualifier hints at scope but does not say, for example, when deletion is preferred over updating or deactivating a user.

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

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

The description identifies this as an admin-level read operation, adding an authorization signal not present in the annotations. It is consistent with readOnlyHint, idempotentHint, and destructiveHint=false, and does not contradict them.

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

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

The main sentence is concise and front-loaded, with a short toolset label and parameter list. The parameter list is redundant with the schema but does not make the description overly long or difficult to scan.

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

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

For a one-parameter, read-only, idempotent retrieval by UUID, the description provides enough information to invoke the tool correctly. It does not describe response shape or not-found behavior, but the operation is simple and no output schema is provided.

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

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

Schema coverage is 100%, and the description simply restates roleId/UUID with no additional semantic details such as format constraints, lookup behavior, or error conditions. The schema fully documents the only parameter, so the baseline of 3 applies.

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

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

The description uses a specific verb ('Retrieve') and resource ('details for a specific role by UUID'), so an agent knows exactly what the tool does. It distinguishes from list-style tools by emphasizing 'specific role by UUID', but it does not explicitly name a sibling alternative.

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

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

No guidance is given about when to use this tool versus alternatives such as admin_list_roles. 'Toolset: Admin' provides context but no explicit when-to-use or when-not-to-use direction.

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