Cypress Cloud MCP

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

With no annotations provided, the description carries full burden but offers minimal behavioral context. It fails to mention that results are paginated (despite page/limit parameters), does not describe what constitutes a 'failed' test versus other states, and omits error handling behavior for invalid run identifiers.

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?

Single sentence is front-loaded with the verb and efficiently structured with no filler words. However, given the tool's complexity (5 parameters with mutual exclusivity rules), the description is arguably undersized rather than optimally concise.

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?

Minimum viable given rich structured data: 100% schema coverage and output schema exist, reducing burden on description. However, it lacks explanation of the parameter combination requirements (run_url vs project_id+run_number), which is essential context 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%, establishing a baseline of 3. The description adds no parameter-specific guidance, but the schema fully documents parameter relationships (e.g., 'When used, do not provide projectId') and constraints, so no additional compensation is required from the description.

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?

Clear verb (Returns) and resource (failed tests) with scoping (from a given cypress run). However, it does not explicitly differentiate from sibling cypress_get_flaky_tests, which could confuse agents about whether flaky tests are included or excluded from 'failed' results.

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 no guidance on when to use versus alternatives, nor does it explain the critical mutual exclusivity between run_url and project_id/run_number parameters (which is only documented in individual parameter descriptions). No prerequisites or error conditions 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?

No annotations are provided, leaving the description to carry full disclosure burden. It only states the tool 'returns' data, offering no information about what defines 'flaky,' external API calls required, pagination behavior, or permission requirements despite the tool likely accessing Cypress Cloud APIs.

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?

Extremely concise at 8 words with no redundancy. However, the brevity is arguably excessive given the tool's complexity (5 parameters with mutual exclusivity constraints), leaving crucial usage patterns undocumented in the description text.

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 acknowledges the need to target a 'given cypress run,' but with zero required parameters and complex alternative identifier schemes in the schema, the description should explicitly note the two mutually exclusive identification methods. Output schema exists, reducing burden on description for return 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?

With 100% schema description coverage and detailed parameter descriptions (including conditional logic for run_url vs project_id), the schema carries the semantic load. The description adds no parameter-specific guidance, warranting the baseline score 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 clearly identifies the action (returns/retrieves) and specific resource (flaky tests) with scope (from a given cypress run). It distinguishes the target resource by name, though it doesn't explicitly differentiate from sibling tool 'cypress_get_failed_tests' in the prose.

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 guidance on when to use this tool versus siblings (e.g., when to query flaky vs failed tests). No mention of the critical mutual exclusivity between 'run_url' and 'project_id'+'run_number' parameter groups, which is only documented in the schema descriptions.

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?

No annotations provided, so description carries full burden. Only behavioral hint is 'available to the user' implying auth scope. Missing details on pagination, caching, or whether this includes archived/deleted projects.

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?

Single sentence with no filler. Front-loaded with the action and resource. Appropriate length for a zero-parameter list operation.

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?

Adequate given low complexity (0 params, flat structure) and presence of output schema. However, gaps remain in explaining workflow relationship to sibling tools that likely require these project identifiers.

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?

Zero parameters per input schema. As per rubric baseline, tools with no parameters score 4 since no semantic clarification is required.

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?

Clear verb ('Returns') and resource ('projects'), with scope ('available to the user'). However, it does not explicitly differentiate from sibling tools like 'cypress_get_runs' that also return lists of entities.

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 no guidance on when to use this tool versus siblings, nor does it mention that this is likely a prerequisite discovery step needed to obtain project IDs for 'cypress_get_runs' or 'cypress_get_failed_tests'.

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?

With no annotations, the description carries full burden. It successfully discloses data scope (returns status/counts/tags vs excludes logs/artifacts), but fails to declare operational traits: no mention of read-only safety, pagination behavior (despite page/limit params), or what occurs when called with zero required parameters.

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 sentences with zero waste. Front-loaded with the action ('Retrieves...'), followed immediately by scope clarification. The negative constraint in sentence two earns its place by preventing mis-selection.

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?

Adequate for a query tool with rich schema (100% coverage) and output schema. The description covers the essential behavioral contract (high-level summary only). Minor gap: could note pagination behavior given the page/limit parameters, though output schema likely handles return structure.

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 has 100% description coverage with clear parameter semantics and cross-parameter constraints already documented (e.g., 'When used, do not provide...'). Description adds no parameter-specific details, which is appropriate given the baseline expectation for high-coverage schemas.

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?

Excellent specificity: 'Retrieves high-level run results' uses a concrete verb with clear resource scope. The second sentence explicitly differentiates from siblings (cypress_get_failed_tests) by stating what is NOT returned (logs, artifacts, detailed results), preventing tool selection 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 implied usage through negative constraints ('does not return logs...'), which hints when to avoid this tool, but lacks explicit guidance like 'For detailed test logs, use cypress_get_run_details instead' or prerequisite conditions despite having complex parameter dependencies in the schema.

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?

No annotations provided, so description carries full burden. It discloses the trigger condition (capability gaps) but lacks mechanical details: persistence guarantees, idempotency, rate limits, or confirmation behavior. For a mutation operation with no safety annotations, additional behavioral context would be valuable.

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 sentences with zero waste. First sentence establishes purpose; second provides usage condition. Information is front-loaded and 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?

Given 100% schema coverage, single simple parameter, and existence of output schema (per context signals), the description comprehensively covers necessary invocation context. Appropriate for a straightforward feedback submission 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 coverage is 100% (feedback parameter well-documented). Description adds crucial semantic requirement 'summarize the request', instructing the agent to synthesize user intent rather than relay raw text. This elevates it above baseline schema documentation.

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 specific verb 'Submits' with clear resource 'user feedback regarding the MCP service'. It effectively distinguishes itself from Cypress data-retrieval siblings (cypress_get_*) by targeting a completely different domain (MCP service meta-feedback vs. Cypress test data).

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 trigger: 'If the user wishes to do something that is not possible via the tools provided'. This clearly signals the condition for invocation. Missing explicit 'when-not-to-use' or alternative tools, though the condition is sufficiently specific.

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