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

No annotations are provided, so the description carries the full burden. It clearly indicates a read operation ('Get') and specifies the returned data, but lacks details on scope (e.g., all projects vs. current user), pagination, or potential errors. It is minimally transparent but not overly detailed.

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 a single, front-loaded sentence that directly communicates the tool's function and important output fields. Every word earns its place; no unnecessary information.

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 zero parameters and no output schema, the description adequately covers the query scope and return fields. The only minor gap is the lack of explicit scope boundaries (e.g., whether 'all' means globally or within a project), but this does not detract significantly from overall completeness for a simple 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?

The tool has zero parameters, so the description does not need to explain parameter semantics. The baseline score of 4 applies since there are no parameters to describe.

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') and clearly identifies the resource ('all issues currently flagged as blocked') and key return fields (blocking reason, assignee). This clearly distinguishes it from sibling tools focused on sprints, own issues, or workload.

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 retrieving blocked issues, which is a clear usage context. However, it does not explicitly mention when to use it versus sibling tools like search_issues_tool or get_my_issues_tool, nor does it state 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?

No annotations are provided, so the description carries the transparency burden. It clearly signals a read-only operation via 'Get' and lists the output content, but it does not disclose behavior when no active sprint exists or whether the scope is the current user's team/board. This is adequate but lacks some edge-case detail.

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 one efficiently front-loaded sentence: 'Get the active sprint:' immediately identifies the action and resource, followed by a colon-separated list of deliverables. Every word earns its place with no redundant 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?

Given no parameters, no output schema, and no annotations, the description is mostly complete for a simple sprint overview, clearly listing the returned metrics. It falls slightly short by not specifying the sprint's scope (e.g., current team/project) or the outcome when no active sprint is present, but these are minor omissions for a low-complexity 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?

The input schema has zero properties, so with 0 parameters the baseline is 4. There are no parameters for the description to clarify, and its enumerated outputs are sufficient for a no-argument tool.

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') and resource ('active sprint'), then enumerates the exact data returned (issues breakdown, completion percentage, in-progress work, blockers, days remaining). This clearly distinguishes it from sibling tools like get_blockers_tool (blockers alone) or get_my_issues_tool (personal issues).

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 use when an active sprint status overview is needed, but it provides no explicit guidance on when to choose this tool over alternatives (e.g., get_blockers_tool or get_roadmap_tool). There are no 'when not to use' or alternative-name mentions, so usage context is only implicit.

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 adds the behavioral trait 'sorted by priority', but does not disclose other relevant details such as permissions, empty result behavior, or whether the list is exhaustive. A moderate score 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 concise, front-loaded sentences. Every phrase earns its place, with no 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 simple single-parameter tool with no output schema, the description covers the core behavior and parameter usage adequately. It lacks alternative guidance, but that is captured in the usage guidelines dimension.

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 0%, but the description compensates by specifying the parameter format ('full name') and giving an example ('Priya Sharma'), adding meaning beyond the bare schema field 'assignee_name'.

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 'Get all issues assigned to a team member, sorted by priority' with a specific verb and resource, clearly distinguishing this from siblings like search_issues_tool and get_team_workload_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?

Provides no guidance on when to use this tool versus alternatives. The only usage instruction ('Use the person's full name') addresses parameter format, not tool selection.

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 the full burden of behavioral transparency. It discloses the scope ('all epics') and the exact output fields, making the read-only nature and return format clear. No hidden side effects or prerequisites are relevant, so this is adequate.

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

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

The description is a single, well-structured sentence that front-loads the primary action and resource. Every clause adds meaning, with no waste.

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 zero-parameter read tool without an output schema, the description fully specifies what the tool does and what it returns. No additional information is needed for an agent to select and invoke it 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?

There are zero parameters, so the baseline is 4. The description correctly adds no parameter information since there are none.

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 tool's function with a specific verb ('Get') and resource ('the product roadmap'), and enumerates the response fields (epics, completion %, issue counts, status, target dates). This distinguishes it from sibling tools that focus on sprints, issues, blockers, workload, or velocity.

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 retrieving product roadmap information but does not explicitly state when to prefer it over siblings or any exclusions. No alternative tool is mentioned as a comparison, so guidance is only implicit.

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 provided, the description carries full burden. It discloses the default-to-active-sprint behavior and optional filters, which is useful. However, it does not state whether the operation is read-only, what exactly constitutes an 'issue count' (e.g., all issues or only open), or how the status breakdown is structured. This ambiguity limits transparency.

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 three sentences: purpose, filters, default. It is front-loaded with the primary action, and every sentence contributes useful information without 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 simple two-parameter tool with no output schema, the description covers the core function, filter options, and default behavior. It doesn't explain response format, but the phrase 'with breakdown by status' hints at the output aggregation. The only notable gap is the interaction of simultaneous team and sprint filters, but overall the description is adequately complete.

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 schema has no descriptions for team or sprint_id (0% coverage), but the description explicitly explains both as optional filters, provides example team names, and clarifies the active-sprint default. This adds meaningful semantics beyond the bare property names. Minor ambiguity remains about how the two filters interact.

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 'Get issue count per team member, with breakdown by status' provides a specific verb and object, and the status breakdown differentiates it from sibling tools like get_my_issues_tool or get_blockers_tool. The optional filters and default sprint behavior further clarify 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 clearly implies the tool is for team-level workload analysis, with filters for team and sprint. However, it does not explicitly state when to prefer this over sibling tools or provide exclusions, so it falls just short of explicit guidelines.

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, so the description carries full burden. It discloses the output (planned vs completed story points, average completion rate) and scope ('all past sprints'), but does not explicitly confirm it is read-only or mention any side effects, rate limits, or data limitations. It adds some value beyond the name but not rich 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 a single concise sentence, front-loaded with the core purpose and specific metrics. It contains no filler and is perfectly sized for the tool's simplicity.

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 and no annotations, the description is the primary source of information. It covers the key return values (planned/completed story points, average completion rate) and scope (past sprints). It could be slightly more explicit about how the average is computed or whether current sprint is included, but it is sufficiently complete for a parameterless sprint velocity 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?

The tool has zero parameters, so the schema provides complete coverage. The description does not need to explain parameters, and the baseline of 4 applies. It correctly focuses on the output rather than inputs.

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 tool retrieves sprint-over-sprint velocity, including planned vs completed story points and average completion rate. The verb 'get' and specific metrics make the purpose clear, though it does not explicitly differentiate from sibling tools like get_team_workload_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?

The description implies usage for historical sprint velocity analysis but provides no explicit guidance on when to choose this over alternatives, nor does it mention exclusions. It lacks comparative context with sibling 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?

Without annotations, the description carries the full transparency burden. It discloses that matching occurs against title and description and that results include status, priority, and assignee, which is useful. However, it does not mention case sensitivity, pagination, sorting, or potential limitations, leaving some behavioral gaps.

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?

Three concise sentences front-load the key action and provide matching scope and return fields. Every sentence adds value with no redundancy or padding.

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 one-parameter search tool with no output schema, the description provides the essential information: what it searches, what it matches, and what it returns. It does not cover advanced aspects like result limits or ordering, but those are not critical for basic 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?

The schema has a single 'query' parameter with no description, but the tool description explains that the query is a keyword matched against title and description. This significantly clarifies the parameter's meaning, compensating well for the 0% 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 clearly states the tool searches for issues by keyword, specifying that it matches against title and description. This distinctively separates it from sibling tools like get_my_issues or get_blockers, which focus on specific views rather than text search.

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 usage when a keyword-based search is needed, but does not explicitly state when to use this over alternatives. It lacks exclusions or guidance about scenarios where other tools would be more appropriate, so usage context is only implicitly addressed.

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