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

With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose if this requires specific permissions, rate limits, whether comments are editable/deletable, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in 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 a single, clear sentence with zero wasted words—it directly states the tool's purpose without redundancy or fluff. This makes it highly efficient and front-loaded for quick comprehension.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial context like authentication needs, error handling, return values, or how it differs from sibling tools, leaving the agent under-informed for effective 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%, with both parameters ('issue_key' and 'comment') clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, so it meets the baseline for adequate but unenhanced 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 action ('Add a comment') and target resource ('to a Jira issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'jira_update_issue' or 'jira_transition_issue' which might also involve modifying issues, missing an opportunity for clearer distinction.

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 guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing issue access), exclusions (e.g., not for private comments), or comparisons to siblings like 'jira_update_issue' for other modifications, leaving the agent without contextual usage cues.

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 the full burden of behavioral disclosure. It states 'Create a new Jira issue,' implying a write operation, but fails to mention critical aspects such as required permissions, whether the creation is idempotent, error handling, or what happens upon success (e.g., returns an issue ID). This is a significant gap for a mutation tool with zero annotation coverage.

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, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly. Every word earns its place, adhering to best practices for conciseness.

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 complexity of creating an issue (a mutation operation) with no annotations and no output schema, the description is incomplete. It doesn't address behavioral traits like authentication needs, error cases, or what the tool returns (e.g., issue key or ID). For a tool with 6 parameters and significant implications, more context is needed to guide the agent effectively.

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 all parameters well-documented in the input schema (e.g., project_key, summary, description). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3 even without param info in 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?

The description clearly states the action ('Create') and resource ('new Jira issue'), making the purpose immediately understandable. It distinguishes from siblings like jira_get_issue or jira_update_issue by specifying creation rather than retrieval or modification. However, it doesn't explicitly differentiate from jira_add_comment or jira_transition_issue in terms of creating vs. adding or transitioning, keeping it from a perfect score.

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 guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid project key), exclusions, or comparisons to siblings like jira_update_issue for modifying existing issues. This lack of context leaves the agent to infer usage based on tool names 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets details' but doesn't specify what details are returned, whether it's a read-only operation, if authentication is required, or any rate limits. This leaves significant gaps for a tool that likely interacts with an external API.

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, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what details are returned, the response format, or any behavioral traits like error handling. For a tool that likely fetches data from Jira, this leaves too much unspecified for effective agent 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 input schema has 100% coverage with a clear description for the 'issue_key' parameter. The description adds no additional parameter information beyond what the schema provides, such as format examples or constraints. Since schema coverage is high, the baseline score 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 clearly states the verb ('Get details') and resource ('specific Jira issue'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'jira_search_issues' or 'jira_get_projects' beyond the 'specific' qualifier, which is somewhat implied but not explicit.

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 guidance on when to use this tool versus alternatives. It doesn't mention that this is for retrieving a single issue by key, as opposed to 'jira_search_issues' for multiple issues or 'jira_get_projects' for project data. There are no exclusions or prerequisites 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?

With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose permissions needed, rate limits, pagination, sorting, or what data is returned. For a read tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence with zero waste. It is front-loaded with the core purpose, making it easy to scan and understand quickly without any redundant or verbose language.

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 tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but lacks completeness. It doesn't explain return format, error conditions, or behavioral constraints, which would help an agent use it correctly despite the low complexity.

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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for this scenario is 4, as it avoids unnecessary repetition of schema information.

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 verb ('Get') and resource ('list of Jira projects'), making the purpose immediately understandable. It distinguishes this read operation from sibling tools that perform mutations like create, update, or transition. However, it doesn't specify scope (e.g., all projects vs. filtered), keeping it from a perfect score.

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 retrieving project lists, but provides no explicit guidance on when to use this versus alternatives like jira_search_issues or jira_get_issue. No prerequisites, exclusions, or comparative context are mentioned, leaving usage decisions 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?

With no annotations, the description carries full burden but provides minimal behavioral insight. It doesn't disclose whether this is a read-only operation, its rate limits, authentication needs, pagination behavior, or what the return format looks like. The description only states what it does, not how it behaves.

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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately clear without unnecessary elaboration.

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 complexity of a search tool with no annotations and no output schema, the description is insufficient. It doesn't explain return values, error handling, or behavioral constraints, leaving significant gaps for an AI agent to understand how to use it effectively.

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 both parameters. The description adds no additional meaning beyond implying JQL usage, which is already covered in the schema's description of the 'jql' parameter. This meets the baseline 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 clearly states the verb ('Search') and resource ('Jira issues') with the method ('using JQL'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'jira_get_issue' or 'jira_get_projects', but the JQL focus implies a more flexible querying approach.

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. It doesn't mention scenarios where this is preferable to 'jira_get_issue' (for single issues) or 'jira_get_projects' (for project lists), nor does it specify prerequisites like JQL knowledge or when not to use it.

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 the full burden of behavioral disclosure. It states the action ('Transition') but doesn't explain what this entails—e.g., whether it requires specific permissions, if it's reversible, what happens to workflow steps, or if there are side effects like notifications. For a mutation tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded with the core action, making it easy to parse and understand quickly.

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 complexity of a mutation tool (changing issue status in Jira) with no annotations and no output schema, the description is incomplete. It lacks crucial context like permission requirements, workflow implications, error conditions, or what the tool returns. This leaves significant gaps for an AI agent to use it effectively.

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 description coverage is 100%, with both parameters ('issue_key' and 'status') clearly documented in the input schema. The description adds no additional meaning beyond what the schema provides, such as examples of valid statuses or constraints on issue keys. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb ('Transition') and resource ('a Jira issue') with the specific action ('to a different status'), making the purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'jira_update_issue' which might also change status, but the verb 'transition' is specific enough for basic differentiation.

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 guidance on when to use this tool versus alternatives like 'jira_update_issue' (which might handle status changes differently) or 'jira_get_issue' (for checking current status). There's no mention of prerequisites, such as needing valid issue keys or available status transitions, leaving usage context entirely 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 but only states it's an update operation. It doesn't disclose behavioral traits like required permissions, whether updates are reversible, rate limits, error conditions, or what happens to unspecified fields. For a mutation tool with zero annotation coverage, this leaves critical 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?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the core purpose. Every word 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 this is a mutation tool with no annotations, no output schema, and complex nested parameters, the description is inadequate. It should explain what the tool returns, error handling, permissions needed, and how it differs from sibling tools. The current description leaves too many contextual gaps.

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 thoroughly. The description adds no additional meaning about parameters beyond what's in the schema (e.g., format examples, field constraints, or update behavior). Baseline 3 is appropriate when schema does the heavy lifting.

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 verb ('Update') and resource ('an existing Jira issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'jira_transition_issue' which also modifies issues, missing an opportunity for clearer distinction.

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 guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., needing issue_key), comparison with 'jira_transition_issue' for workflow changes, or when to use 'jira_create_issue' instead. The agent receives no usage context.

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