DevOps MCP Hub

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.0.0
Disambiguation3/5
Most Jira operational tools (get_issue, search_issues, create_issue, etc.) are clearly distinct, but there is overlap in the reporting/generation tools: generate_release_notes vs save_release_notes_to_file vs save_doc_to_github are confusingly similar, as are create_issue and create_smart_issue. An agent could easily select the wrong tool when these overlapping functions are involved.
Naming Consistency5/5
Every tool name follows a consistent verb_noun pattern (e.g., get_boards, create_issue, analyze_sprint_health, save_doc_to_github). There is no mixing of camelCase or alternate verb styles, making the naming highly predictable.
Tool Count2/5
With 31 tools, the server exceeds the 25-tool threshold for 'too many', making it feel bloated. Many tools are extremely narrow (e.g., get_transitions, get_attachments) and could be consolidated, though the diversity of Jira operations explains some of the count.
Completeness4/5
The server covers the full Jira issue lifecycle (create, get, update, delete, transition, comment, assign, worklog) plus sprint tracking and AI-based reporting. Minor gaps exist for things like project creation or issue linking, but these are not core to the apparent DevOps hub purpose and can be worked around.
Average 2.9/5 across 31 of 31 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior, but it only says 'Generate comprehensive release notes'. It does not mention what data is used, whether it is read-only, if it has side effects, or what the output format is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only one sentence, which is concise, but it under-specifies the tool's functionality. It restates the tool's name without adding substantive detail, making it more under-specification than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has six parameters, two required, no output schema, and no annotations, this description is far from complete. It fails to convey how the parameters work together, what the output is, or how the tool behaves, making correct invocation difficult.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the missing parameter details, but it provides none. The six parameters are left entirely to their names, with no explanation of their meaning, format, or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action 'Generate' and the resource 'release notes', which is clear and specific. However, it does not differentiate from the sibling tool 'save_release_notes_to_file', which also involves release notes, so it earns a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'save_release_notes_to_file' or 'analyze_sprint_health'. It does not state any 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.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only says 'Create a new Jira issue' and does not mention side effects, return values, authentication requirements, failure modes, or idempotency. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no waste, which is appropriately concise for a basic purpose statement. However, it is too under-specified for a tool with six parameters, though that is more an issue of completeness than structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and zero schema description coverage, the description is completely inadequate. A create operation with six parameters needs at least guidance on parameter meaning, likely return value, and usage context. The single sentence does not enable an agent to invoke the tool correctly for non-trivial cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning no parameter descriptions are provided in the schema. The description itself does not mention or explain any of the six parameters (e.g., what projectKey is, valid priority values, or how labels are formatted). The tool provides no semantic meaning beyond raw parameter names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create a new Jira issue,' which is a specific verb ('create') and resource ('Jira issue'), making the purpose clear. It does not explicitly distinguish from the sibling tool 'create_smart_issue,' but the straightforward action is still understandable in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 instead of alternatives, such as create_smart_issue, nor does it mention prerequisites, limitations, or when not to use it. There is no mention of required projectKey/summary or any setup conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It only offers 'workload analysis' and gives no information about the return format, read-only nature, or side effects. It does not contradict any annotations, but it reveals almost nothing about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short phrase, making it concise. However, it is under-specified and lacks structure, such as a clear sentence or bullet points, which reduces its usefulness. The brevity is not a strength because it comes at the cost of essential content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations or output schema, the description must clarify what the agent receives and how to use the tool. It fails to do so, leaving the agent with only a vague notion of 'team workload analysis.' Given the two-parameter schema, a fuller description would explain the purpose of each parameter and the shape of the returned dashboard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
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 mention sprintId or projectKey at all. An agent must rely solely on the parameter names, which is insufficient for correct invocation, especially with optional parameters. The description adds no value to parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Team workload analysis with balance metrics' indicates the tool's general subject, but it lacks an explicit verb (e.g., 'get' or 'retrieve') and does not distinguish it from related tools like get_team_worklogs or analyze_sprint_health. It is not a tautology, yet it remains vague about the exact output or scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as get_team_worklogs or analyze_sprint_health. It simply names the feature without any contextual cues about prerequisites, use cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It only states it retrieves a summary, but does not mention whether it aggregates data, what parameters are required, potential side effects, or return format. This is a significant gap for a tool that may have side effects or specific data handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short phrase, which is concise and front-loaded. However, it is under-specified for a tool with 4 parameters and no other documentation. It conveys the basic purpose but omits critical contextual details, making it less effective than a slightly longer description would be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 optional parameters, no annotations, no output schema), the description is severely incomplete. It does not explain what the summary contains, how parameters interact, or what the response looks like. This is inadequate for an agent to confidently select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters (endDate, sprintId, startDate, projectKey) with 0% description coverage. The description does not clarify the meaning of any parameter or how 'team' maps to them. It completely fails to compensate for the lack of schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get worklog summary for team' uses a specific verb (Get) and resource (worklog summary), and mentions 'for team' to indicate scope. However, it does not define what 'team' means or how it differs from sibling tools like get_worklogs or get_workload_dashboard, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or scenarios where another tool would be more appropriate. The context signals show many sibling worklog-related tools, but the description does not reference them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It merely restates the tool's function without mentioning partial update semantics, side effects, permission requirements, or error behavior. This is a tautology of the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. While it is terse, it communicates the core purpose effectively, though it could provide more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With five parameters, no output schema, and no annotations, the description is incomplete. It does not explain how the update behaves (e.g., partial vs. full replacement) or any prerequisites. The schema mitigates some gaps but the description itself is insufficient for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
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 explain any of the five parameters. It adds no meaning beyond the property names in the schema, failing to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (update) and the resource (existing Jira issue), which distinguishes it from siblings like create_issue and delete_issue. However, it lacks explicit mention of updatable fields, though those are provided in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as transition_issue or assign_issue. The description does not provide any usage context, exclusions, or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the core function and omits any detail about the optional status filter, response format, pagination, or ordering. It also does not clarify how 'current user' is determined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that is front-loaded and wastes no words. It is appropriately concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 too minimal. It fails to explain the status parameter, differentiate usage from sibling tools, or disclose response details, making it incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter ('status') with 0% description coverage, and the tool description does not mention it at all. The description adds no meaning beyond the bare parameter name, leaving the agent without any information about acceptable values or behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') with a clear resource ('issues') and scope ('assigned to current user'), which distinguishes it from sibling tools like 'get_issue' (single issue) and 'search_issues' (arbitrary search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention that it returns only the current user's issues, nor does it suggest using 'search_issues' for broader queries or 'get_issue' for a specific issue.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only says 'Get' without disclosing whether it's read-only, pagination behavior, ordering, required permissions, or what happens when no issues exist. This is too minimal for an agent to understand side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (four words) and front-loaded with the key action and resource. It earns high marks for brevity, but the terseness borders on under-specification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and minimal description leave significant gaps: return format, pagination, filtering, and relation to sibling tools. For a simple tool this may be acceptable, but it's not robust enough for reliable agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description doesn't mention the sprintId parameter at all. Although the parameter name and tool context make it obvious, the description adds no semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action (get) and resource (issues in a sprint), distinguishing it from siblings like get_sprints or get_issue. However, it doesn't explicitly state that it returns a list or mention scope, so it's clear but not fully differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 search_issues or get_issue. There's no mention of preferred use cases, limitations, or scenario-based recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Because no annotations are present, the description must carry the full burden of behavioral disclosure. It only states the basic action and does not clarify permissions, return format, or behavior when no time tracking data exists. This exceeds minimal transparency but falls short of a safe, informative profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence with no redundant words, making it easy to parse. It is appropriately concise for a simple getter, though additional detail could be added without harming structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 and annotations, the description should explain what 'time tracking info' includes and how it relates to sibling tools like get_worklogs. It fails to provide this context, leaving the return value and tool boundaries unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter issueKey is self-explanatory, and the description's phrase 'for an issue' adds minimal semantic value. With 0% schema description coverage, the description should compensate with details like format or examples, but it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('time tracking info'), with an explicit object ('for an issue'). This distinguishes it from related tools like get_issue and get_worklogs, though the exact scope of 'time tracking info' is left vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as get_worklogs or add_worklog. There is no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining side effects and requirements. It only states the basic action (generate and save) without disclosing whether GitHub authentication is needed, whether files are overwritten, or what output the tool returns. This is insufficient for a write operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant words. It front-loads the core action and destination, making it easy to parse, though it sacrifices informative content for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 5 parameters, the description is incomplete. It does not explain what a workload report contains, the relationship between parameters, or any expected results. For a tool with moderate complexity, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 60%, and the description adds little beyond the schema. The phrase 'to local file or GitHub' hints at the role of saveToGitHub, but it does not clarify githubOwner or githubRepo, nor does it elaborate on sprintId or projectKey beyond their basic schema descriptions. The tool description fails to compensate for undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates and saves a workload report, with a destination of local file or GitHub. It distinguishes itself as a report-saving tool, though it doesn't explicitly differentiate from sibling tools like save_sprint_report or save_doc_to_github.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 save_sprint_report or get_workload_dashboard. There are no explicit usage conditions, prerequisites, or exclusions, leaving the agent to infer suitability 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It only states the action and resource, with no mention of pagination, result format, authentication, rate limits, or any side effects. For a search tool, this is minimal but not contradictory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It states the essential purpose efficiently, which is appropriate for a very simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, no annotations, and no output schema, the description is the only source of operational context. It lacks details on what fields are searched, how results are returned, or any constraints, making it insufficient for robust tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
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 explain the 'query' parameter at all. The agent must guess what 'query' means, and the description adds no value beyond the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search for Jira users' uses a specific verb ('search') and resource ('Jira users'), clearly stating what the tool does. It does not explicitly differentiate from sibling tools like 'search_issues', but the resource is distinct, so it meets the bar for clear purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description contains no context, exclusions, or mentions of related tools, leaving the agent to infer usage 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the action but does not convey that this is a write operation, any required permissions, potential side effects, or whether the comment is appending to existing ones. This is insufficient for a mutating tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and easy to parse. However, it is under-specified, lacking important context, which prevents a perfect score. Still, it earns a high mark for its brevity and clear structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two required parameters and no output schema, the description should at least mention the expected behavior (e.g., returns the created comment or success indicator) and any constraints. It provides only the basic action, leaving the agent without enough context to confidently invoke the tool in varied scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no extra meaning beyond parameter names. The parameters issueKey and comment are self-explanatory to some degree, but the description does not clarify formats, required values, or relationships. It fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add a comment to an issue' uses a specific verb ('Add') and resource ('comment to an issue'), clearly distinguishing it from sibling tools like get_comments (read) and create_issue (different resource). It is explicit about the action performed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_comments or transition_issue. There is no mention of prerequisites (e.g., issue existence) or context where adding a comment is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, but it only states the action. It doesn't disclose whether an existing assignee is overwritten, what happens if the assignee parameter is omitted, or any permissions required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that conveys the essential action with no redundant wording. It is appropriately brief for the simplicity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and minimal description, the tool lacks essential context. It doesn't mention return values, error conditions, or edge-case behavior such as unassignment when assignee is empty, making it incomplete for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description only implicitly links 'assignee' to 'a user' and 'issueKey' to 'an issue'. It fails to explain that assignee is optional or whether it expects a username, account ID, or email, leaving parameter meaning ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'assign' with the resource 'issue' and target 'user', clearly stating the core function. However, it doesn't explicitly differentiate from siblings like update_issue, which could also modify assignee, so it stops short of full distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There is no mention of prerequisites, or scenarios like assigning vs. unassigning an issue, and no contrast with update_issue or transition_issue.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only includes a vague caution, but does not state that deletion is permanent, irreversible, or has cascading effects on linked data or comments.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short ('Delete a Jira issue (use with caution!)') and front-loaded, with no wasted words. However, it is under-specified, though that is reflected in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations and no output schema, the description should provide more context such as expected outcomes, permissions required, or irreversibility. The current description is too minimal for an agent to safely invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
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 mention the issueKey parameter at all. There is no explanation of expected format, uniqueness, or how it is used, leaving the agent without essential semantic information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the resource ('a Jira issue'), making the tool's purpose unambiguous. It is distinct from sibling tools like update_issue or transition_issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'use with caution!' hints at destructive nature but provides no explicit guidance on when to use this tool versus alternatives. For example, it does not suggest considering transition_issue or other non-destructive options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'Get worklogs for an issue' and adds no details about return format, authentication, or limitations. The read-only nature is implied by 'Get' but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that conveys the core purpose with no filler. It is maximally concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter, the description is minimal but insufficient. It lacks any mention of output structure, error conditions, or relationship to other worklog tools. Given no output schema or annotations, more detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'issueKey' but schema_description_coverage is 0%. The description does not add any semantics beyond the schema—it only repeats that it's for an issue. No format, example, or constraints are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and the resource 'worklogs for an issue', clearly stating what the tool does. However, it does not distinguish from sibling tools like get_team_worklogs, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description simply states the action without providing context on selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It implies a read-only analysis operation but does not disclose side effects, required permissions, latency, or output format. The phrase 'NLP analysis' is too generic to convey behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the key action and resource. It contains no redundant words and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex NLP tool with no output schema and no annotations. The description fails to explain what 'smart suggestions' look like, what the tool returns, or how the analysis behaves. Significant context is missing for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both text and projectKey already described ('Issue description text' and 'Project for context'). The description adds marginal meaning by indicating text is the subject of analysis, but does not go beyond schema for projectKey. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs NLP analysis on issue text to produce smart suggestions, identifying a specific verb and resource. However, 'smart suggestions' is vague and does not specify the exact output or type of analysis, and it does not explicitly differentiate from sibling tools like create_smart_issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention prerequisites, typical use cases, or any exclusions, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It fails to mention that this is a read-only analysis, whether it makes external calls, what specific metrics are computed, or what the output structure looks like. The 'AI-powered' wording hints at complexity but leaves the operational behavior opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that front-loads the core purpose. It avoids excessive detail and is easy to parse. Slightly more specificity would be useful, but it is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that purportedly performs AI-driven analysis, the description is notably incomplete. It does not specify what metrics are analyzed, what kind of recommendations are generated, whether the result is a report or a visual, or any dependent data requirements. The absence of an output schema or annotations increases the need for descriptive completeness, which is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters (sprintId and boardId) have descriptive schema entries, achieving 100% schema coverage. The description adds no additional parameter context beyond this, so 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes sprint health and produces metrics and recommendations. It uses a specific verb ('analyze') and resource ('sprint health'), distinguishing it from sibling tools that deal with raw sprint data or issue management. However, 'AI-powered' is somewhat vague and doesn't fully define what health means.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_sprints or get_sprint_issues. There is no mention of use cases, prerequisites, or exclusions. The agent must infer usage solely from the tool name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral details. It only states 'AI-suggested' without explaining whether user-provided type/priority override the AI, how labels are handled (they aren't in the schema), or any permissions or side effects. The description also doesn't mention the return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with a clear verb-first structure. No fluff, but it could benefit from slightly more detail given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool creates an issue with AI-suggested fields, yet the description omits essential context: no output schema, no annotations, no behavior explanation for labels (missing from schema), and no clarification of parameter roles. It is not complete enough for an AI agent to use confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds some nuance for type and priority (AI-suggested) but fails to clarify the required text and projectKey parameters, nor how optional parameters interact with the AI suggestions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Create' with the resource 'issue' and adds 'AI-suggested type, priority, and labels' which clearly distinguishes it from the sibling create_issue tool. The purpose is immediately clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives like create_issue or analyze_issue_text. The AI-suggested aspect implies a use case, but no direct when-to-use or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It only restates the read action without mentioning response format, pagination, ordering, or any other runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It is concise and directly to the point, though slightly under-specified in content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description is too sparse. It tells the agent what the tool does but not what it returns, how many items, or any edge cases, making it incomplete for safe autonomous invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% since boardId has no description. The description only implies 'for a board' and does not explicitly define boardId or any constraints, leaving the sole parameter semantically under-specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get sprints for a board' clearly states a specific action (get) and resource (sprints), scoped by board. It distinguishes itself from sibling tools like get_boards and get_sprint_issues by naming a distinct resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_sprint_issues or get_boards. It lacks any mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only states the action without mentioning side effects, permissions, or what happens upon success/failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. However, its brevity borders on under-specification, so it earns a 4 rather than a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations or output schema, the description is insufficiently complete. It lacks details on return values, permissions, and any behavioral context needed for a write operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all 4 parameters with descriptions, so the baseline is 3. The description adds no additional parameter-specific context beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Log' and resource 'time worked on an issue', making the tool's function clear. It is distinct from sibling tools such as add_comment and get_worklogs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 add_comment or get_worklogs. There are no prerequisites, exclusions, or context cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It only restates the action without clarifying whether the operation is read-only, what response format to expect, or any required permissions. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary filler. It is appropriately sized for a simple tool and delivers its core message upfront, earning perfect marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the tool is simple with only one parameter, the lack of an output schema and annotations means the description should explain what the response contains (e.g., metadata, download links). It does not, leaving the agent without essential information about the expected return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'issueKey' is self-explanatory from its name, but the description adds no additional meaning. With schema description coverage at 0%, the description fails to compensate by explaining the expected format (e.g., 'PROJ-123') or how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving attachments for a given issue. It uses a specific verb 'Get' and resource 'attachments' with context 'on an issue', distinguishing it from sibling tools like get_issue or get_comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or contrast with similar tools, leaving the usage context purely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, and the description does not disclose any behavioral traits such as pagination, ordering, permissions, or error handling. It only restates the basic read operation implied by the name, which is insufficient without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only five words to convey the entire purpose. It is front-loaded with the main verb and resource, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 too minimal to be complete. It does not mention what the returned comments look like, any limitations, or the expected behavior when the issue is not found. It is sufficient for basic invocation but lacking in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter explanations. It does not explain the issueKey parameter beyond its name, lacking format, example, or any additional context. The parameter is simple, but the description fails to add meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (get) and the resource (comments) on a specific entity (an issue). It is unambiguous and distinct from sibling tools like get_issue or get_worklogs, as it specifically targets comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, no prerequisites, and no exclusions. It is a single declarative sentence without any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only says 'Get project details', which implies a read operation, but does not disclose any potential behavior such as permissions, rate limits, or response format. This is minimal and leaves the agent uninformed about side effects or error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no waste. It gets straight to the point, though it could be slightly more informative without sacrificing conciseness. It earns its place but does not elaborate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get operation with one parameter, the description is minimally adequate. However, there is no output schema and no annotation support, so the agent is left without details on return structure, error conditions, or prerequisites. Slightly more context would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 explain the projectKey parameter beyond its name. While the parameter name is self-explanatory, the description adds no extra meaning and fails to compensate for the lack of schema descriptions, which is required given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description "Get project details" clearly states a specific verb (Get) and resource (project details), distinguishing it from sibling tools such as get_projects (plural) and get_issue (different resource). It precisely conveys that this tool fetches a single project's information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_projects or get_issue. The description implies usage for a single project by its key, but does not explicitly mention alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It mentions retrieving 'all' boards but does not disclose pagination, permission requirements, or any potential limitations. The read-only nature is implied by 'Get' but not explicitly stated. This minimal transparency is insufficient for a tool without structured metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence: 'Get all Jira boards'. It is front-loaded and contains no unnecessary words, earning a perfect score for conciseness and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (no parameters, no output schema), so the description is adequate for basic understanding. However, it lacks any information about return format, potential size of results, or access restrictions. Given the lack of annotations and output schema, a bit more context (e.g., 'returns board objects') would be helpful. This is minimally sufficient but leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially complete (100% coverage). The description adds clarity by specifying 'all' boards, confirming there is no filtering. This aligns with the 0-parameter baseline and effectively communicates the lack of input parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves all Jira boards, using a specific verb ('Get') and resource ('boards'). It is not a tautology and the scope ('all') is explicit. However, it does not differentiate from sibling tools like 'get_projects' or 'get_sprints' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 simply states what it does, without specifying use cases, exclusions, or relationships to other list-type tools. An agent would have to infer that this is the go-to tool for listing boards.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It indicates a write operation to GitHub but does not state whether it overwrites existing files, creates a commit, requires authentication, or what the response looks like. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core action and target. It contains no fluff or redundant phrasing, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters, no output schema, and no annotations. While the purpose is clear and parameters are documented, the description omits operational details such as whether the tool creates a new file or updates an existing one, any side effects, or expected return values. For a write tool without annotations, the description is too minimal to fully guide an agent on what happens when invoked.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 and the description adds no additional parameter information beyond what is already in the schema. The description does not clarify how 'title', 'content', and 'path' interact (e.g., whether the title becomes the filename or how the path is combined), but the schema already describes each field adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Save') and clearly identifies the resource ('markdown content directly to a GitHub repository'). It distinguishes itself from sibling tools like save_release_notes_to_file by emphasizing 'any markdown content' rather than a specific report type, making the tool's general-purpose nature explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. It does not mention any conditions, prerequisites, or exclusions, nor does it reference related save_* tools that might be more appropriate for specific report types. The 'any markdown content' phrasing implicitly suggests broad usage, but there is no explicit 'when to use this' direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing side effects. 'Save to local file or GitHub' implies mutation, but it does not mention authentication requirements, overwrite behavior, or any implications of writing to GitHub. This is a significant gap for a tool that performs writes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise, front-loaded, and contains no fluff. It efficiently conveys the core action and destination, making it appropriately sized for the purpose it serves.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, no annotations, and no output schema, the description is severely under-specified. It does not explain how parameters relate to the GitHub vs local file options, date range semantics, or what the tool returns. The description is far from sufficient for reliable tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 7 parameters with 0% description coverage, and the description provides zero explanation of parameters like projectKey, version, startDate, endDate, githubRepo, githubOwner, or saveToGitHub. The description entirely fails to compensate for the schema's lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('generate') and resource ('release notes') with a clear destination ('local file or GitHub'), and distinguishes it from Confluence-related alternatives by noting 'no Confluence needed'. This clearly differentiates from sibling tools like generate_release_notes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when you want release notes saved locally or to GitHub. However, it does not explicitly name alternatives or give when-not-to-use guidance beyond the implicit 'no Confluence needed' hint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits such as side effects or permissions. It only states the action without mentioning that it is a write operation, may fail on invalid transitions, or could have irreversible consequences.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it concise and front-loaded. However, it omits critical details, so it is brief without being fully informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, output schema, or parameter guidance, this description is insufficient. It fails to mention the need to fetch valid transitions via get_transitions, what happens if the transition is invalid, or any required permissions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 explain the two parameters. While 'issueKey' is somewhat self-explanatory, 'transitionName' is ambiguous (could be a status name, transition ID, or something else) and is not elaborated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'move' with a clear resource ('issue') and outcome ('different status'), which precisely defines the tool's function. It distinguishes from sibling tools like update_issue by focusing specifically on status transitions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for changing an issue's status but provides no explicit guidance on when to use it versus update_issue, nor does it mention prerequisites like calling get_transitions to fetch valid transition names. There is no exclusion or alternative mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. 'Get details' is vague and does not specify what fields or data are returned, whether the issue includes comments, attachments, or only core fields, or any potential permissions or side effects. The description offers no more insight than the tool name itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that directly states the tool's purpose. It contains no filler or redundant information and is appropriately sized for the simple tool it describes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and absence of annotations or output schema, the description is minimally sufficient but incomplete. It does not specify what 'details' includes, which could matter for an agent deciding whether to call this tool or use search_issues or get_comments. The description is adequate but leaves gaps in behavioral expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a clear description for the only parameter issueKey (e.g., 'Issue key (e.g., PROJ-123)'). Since schema coverage is 100%, the description does not need to add parameter details. The baseline of 3 applies, and no additional context is given in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb (+resource) 'Get details of a specific Jira issue', which clearly identifies the tool's function and distinguishes it from sibling tools like search_issues (multiple issues) or get_projects (projects). It leaves no ambiguity about what resource this tool targets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as search_issues for finding issues or get_project for project-level details. It does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only says 'Get available transitions', which essentially restates the tool name. It does not disclose whether the operation is read-only, what a transition is, or what the response contains. Minimal behavioral context beyond 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is concise but slightly under-specified, earning a high but not perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only one parameter, and the schema communicates the required input. However, without an output schema or annotations, the description does not explain the meaning of 'transitions' or the nature of the return value. Adequate for a minimal tool but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'issueKey' and zero description coverage. The description does not explain the parameter. While the parameter name is self-explanatory, the description adds no meaning beyond the schema, and the low schema coverage requires compensation that is absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get available transitions for an issue' uses a specific verb ('Get') and clear resource ('available transitions') and object (an issue). It clearly distinguishes itself from siblings like 'transition_issue' by indicating it's a retrieval rather than an action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by the verb 'Get' and the resource 'transitions', but it does not explicitly state when to use this tool versus alternatives like 'transition_issue' or 'get_issue'. The distinction is inferable but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It reveals only that it performs a search via JQL, without disclosing return format, pagination behavior, or whether any side effects occur. Since 'search' implies a read-only operation, this is somewhat apparent, but the description adds no further context about limits or output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single six-word sentence, 'Search Jira issues using JQL,' that is efficient and front-loaded. Every word contributes to conveying the core purpose without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with two fully documented parameters and no output schema. The description explains the basic action but lacks usage guidance and behavioral details such as pagination behavior or return format. Given no annotations, a bit more context would improve completeness, but the essential operation is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, as both parameters (jql, maxResults) have descriptions. The description's mention of 'using JQL' aligns with the jql parameter but adds no additional meaning beyond the schema. Baseline 3 is appropriate because the schema already documents parameters fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search Jira issues using JQL' clearly states a specific verb (search) and resource (Jira issues) with a method (JQL). It distinguishes this from siblings like get_issue (single issue) and get_sprint_issues (sprint-specific queries) by indicating a flexible JQL search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or cases where get_issue or get_my_issues might be more appropriate. The JQL search intent is implied but not contrasted with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It only says 'generate and save' without addressing file overwrite behavior, return values, authentication requirements, or side effects like creating GitHub repos. This leaves significant behavioral ambiguity 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the main verb and resource, and contains no filler. Every word contributes to the meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no annotations, and no output schema, the description is too sparse. It doesn't explain what happens when saving locally vs GitHub, what the report contains, or what the tool returns after saving. This leaves the agent without enough context to anticipate the tool's full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all 5 parameters with descriptions, so the baseline is 3. The description adds no parameter-level detail beyond the schema, such as how saveToGitHub interacts with githubRepo/githubOwner or what boardId influences.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates and saves a sprint report, with explicit destination options (local file or GitHub). This distinguishes it from sibling tools like save_workload_report or save_release_notes_to_file, making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for saving sprint reports but provides no explicit guidance on when to choose this over alternative save tools or when not to use it. There is no mention of prerequisites (e.g., GitHub auth) or relationship to other report tools, so the 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the operation is a read ('Get all'), but provides no additional details such as return format, pagination, or any limitations. This is minimally transparent but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler words. Every word earns its place, making it exemplary in conciseness and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, zero-parameter read-only tool, the description adequately captures its purpose. The lack of an output schema or annotations does not require more explanation, though mentioning the return type would have been a small improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so description-based parameter explanations are unnecessary. Per the rubric, 0 params yields a baseline of 4, and the description does not need to add parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get all Jira projects' uses a specific verb ('Get') and clearly identifies the resource ('Jira projects') and scope ('all'), making it distinct from the sibling 'get_project' which implies a single project. This directly states what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a complete list of projects is needed, but it does not explicitly mention alternatives or exclusions. For example, it fails to contrast with 'get_project' for single-project lookups, so usage guidance is only implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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