mcp-github-project-manager

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tool set covers distinct GitHub project management operations, but there is significant overlap in AI-powered analysis tools (e.g., analyze_task_complexity, enrich_issue, expand_task, generate_prd, parse_prd) that could confuse an agent about which to use for similar tasks. Core CRUD operations are clearer, but the AI tools blur boundaries.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., create_issue, update_project, list_sprints), with clear action-object naming. Minor deviations exist (e.g., get_next_task vs. plan_sprint), but overall naming is predictable and readable across the set.
Tool Count2/5
With 84 tools, the count is excessive for a GitHub project manager server, leading to bloat and potential confusion. Many tools could be consolidated (e.g., multiple AI analysis tools, separate CRUD for similar entities), making the surface unwieldy and overwhelming for agents.
Completeness5/5
The tool set provides comprehensive coverage for GitHub project management, including full CRUD for projects, issues, PRs, sprints, milestones, and fields, plus advanced features like automation rules, AI-powered analysis, and traceability matrices. No obvious gaps exist for the domain.
Average 2.7/5 across 84 of 84 tools scored. Lowest: 1.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No issues in the last 6 months
- No commit activity data available
- Last stable release on February 1, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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This repository includes a glama.json configuration file.
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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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Create a new milestone' implies a write/mutation operation but reveals nothing about permissions required, whether creation is idempotent, what happens on success/failure, rate limits, or what the response contains. This is inadequate 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single three-word phrase—which is appropriately sized for a simple concept. However, it's under-specified rather than efficiently informative. It's front-loaded but lacks substance, so while it's not verbose, it doesn't earn its place with useful content.
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 (a mutation operation with 3 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what the tool does beyond the name, how to use it, what the parameters mean, or what to expect in return. This leaves critical gaps for an AI agent.
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 none of the 3 parameters (title, description, dueDate) are documented in the schema. The description provides no information about these parameters—not their purpose, format constraints (e.g., date format for dueDate), or examples. It fails to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a new milestone' is a tautology that restates the tool name without adding specificity. It doesn't explain what a milestone is in this context, what resource it creates, or how it differs from similar tools like 'create_sprint' or 'create_project' in the sibling list. The verb 'create' is clear but the object 'milestone' lacks definition.
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?
No guidance is provided about when to use this tool versus alternatives. The sibling list includes related tools like 'create_sprint', 'create_project', and 'update_milestone', but the description offers no comparison or context about appropriate use cases, 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 behavioral disclosure. 'List milestones' offers no insight into whether this is a read-only operation, its potential side effects, authentication requirements, rate limits, or output format. For a tool with three parameters and no output schema, this lack of behavioral context is a significant 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 extremely concise at two words, with zero wasted text. It is front-loaded and efficiently states the core action, though this brevity comes at the cost of completeness. Every word earns its place by directly addressing the tool's function, albeit minimally.
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 (three parameters, no output schema, no annotations), the description is grossly inadequate. It does not explain what the tool returns, how parameters affect results, or behavioral traits. For a list operation with filtering and sorting capabilities, this leaves critical gaps in understanding how to use the tool effectively.
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 0% description coverage, meaning parameters 'status', 'sort', and 'direction' are entirely undocumented in the schema. The description adds no information about these parameters—their meanings, allowed values, or usage—failing to compensate for the schema's deficiencies. This leaves the agent with no semantic understanding of the inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List milestones' is a tautology that merely restates the tool name without adding meaningful context. It specifies the verb 'list' and resource 'milestones' but lacks any detail about scope, format, or what distinguishes it from sibling tools like 'get_milestone_metrics', 'get_overdue_milestones', or 'get_upcoming_milestones'. This minimal statement fails to clarify the tool's specific purpose beyond the obvious.
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 any context, prerequisites, or exclusions, nor does it reference sibling tools that might serve similar purposes (e.g., filtered milestone queries). Without such information, an agent cannot make informed decisions about tool selection.
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?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't mention that this is a mutation operation, what permissions are required, whether changes are reversible, what happens to unspecified fields, or any rate limits. The description fails to provide any behavioral context beyond the basic verb.
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 maximally concise with a single clear sentence. There's no wasted verbiage or unnecessary elaboration, though this conciseness comes at the cost of completeness. Every word earns its place in stating the basic operation.
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?
For a complex mutation tool with 6 parameters (including nested objects), 0% schema coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what an automation rule is, what fields can be updated, what the expected behavior is, or what the tool returns. The description fails to provide the necessary context for proper 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?
With 0% schema description coverage and 6 parameters (including complex nested objects for triggers and actions), the description provides zero information about parameters. It doesn't mention the required 'ruleId', the optional fields like 'name' or 'enabled', or the structure of triggers and actions arrays. The description fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update an existing automation rule' is a tautology that restates the tool name without adding specificity. It mentions the verb 'update' and resource 'automation rule' but doesn't distinguish what aspects can be updated or how this differs from other automation tools like 'enable_automation_rule' or 'disable_automation_rule'.
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 zero guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like needing an existing rule ID), when this should be used instead of creating/deleting rules, or how it relates to sibling tools like 'create_automation_rule' or 'delete_automation_rule'.
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 fully disclose behavioral traits. It only states the action without any details on permissions required, whether the removal is reversible, side effects (e.g., if it affects issue status or sprint metrics), error handling, or rate limits. This is a critical gap for a mutation tool, making it opaque and risky for an agent to use.
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 at three words, with no wasted language. It's front-loaded and to the point, making it easy to parse quickly. While brevity can lead to underspecification, in terms of structure and efficiency, it earns full marks.
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 complexity of a mutation tool with no annotations, 2 undocumented parameters, and no output schema, the description is severely incomplete. It fails to explain behavior, parameters, or expected outcomes, leaving the agent without enough context to use the tool safely or effectively. This is inadequate for the tool's requirements.
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 input schema provides no descriptions for the parameters. The description adds no semantic information about 'sprintId' or 'issueIds', such as format examples, constraints, or what constitutes valid values. For a tool with 2 required parameters, this leaves the agent guessing, resulting in a low score.
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 'Remove issues from a sprint' clearly states the action (remove) and target (issues from a sprint), which is better than a tautology. However, it lacks specificity about what 'remove' entails (e.g., unassigning vs. deleting) and doesn't distinguish it from sibling tools like 'remove_project_item' or 'clear_field_value', which might have overlapping functionality. It's vague but functional.
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 doesn't mention prerequisites (e.g., needing an existing sprint or valid issue IDs), exclusions, or related tools like 'add_issues_to_sprint' for context. This leaves the agent to infer usage from the name alone, which is insufficient for effective tool selection.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides almost none. 'List all sprints' doesn't indicate whether this is a read-only operation, what permissions might be required, whether results are paginated, what format the output takes, or any rate limits. For a tool with no annotation coverage, this minimal description is inadequate.
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 maximally concise at just three words. There's no wasted language or unnecessary elaboration. While this conciseness comes at the cost of completeness, from a pure brevity perspective, it's perfectly efficient.
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 no annotations, no output schema, and a parameter with 0% schema description coverage, the description 'List all sprints' is completely inadequate. It doesn't explain the required parameter, doesn't describe the output format, doesn't provide behavioral context, and creates confusion about what 'all' means given the required status parameter. For a tool in this context, the description fails to provide necessary information.
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 shows one required parameter 'status' with 0% description coverage. The tool description 'List all sprints' doesn't mention any parameters at all, creating a contradiction - if it lists 'all' sprints, why is a 'status' parameter required? The description fails to explain what the status parameter does, what values it accepts, or how filtering by status relates to 'all' sprints.
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 'List all sprints' clearly states the verb ('List') and resource ('sprints'), making the basic purpose understandable. However, it's vague about scope - 'all' could mean all sprints in the system, all sprints for a project, or all sprints with a specific status. It doesn't distinguish from sibling tools like 'get_current_sprint' or 'get_sprint_metrics' which also retrieve sprint 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?
The description provides no guidance on when to use this tool versus alternatives. There are multiple sibling tools that retrieve sprint information (get_current_sprint, get_sprint_metrics), but the description doesn't explain when list_sprints is appropriate versus those other options. No context about prerequisites, limitations, or typical use cases is 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'AI-powered' which hints at automation, but doesn't explain what 'enrichment' entails (e.g., adding metadata, categorizing, prioritizing), whether it's read-only or mutative, what permissions are needed, or any rate limits. For a bulk operation with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that's front-loaded with key information ('Bulk AI-powered issue enrichment'). There's no wasted verbiage, though it could benefit from slightly more detail given the complexity. It's appropriately sized for a tool description.
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 complexity (bulk AI operation with 4 parameters), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what enrichment does, what the inputs mean, what the output looks like, or any behavioral constraints. For a tool that likely performs significant processing, this leaves too much undefined.
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 all 4 undocumented parameters. The description mentions 'bulk' and 'multiple issues' which loosely relates to 'issueIds', but doesn't explain 'projectId', 'projectContext', or 'autoApply' parameters. It adds minimal semantic value beyond what's implied by the tool name, failing to address the coverage gap.
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 'Bulk AI-powered issue enrichment for multiple issues at once' clearly states the action (enrichment) and resource (issues), and specifies it's for multiple issues. However, it doesn't distinguish this from the sibling 'enrich_issue' tool, which appears to be a single-issue version. The purpose is clear but lacks sibling differentiation.
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 'enrich_issue' or other issue-related tools. It mentions 'bulk' and 'multiple issues at once' which implies scale, but doesn't specify thresholds, prerequisites, or when not to use it. No explicit alternatives or contextual boundaries are provided.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides none. It doesn't indicate whether this is a read-only operation, what permissions are required, what happens if no sprint is active, or what the return format looks like. For a tool with zero annotation coverage, this is a significant 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 perfectly concise at just 4 words. It's front-loaded with the core purpose and contains no wasted words. Every word earns its place in communicating the essential function.
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 no annotations, no output schema, and 0% schema description coverage for its single parameter, the description is incomplete. It doesn't explain what 'includeIssues' does, what the return format looks like, or behavioral aspects like error conditions. For a tool with this complexity profile, the description should provide more context.
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 description coverage is 0%, meaning the single parameter 'includeIssues' is completely undocumented in the schema. The description provides no information about this parameter - not what it does, what values it accepts, or how it affects the response. The description fails to compensate for the schema's lack of 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 states the verb ('Get') and resource ('currently active sprint'), making the purpose immediately understandable. It distinguishes from siblings like 'get_sprint_metrics' or 'list_sprints' by focusing on the current/active sprint specifically. However, it doesn't explicitly contrast with 'get_current_iteration' which might be a similar concept.
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. There's no mention of prerequisites, when-not-to-use scenarios, or comparison with sibling tools like 'get_current_iteration' or 'get_sprint_metrics'. The agent must 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.
Behavior1/5
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 but provides almost none. 'List GitHub projects' doesn't indicate whether this is a read-only operation, what permissions are required, whether it's paginated, what format the output takes, or any rate limits. For a tool with 2 parameters and no output schema, this leaves critical behavioral aspects unspecified.
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 maximally concise at just three words, with no wasted language. It's front-loaded with the core action and resource. While this conciseness comes at the expense of completeness, as a standalone statement it's efficiently structured.
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 2 parameters with 0% schema coverage, no annotations, no output schema, and many sibling tools, the description is completely inadequate. It doesn't explain what the tool returns, how to use its parameters, when to choose it over alternatives, or any behavioral characteristics. For a listing tool in a complex GitHub project management context, this leaves too many gaps.
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 description provides zero information about the tool's 2 parameters (status and limit), despite 0% schema description coverage. The schema shows 'status' is required and 'limit' is optional, but the description doesn't explain what values 'status' accepts, what it filters by, what 'limit' controls, or their expected formats. With no parameter guidance in either schema or description, this is inadequate.
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 'List GitHub projects' clearly states the verb ('List') and resource ('GitHub projects'), making the tool's purpose immediately understandable. It distinguishes this as a read operation rather than a creation or modification tool. However, it doesn't specify what aspects of projects are listed or how they differ from other list tools like 'list_project_items' or 'list_project_views'.
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. With many sibling tools like 'get_project', 'list_project_items', and 'list_project_views', there's no indication of when this specific listing tool is appropriate versus those other options. No prerequisites, exclusions, or comparison context is provided.
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 full burden for behavioral disclosure. It states only the basic action ('List') without any information about permissions required, rate limits, pagination behavior, error conditions, or output format. This leaves critical behavioral aspects undocumented for a read operation.
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, straightforward sentence with no wasted words. It's front-loaded with the core purpose and appropriately sized for a simple-sounding tool, though this conciseness comes at the expense of completeness.
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 no annotations, no output schema, and 0% schema description coverage for its two parameters, the description is incomplete. It omits essential context: parameter meanings, behavioral traits (like pagination or authentication), and how results are returned. For a list operation with parameters, this leaves too much undefined.
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 neither parameter ('state' or 'perPage') has any documentation in the schema. The description provides no information about these parameters—not their purpose, allowed values (e.g., 'open', 'closed', 'all' for state), or defaults. With two undocumented parameters, the description fails to compensate for the schema gap.
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 ('List') and resource ('pull requests in a GitHub repository'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_pull_request' (singular) or 'list_pull_request_reviews', but the verb+resource combination is specific enough for basic understanding.
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 doesn't mention sibling tools like 'get_pull_request' (for single PR details) or 'list_pull_request_reviews', nor does it specify use cases like filtering, pagination needs, or repository context requirements. The agent must 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 behavioral disclosure. It mentions 'AI-powered analysis' and 'comprehensive list of actionable development tasks', but doesn't describe what the tool actually does behaviorally - whether it creates records, modifies data, requires specific permissions, has rate limits, or what format the output takes. The description is too vague about the actual behavior beyond the basic purpose statement.
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 reasonably concise - just one sentence. However, the 'similar to claude-task-master functionality' comparison adds questionable value without explanation. The structure is front-loaded with the core purpose, but the comparison feels tacked on rather than integral to understanding 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?
For a complex tool with 18 parameters (14 required), no annotations, no output schema, and 0% schema description coverage, the description is severely inadequate. It provides only a high-level purpose statement without explaining the extensive parameter set, expected outputs, behavioral characteristics, or how this differs from related sibling tools. The description doesn't meet the needs of such a complex 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 description provides zero information about any of the 18 parameters. With schema description coverage at 0%, the description fails completely to compensate by explaining what parameters like 'prdContent', 'maxTasks', 'autoEstimate', or the 16 other parameters mean or how they affect the parsing. This leaves the agent with no semantic understanding of the inputs.
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's purpose: 'Parse a Product Requirements Document (PRD) and generate a comprehensive list of actionable development tasks with AI-powered analysis.' It specifies the verb (parse), resource (PRD), and output (development tasks). However, it doesn't explicitly differentiate from sibling tools like 'enhance_prd' or 'generate_prd', which appear related but have different functions.
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 mentions 'similar to claude-task-master functionality' as a reference point, but doesn't specify when this tool is appropriate compared to siblings like 'enhance_prd' or 'analyze_task_complexity'. There's no mention of prerequisites, constraints, or typical use cases.
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 implies a complex write operation ('add', 'analyze', 'expand', 'manage lifecycle') but doesn't specify permissions needed, whether changes are reversible, rate limits, or what the output looks like. The description is vague on implementation details, leaving critical behavioral traits unclear.
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 run-on sentence that packs multiple actions ('add', 'analyze', 'expand', 'manage'), making it somewhat dense but not excessively verbose. It could be more structured by separating distinct phases, but it avoids unnecessary fluff and gets straight to the point.
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 complexity (10 parameters, 6 required, no output schema, no annotations), the description is inadequate. It outlines high-level functionality but lacks details on parameter usage, behavioral constraints, output format, and differentiation from siblings. For a tool with such a broad scope and many inputs, more comprehensive guidance 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?
Schema description coverage is 0%, so the description must compensate for all 10 parameters. It mentions 'feature', 'PRD or project', 'impact analysis', 'actionable tasks', and 'lifecycle management', which loosely map to some parameters like 'featureIdea' and 'targetPRD', but fails to explain the purpose or format of most parameters (e.g., 'autoApprove', 'expandToTasks', 'createLifecycle'), leaving significant gaps in understanding.
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's purpose: 'Add a new feature to an existing PRD or project, analyze its impact, and expand it into actionable tasks with complete lifecycle management.' It specifies the verb ('add'), resource ('feature'), and scope ('PRD or project'), though it doesn't explicitly differentiate from siblings like 'enhance_prd' or 'expand_task'.
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 doesn't mention prerequisites (e.g., needing an existing PRD/project), exclusions, or comparisons to sibling tools like 'enhance_prd' or 'create_issue', leaving the agent without contextual usage 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 burden. It mentions 'Add' implying a write operation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, error handling, or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently states the core action, making it easy to parse quickly. Every word earns its place, achieving optimal conciseness for such a brief statement.
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 complexity (a mutation tool with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover parameter meanings, behavioral context, or return values, leaving the agent with insufficient information to use the tool effectively. This is inadequate for a tool of this nature.
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 parameters are undocumented in the schema. The description doesn't add any meaning beyond the schema—it doesn't explain what 'projectId', 'contentId', or 'contentType' represent, their formats, or examples. With low coverage, the description fails to compensate, leaving parameters ambiguous.
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 states the action ('Add') and target ('item to a GitHub project'), which is clear but vague. It doesn't specify what kind of item (issue, pull request, etc.) or differentiate from siblings like 'create_issue' or 'create_draft_issue', which also add items to projects. The purpose is understandable but lacks specificity.
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. Sibling tools like 'create_issue' or 'create_draft_issue' might serve similar purposes, but the description doesn't clarify prerequisites, context, or exclusions. This leaves the agent guessing about appropriate usage scenarios.
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 burden for behavioral disclosure. 'Get a list' implies a read operation, but it doesn't specify permissions needed, pagination behavior, rate limits, or what 'overdue' means (e.g., based on due dates vs. completion status). The description is too minimal for a tool that likely queries time-sensitive data.
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 at just one sentence with no wasted words. It's front-loaded with the core purpose, though this brevity comes at the cost of completeness. Every word earns its place in conveying the basic function.
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 with 2 required parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes 'overdue', how results are returned, or provide any context about the parameters. The minimal description leaves too many gaps for effective tool 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?
With 0% schema description coverage for both parameters (limit and includeIssues), the description adds no semantic information about what these parameters do. It doesn't explain what 'limit' controls (e.g., max results) or what 'includeIssues' means (e.g., whether to fetch associated issues). The description fails to compensate for the schema's lack of documentation.
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 'Get a list of overdue milestones' clearly states the verb ('Get') and resource ('overdue milestones'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_milestone_metrics' or 'get_upcoming_milestones', leaving the scope differentiation unclear.
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. With sibling tools like 'get_milestone_metrics' and 'get_upcoming_milestones' available, there's no indication of what makes 'overdue' milestones distinct or when this specific query 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'List GitHub issues' implies a read-only operation but doesn't specify permissions, rate limits, pagination, or output format. This leaves critical behavioral traits undocumented for a tool with 7 parameters.
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 with just three words, making it front-loaded and efficient. There's no wasted verbiage, though this brevity contributes to gaps 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 tool with 7 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter usage, behavioral constraints, or output expectations, leaving the agent with insufficient context for effective 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 description coverage is 0%, so parameters like 'status', 'milestone', 'labels', 'assignee', 'sort', 'direction', and 'limit' are completely undocumented in the schema. The description adds no semantic information about these parameters, failing to compensate for the coverage gap.
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 'List GitHub issues' clearly states the verb ('List') and resource ('GitHub issues'), making the basic purpose understandable. However, it doesn't differentiate from sibling tools like 'get_issue' (singular) or 'list_project_items', leaving ambiguity about scope and specificity.
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. With siblings like 'get_issue' (for single issues), 'list_project_items' (for project-specific items), and 'triage_all_issues' (for triaging), the description offers no 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 provided, so the description carries the full burden of behavioral disclosure. 'Update' implies a mutation operation, but the description doesn't specify required permissions, whether changes are reversible, rate limits, or what the response looks like (e.g., success confirmation or error handling). For a mutation tool with 7 parameters and no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action ('Update a GitHub issue'), making it easy to scan. Every word earns its place, though it may be overly concise 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?
Given the tool's complexity (7 parameters, mutation operation, no output schema, and no annotations), the description is incomplete. It doesn't cover parameter meanings, behavioral details, or usage context. For a tool that modifies data in a system like GitHub, more information is needed to ensure correct invocation, especially with siblings like 'create_issue' and 'update_issue_comment' present.
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%, meaning none of the 7 parameters have descriptions in the schema. The tool description adds no information about parameters beyond what's inferred from the name (e.g., 'issueId' for identifying the issue). It doesn't explain what fields like 'milestoneId' or 'assignees' represent, their formats, or constraints. With low coverage, the description fails to compensate.
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 'Update a GitHub issue' clearly states the verb ('Update') and resource ('GitHub issue'), which is better than a tautology. However, it lacks specificity about what aspects can be updated and doesn't differentiate from sibling tools like 'update_issue_comment' or 'update_milestone' that also update GitHub entities. The purpose is understandable but generic.
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 doesn't mention prerequisites (e.g., needing an existing issue ID), when not to use it (e.g., for creating new issues vs. updating), or refer to sibling tools like 'create_issue' for initial creation. Usage is implied from the name but not explicitly 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Update' implies a mutation operation, but the description doesn't state whether this requires specific permissions, what happens to existing sprint data not mentioned in the update, whether changes are reversible, or any rate limits. It lacks critical context 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, efficient sentence with zero wasted words. It's appropriately sized for a basic tool definition, though this conciseness comes at the cost of detail 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?
Given the complexity (a mutation tool with 6 parameters, no annotations, and no output schema), the description is inadequate. It doesn't compensate for the lack of structured data, failing to explain parameter meanings, behavioral traits, or expected outcomes. For a tool that modifies development sprints, more context is needed to guide proper usage.
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 description coverage is 0%, meaning none of the 6 parameters are documented in the schema. The description adds no information about parameters beyond what's implied by the tool name ('sprint' suggests sprintId). It doesn't explain the purpose of fields like title, description, dates, or status, leaving the agent to guess based on parameter names alone.
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 'Update a development sprint' clearly states the verb ('update') and resource ('development sprint'), providing a basic understanding of the tool's function. However, it doesn't distinguish this tool from sibling tools like 'update_issue' or 'update_milestone' beyond the resource type, and it lacks specificity about what aspects of a sprint can be updated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention prerequisites (e.g., needing an existing sprint), exclusions, or comparisons to sibling tools like 'create_sprint' or 'plan_sprint'. The agent must infer usage solely from the tool name and input schema.
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 mentions 'AI-powered analysis' but doesn't detail what that entails—such as whether it's a read-only operation, if it modifies data, requires specific permissions, has rate limits, or what the output format might be. For a tool with 8 parameters and no output schema, this lack of behavioral context is a significant gap, though it doesn't contradict any annotations.
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 that front-loads the core action ('Perform detailed AI-powered analysis') and lists key outputs. There's no wasted verbiage, and it's appropriately sized for a high-level overview. However, it could be more structured by explicitly separating inputs from outputs or adding brief usage notes.
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 complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the tool's behavior, parameter roles, or expected outputs, leaving the agent with inadequate information to use it effectively. While it states the purpose clearly, the lack of guidance, transparency, and parameter details makes it insufficient for a tool of this nature.
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 schema provides no parameter details. The description lists analysis aspects ('task complexity, effort estimation, risk assessment, actionable recommendations'), which loosely map to some parameters like 'includeBreakdown' or 'includeRisks', but it doesn't explain what each parameter means, their expected formats, or how they influence the analysis. With 8 parameters (6 required), this minimal compensation is insufficient.
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's purpose with specific verbs ('perform detailed AI-powered analysis') and resources ('task complexity, effort estimation, risk assessment'), and it mentions providing 'actionable recommendations'. It distinguishes itself from most sibling tools, which focus on CRUD operations or specific project management tasks, by offering analytical capabilities. However, it doesn't explicitly differentiate from potential analytical siblings like 'enhance_prd' or 'generate_prd', which might also involve analysis.
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 doesn't mention prerequisites, such as needing task details or team context, or specify scenarios where this analysis is beneficial (e.g., during sprint planning or risk assessment phases). With many sibling tools for task and project management, the lack of usage context leaves the agent guessing about appropriate application.
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 full burden. It discloses that archiving hides items without deletion, which is useful behavioral context. However, it lacks details on permissions required, whether the action is reversible, rate limits, or what happens to dependent data, leaving significant gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and adds clarifying context without waste. Every word earns its place, 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?
For a mutation tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers the basic effect of archiving but misses parameter details, usage context, permissions, and behavioral nuances needed for safe and effective use.
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 provides no information about the parameters 'projectId' and 'itemId'. It doesn't explain what these IDs represent, how to obtain them, or their format, failing to compensate for the lack of schema 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 states the action ('Archive an item') and resource ('in a GitHub project'), with specific clarification that archived items are hidden but not deleted. However, it doesn't explicitly differentiate from sibling tools like 'remove_project_item' or 'unarchive_project_item', which would require 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?
The description provides no guidance on when to use this tool versus alternatives like 'remove_project_item' or 'unarchive_project_item', nor does it mention prerequisites or context for archiving. It only explains what archiving does, not when it's 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, the description carries full burden. It states the tool 'removes/clears the value', implying a destructive mutation, but doesn't disclose permissions needed, whether the change is reversible, rate limits, or what happens to the field after clearing (e.g., becomes null/empty). It lacks behavioral context beyond the basic action.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, 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?
For a destructive mutation tool with 3 undocumented parameters, 0% schema coverage, and no output schema, the description is inadequate. It doesn't compensate for the missing parameter documentation or provide necessary behavioral context, making it incomplete for safe and effective use.
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 provides no information about the three required parameters (projectId, itemId, fieldId). It doesn't explain what these IDs represent, their format, or how to obtain them, leaving parameters completely undocumented.
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 ('Clear a field value') and resource ('for a GitHub project item'), specifying it works for 'any field type'. It distinguishes from sibling 'set_field_value' by focusing on removal rather than assignment, though it doesn't explicitly name that sibling.
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 'set_field_value' (for setting values) or 'remove_project_item' (for deleting entire items). The description mentions it works for 'any field type' but doesn't specify prerequisites or constraints.
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. While it mentions 'AI-powered improvements' and lists enhancement types, it doesn't cover critical aspects like whether this is a read-only or mutation operation, potential side effects, authentication needs, rate limits, or output format. For a tool with 9 parameters and no annotations, this is a significant gap.
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 that front-loads the core purpose. It avoids unnecessary words and gets straight to the point. However, it could be more structured by separating the 'what' from the 'how' aspects of enhancement.
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 complexity (9 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain what the tool returns, how enhancements are applied, error conditions, or the relationship between parameters. For a tool that presumably modifies content, this leaves too many unknowns for proper agent usage.
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?
With 0% schema description coverage and 9 parameters (7 required), the description provides no information about parameter meanings, relationships, or usage. It doesn't explain what 'enhancementType' values represent, how 'focusAreas' should be used, or what format 'prdContent' expects. The description fails to compensate for the complete lack of schema 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 states the tool's purpose: 'Enhance an existing PRD with AI-powered improvements, adding missing elements, improving clarity, and providing comprehensive analysis.' It specifies the verb ('enhance'), resource ('existing PRD'), and scope of improvements. However, it doesn't explicitly differentiate from sibling tools like 'generate_prd' or 'parse_prd', which would be needed for a score of 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?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, when not to use it, or how it differs from related tools like 'generate_prd' or 'enrich_issue'. The agent must infer usage from the purpose statement 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 full burden of behavioral disclosure. It mentions 'AI-powered analysis' and 'implementation recommendations', which hint at generative behavior, but doesn't detail output format, error handling, rate limits, or side effects. For a tool with 11 parameters and no output schema, this leaves significant gaps in understanding how the tool behaves and what it returns.
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, well-structured sentence that efficiently conveys the core functionality. It's front-loaded with the main purpose and adds key features without unnecessary elaboration. However, given the complexity of the tool (11 parameters, no annotations), it might benefit from slightly more detail to justify its 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?
For a tool with 11 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain parameter semantics, output format, or behavioral constraints. While it clearly states the purpose, it lacks the depth needed for an agent to confidently use this tool in context with its many siblings in project management workflows.
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%, meaning none of the 11 parameters have descriptions in the schema. The tool description doesn't mention any parameters or explain their meanings (e.g., what 'currentComplexity' vs 'targetComplexity' represent, how 'maxSubtasks' works). This forces the agent to guess parameter purposes based solely on property names, which is inadequate for effective tool invocation.
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's purpose: 'Break down a complex task into smaller, manageable subtasks with AI-powered analysis, dependency detection, and implementation recommendations.' It specifies the verb ('break down'), resource ('complex task'), and key capabilities (analysis, dependency detection, recommendations). However, it doesn't explicitly differentiate from sibling tools like 'analyze_task_complexity' or 'plan_sprint', which might have overlapping functions.
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 mentions the tool's function but doesn't specify contexts, prerequisites, or exclusions. With many sibling tools in project management contexts (e.g., 'analyze_task_complexity', 'plan_sprint'), the lack of comparative guidance leaves the agent uncertain about optimal tool 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool provides 'AI-powered recommendations' but doesn't clarify key behavioral aspects: whether it's a read-only operation, how it handles missing data, if it requires specific permissions, what the output format looks like, or any rate limits. For a tool with 10 parameters and no output schema, this lack of detail is a significant gap.
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, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action ('Get AI-powered recommendations') and includes key contextual elements. However, it could be slightly more concise by avoiding the repetition of 'based on' phrasing, but overall it's appropriately sized for 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?
Given the tool's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, parameter meanings, output format, and usage guidelines. While it states the purpose clearly, it doesn't provide enough context for an agent to effectively select and invoke this tool, especially compared to siblings with similar functions like 'plan_sprint'.
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 description coverage is 0%, meaning none of the 10 parameters are documented in the schema. The description mentions general factors like 'priorities, dependencies, team capacity, and current project state', which loosely map to some parameters (e.g., 'teamSkills', 'sprintCapacity', 'currentPhase'), but it doesn't explain what individual parameters do, their expected formats, or how they influence the recommendations. This fails to compensate for the poor schema coverage.
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's purpose: 'Get AI-powered recommendations for the next task to work on based on priorities, dependencies, team capacity, and current project state.' It specifies the verb ('Get AI-powered recommendations') and resource ('next task'), and mentions key factors like priorities and dependencies. However, it doesn't explicitly distinguish this from sibling tools like 'plan_sprint' or 'analyze_task_complexity', which might have overlapping functionality.
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 mentions factors like 'priorities, dependencies, team capacity, and current project state' but doesn't specify scenarios where this tool is preferred over siblings such as 'plan_sprint' or 'get_current_iteration'. There's no mention of prerequisites, exclusions, or typical use cases, leaving the agent with minimal contextual 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 the full burden of behavioral disclosure. It states 'Set a field value', implying a mutation/write operation, but doesn't clarify permissions required, whether it overwrites existing values, error handling (e.g., invalid field types), or side effects. The list of supported field types adds some context but lacks operational details like rate limits or authentication needs.
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 that front-loads the core action and resource. The list of field types is relevant and adds value without unnecessary elaboration. There's no wasted text, though it could be slightly more structured (e.g., separating core purpose from details).
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's complexity (a mutation with 4 parameters), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions or errors, parameter semantics, or return values. For a write operation in a GitHub context, this leaves significant gaps for an AI agent to operate safely and effectively.
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 schema provides no parameter details. The description mentions 'field types' (e.g., TEXT, NUMBER) but doesn't explain how the 'value' parameter maps to these types or what formats are expected (e.g., string representation of dates). It also doesn't clarify what 'projectId', 'itemId', and 'fieldId' refer to (e.g., numeric IDs, names), leaving parameters largely undocumented.
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 ('Set a field value') and resource ('for a GitHub project item'), making the purpose unambiguous. It also lists the supported field types, which adds specificity. However, it doesn't explicitly differentiate from sibling tools like 'clear_field_value' or 'get_field_value', though the verb 'Set' implies a write operation distinct from 'get'.
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 doesn't mention prerequisites (e.g., needing a project, item, and field to exist), compare it to sibling tools like 'clear_field_value' or 'update_project_field', or specify contexts where it's appropriate. The agent must infer usage from the tool name and parameters 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 full burden for behavioral disclosure. It states this is an 'add' operation (implying mutation), but doesn't disclose any behavioral traits: it doesn't mention permissions required, whether this is idempotent, what happens if issues are already in the sprint, error conditions, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant 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, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a simple tool and gets straight to the point. Every word earns its place in conveying the essential action.
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 this is a mutation tool with no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what happens after adding issues, error conditions, permissions needed, or relationship to sibling tools. For a tool that modifies data, more contextual information is needed for safe and effective 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 description coverage is 0%, so the schema provides no parameter documentation. The description doesn't mention any parameters at all - it doesn't explain what 'sprintId' and 'issueIds' represent, their format, or constraints. While the parameter names are self-explanatory to some extent, the description adds zero semantic value beyond what's already inferable from the schema property names.
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 ('add') and target resource ('issues to an existing sprint'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'create_sprint' (which creates new sprints) and 'remove_issues_from_sprint' (which does the opposite operation). However, it doesn't specify what type of 'issues' are being added (e.g., Jira issues, GitHub issues), which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention prerequisites (e.g., that the sprint must already exist), nor does it differentiate from similar tools like 'assign_items_to_iteration' or explain when to use 'add_issues_to_sprint' versus 'create_issue' followed by this tool. The agent must 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 full burden for behavioral disclosure. While 'bulk assign' implies a write/mutation operation, it doesn't specify permissions required, whether the operation is reversible, what happens to previously assigned iterations, or any rate limits. This leaves significant behavioral gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for what it communicates, though what it communicates is limited in scope.
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 4 parameters (0% schema coverage), no annotations, and no output schema, the description is inadequate. It doesn't explain what 'items' are (issues, tasks, etc.), what format IDs should use, what happens on success/failure, or provide any error handling context, leaving the agent poorly equipped to use this tool correctly.
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?
With 0% schema description coverage for all 4 parameters, the description provides no semantic information about what 'projectId', 'itemIds', 'iterationId', or 'fieldName' represent. The description mentions 'items' and 'iteration' which loosely map to two parameters, but doesn't explain their formats, relationships, or why 'fieldName' might be optional when others are required.
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 ('bulk assign') and target ('multiple items to a specific iteration'), providing a specific verb+resource combination. However, it doesn't differentiate from potential sibling tools like 'add_issues_to_sprint' or 'set_field_value' that might handle similar assignment operations, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention prerequisites, constraints, or compare it to sibling tools like 'add_issues_to_sprint' or 'set_field_value' that might handle similar operations, leaving the agent with minimal context for proper tool 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 but only states the action ('create') without details on permissions, side effects, error handling, or response format. It misses critical information like whether this requires admin access, what happens on failure, or if it's idempotent.
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, efficient sentence with no wasted words, making it easy to parse. It's appropriately sized for a basic purpose statement, though it lacks depth due to its 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 the complexity (6 parameters with nested structures, no annotations, no output schema), the description is insufficient. It doesn't explain parameter meanings, behavioral traits, or expected outcomes, making it incomplete for effective tool use in this context.
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 schema provides no parameter details. The description adds no information about the 6 parameters (e.g., what 'triggers' or 'actions' entail, format of 'projectId'), failing to compensate for the coverage gap and leaving parameters largely unexplained.
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 verb ('create') and resource ('automation rule for a GitHub project'), making the purpose evident. However, it doesn't differentiate from sibling tools like 'update_automation_rule' or 'delete_automation_rule', which would require explicit scope or condition distinctions.
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 'update_automation_rule' or 'list_automation_rules'. The description lacks context about prerequisites, typical scenarios, or exclusions, leaving usage ambiguous.
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. While 'Create' implies a write operation, it lacks details on permissions required, rate limits, side effects, or what happens on success/failure. This is inadequate 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, efficient sentence with zero wasted words. It's front-loaded and immediately communicates the core purpose without unnecessary elaboration, 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?
For a tool with 7 parameters, 4 required, no annotations, no output schema, and 0% schema coverage, the description is severely incomplete. It doesn't explain parameter usage, behavioral traits, or output expectations, leaving critical gaps for the agent to operate effectively.
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%, meaning none of the 7 parameters are documented in the schema. The description adds no information about parameters like 'title,' 'description,' or 'milestoneId,' failing to compensate for the schema gap. This leaves the agent guessing about parameter meanings and formats.
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 'Create a new GitHub issue' clearly states the action (create) and resource (GitHub issue), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_draft_issue' or 'create_project_item,' which would require explicit comparison to achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With many sibling tools like 'create_draft_issue' and 'create_project_item' available, there's no indication of prerequisites, differences, or specific contexts for choosing this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Add a comment') which implies a write operation, but doesn't cover permissions needed, rate limits, error conditions, or what happens on success (e.g., comment ID returned). This leaves significant gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information without unnecessary elaboration.
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 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't address behavioral aspects like permissions or response format, leaving the agent with insufficient context to use the tool effectively beyond basic parameter inference.
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 undocumented parameters. It mentions 'a GitHub issue' which hints at 'issueNumber', and 'comment' which relates to 'body', but doesn't explain parameter formats (e.g., issueNumber as integer, body as markdown) or constraints. This adds minimal value beyond the schema's structure.
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 ('Add a comment') and target resource ('to a GitHub issue'), making the purpose immediately understandable. It doesn't differentiate from siblings like 'update_issue_comment' or 'list_issue_comments', but it's specific enough to avoid confusion with unrelated tools.
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 'update_issue_comment' or 'delete_issue_comment', nor does it mention prerequisites such as issue existence or authentication requirements. It's a basic statement of function without contextual usage information.
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 full burden for behavioral disclosure. While 'Create' implies a write/mutation operation, it doesn't specify permissions needed, whether the operation is idempotent, what happens on conflicts, or what the response looks like. This leaves significant gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a basic tool description and front-loads the essential information.
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 4 parameters (3 required), 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter meanings, behavioral implications, or what to expect from the operation, leaving the agent with insufficient information to use the tool effectively.
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?
With 0% schema description coverage for all 4 parameters, the description provides no information about what 'title', 'shortDescription', 'owner', or 'visibility' mean, their formats, constraints, or examples. The description doesn't compensate for the complete lack of parameter documentation in 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 states the action ('Create') and resource ('new GitHub project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_roadmap' or 'create_sprint' that also create GitHub entities, so it doesn't reach the highest clarity level.
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 'create_roadmap' or 'create_sprint', nor does it mention prerequisites or context for creating a project. It simply states what the tool does without usage 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'create' implies a write operation, the description doesn't mention permissions required, whether it's idempotent, rate limits, or what happens on success/failure. It lacks critical context for a mutation tool with no 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, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration.
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 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter usage, behavioral traits, or expected outcomes, leaving significant gaps for an AI agent to invoke it correctly.
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%, meaning none of the 6 parameters are documented in the schema. The description adds no information about parameters beyond what's implied by the tool name (e.g., it mentions 'custom field' but doesn't explain what 'projectId,' 'type,' 'options,' etc., mean or how they should be used).
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 ('create') and resource ('custom field for a GitHub project'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'update_project_field' or 'list_project_fields,' but the verb 'create' distinguishes it from update/list operations.
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. There's no mention of prerequisites (like needing a project ID), when not to use it, or how it differs from related tools like 'update_project_field' or 'list_project_fields' in the sibling list.
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. 'Create' implies a write/mutation operation, but the description doesn't specify permissions required, whether the view is immediately active, error conditions, or what happens on success. This is inadequate 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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in conveying the essential purpose.
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 3 required parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It states what the tool does at a high level but lacks crucial details about behavior, parameters, and outcomes that an agent needs to invoke it correctly.
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 schema provides no parameter documentation. The description mentions no parameters at all, failing to compensate for this gap. It doesn't explain what 'projectId', 'name', or 'layout' represent or how they should be used, leaving all three parameters semantically undefined.
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 ('Create a new view') and the resource ('for a GitHub project'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'create_project' or 'create_roadmap', which also create project-related entities, so it doesn't reach the highest score.
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 'create_project' or 'update_project_view'. It doesn't mention prerequisites (e.g., needing an existing project) or contextual constraints, 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 full burden for behavioral disclosure. It states this is a creation operation but doesn't mention authentication requirements, rate limits, whether it's idempotent, what happens on success/failure, or the response format. This is inadequate 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a basic tool description and front-loads the essential information.
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 5 parameters (3 required), 0% schema description coverage, no annotations, and no output schema, the description is severely incomplete. It doesn't explain parameter meanings, behavioral aspects, or what the tool returns, leaving significant gaps for an AI agent to use it correctly.
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%, meaning none of the 5 parameters have schema descriptions. The tool description provides no information about what 'title', 'body', 'head', 'base', or 'draft' mean, their expected formats, or how they relate to GitHub pull request creation. This leaves critical parameter semantics undocumented.
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 ('create') and resource ('new pull request in a GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_pull_request' or explain how it differs from 'create_pull_request_review' in the same server.
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 'update_pull_request' or 'create_pull_request_review'. It also doesn't mention prerequisites (e.g., needing repository access) or when not to use it (e.g., for existing pull requests).
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 full burden for behavioral disclosure. While 'create' implies a write operation, it doesn't disclose important behavioral traits: whether this requires specific permissions, if reviews are editable/deletable, rate limits, or what happens when multiple reviews are submitted. The description mentions the three event types but doesn't explain their consequences (e.g., APPROVE may merge the PR).
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, efficient sentence that front-loads the core purpose. Every word earns its place - 'create a review' establishes the action, 'on a pull request' specifies the context, and the parenthetical clarifies the three review types. No wasted words or redundant information.
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 4-parameter mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain the review creation process, expected responses, error conditions, or how parameters interact. While concise, it lacks the completeness needed for an agent to understand the full context of this write operation.
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 undocumented parameters. It only mentions the 'event' parameter's three possible values but doesn't explain what 'pullNumber', 'body', or 'comments' represent or how they relate to the review. No guidance on parameter interactions (e.g., when 'comments' array should be used with specific events) is 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 clearly states the action ('create a review') and resource ('on a pull request'), specifying the three possible review types (approve, request changes, or comment). It distinguishes from sibling tools like 'create_issue_comment' or 'update_pull_request' by focusing specifically on pull request reviews. However, it doesn't explicitly differentiate from 'list_pull_request_reviews' beyond the verb difference.
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 doesn't mention prerequisites (e.g., needing access to the pull request), when to choose different event types, or how this differs from other comment/approval mechanisms. No explicit alternatives 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'create' implies a write operation, the description doesn't mention permission requirements, whether this operation is reversible, what happens on success/failure, or any rate limits. For a creation tool with complex nested parameters, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for what it communicates, though it could benefit from additional context 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?
For a creation tool with complex nested parameters (2 parameters with deep nesting), no annotations, and no output schema, the description is inadequate. It doesn't explain the parameter structure, expected behavior, success conditions, or relationship to sibling tools, leaving too many gaps for effective tool 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?
With 0% schema description coverage and 2 complex nested parameters, the description provides no information about what 'project' and 'milestones' should contain. It mentions 'milestones and tasks' but doesn't explain how these map to the actual parameter structure or what the 'issues' field within milestones represents.
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 verb 'create' and the resource 'project roadmap with milestones and tasks', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'generate_roadmap' or 'create_project', which could cause confusion about when to use this specific tool.
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 'generate_roadmap', 'create_project', or 'create_milestone'. There's no mention of prerequisites, context, or exclusions that would help an agent choose between these related 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 provided, the description carries full burden for behavioral disclosure. It states 'Create' which implies a write/mutation operation, but doesn't mention permissions needed, whether sprints can be modified after creation, what happens with invalid dates, or any rate limits. This leaves significant behavioral gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a basic tool description and front-loads the essential information.
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 5 required parameters, 0% schema coverage, and no output schema, the description is insufficient. It doesn't explain what a 'development sprint' entails in this system, what happens after creation, or how to interpret the parameters. The context signals indicate high complexity that the description doesn't address.
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?
With 0% schema description coverage for all 5 required parameters, the description provides no information about what 'title', 'description', 'startDate', 'endDate', or 'issueIds' should contain. The description doesn't compensate for the complete lack of parameter documentation in 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 states the verb ('Create') and resource ('new development sprint'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'plan_sprint' or 'update_sprint', which reduces clarity about when to choose this specific tool.
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 like 'plan_sprint' or 'update_sprint'. The description only states what it does without context about prerequisites, timing, or relationship to other sprint-related operations.
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 states the tool 'create[s]' something, implying a write/mutation operation, but doesn't specify whether this requires specific permissions, what format the output takes (e.g., a file, report, or database entry), or any side effects like overwriting existing data. For a complex creation tool with 8 parameters and no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Create a comprehensive requirements traceability matrix') and elaborates on its scope. There's no wasted text, though it could benefit from slight structuring (e.g., breaking into clauses) for even clearer readability. Overall, it's appropriately sized for 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?
Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It outlines the tool's purpose but lacks crucial details: no explanation of parameter semantics, no behavioral context (e.g., output format, error handling), and no usage guidelines. This leaves the agent poorly equipped to invoke the tool correctly, especially with 100% required parameters and nested objects in arrays.
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 none of the 8 parameters are documented in the schema. The description mentions 'PRD business requirements', 'features', 'use cases', and 'tasks', which loosely map to parameters like 'prdContent', 'features', and 'tasks', but it doesn't explain their formats, purposes, or how they interrelate. It omits parameters like 'projectId', 'includeUseCases', and others entirely, failing to compensate for the schema's lack of 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 clearly states the tool's purpose with specific verbs ('create') and resources ('requirements traceability matrix'), detailing what it links (PRD business requirements → features → use cases → tasks) and specifying 'full bidirectional traceability'. It distinguishes itself from sibling tools like 'create_roadmap' or 'generate_prd' by focusing on traceability mapping rather than general project creation or documentation generation.
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. While it implies usage for traceability mapping, it doesn't mention prerequisites (e.g., needing existing PRD content), exclusions, or comparisons to similar tools like 'create_roadmap' or 'enhance_prd' that might handle related project documentation tasks. This leaves the agent without clear contextual boundaries.
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 states the destructive action ('Delete') but doesn't mention critical details like whether this operation is reversible, what permissions are required, potential side effects, or error conditions. This leaves significant gaps for safe tool invocation.
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 with zero wasted words. It's appropriately sized for a simple operation and front-loads the essential information (action + resource). Every word 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?
For a destructive operation with no annotations, no output schema, and undocumented parameters, the description is incomplete. It doesn't address behavioral risks, parameter meaning, or expected outcomes. Given the complexity of a delete operation in a GitHub context, more contextual information 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 input schema has 0% description coverage, and the tool description provides no information about the 'draftIssueId' parameter. It doesn't explain what a draft issue ID is, where to find it, or its expected format. The description fails to compensate for the complete lack of schema 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 states the action ('Delete') and resource ('a draft issue from a GitHub project'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'delete_issue' or 'delete_project_item', which reduces clarity about its unique 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. There's no mention of prerequisites (e.g., needing a draft issue ID), exclusions (e.g., cannot delete published issues), or comparisons to sibling tools like 'delete_issue' or 'remove_project_item'.
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 states the tool performs a deletion but doesn't mention whether this action is reversible, requires specific permissions, has side effects (e.g., affecting associated issues), or provides confirmation feedback. For a destructive operation with zero annotation coverage, this is a significant 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, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loaded with the essential action and resource.
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's destructive nature, lack of annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't address critical aspects like behavioral consequences, parameter details, or expected outcomes, leaving significant gaps for an AI agent to understand and use the tool safely.
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 description coverage is 0%, meaning the single parameter 'milestoneId' is undocumented in the schema. The description adds no information about this parameter—what format it expects, where to obtain it, or examples. With low coverage and no compensation in the description, this falls below the baseline.
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 ('Delete') and the resource ('a GitHub milestone'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from other deletion tools like 'delete_automation_rule' or 'delete_project' beyond the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'update_milestone' or 'archive_project_item', nor does it mention prerequisites (e.g., needing milestone ID from 'list_milestones' or 'get_milestone_metrics'). It simply states what the tool does without contextual usage information.
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. While 'Delete' implies a destructive mutation, it doesn't specify whether this is permanent, reversible, requires specific permissions, or has side effects (e.g., deleting associated items). The description is minimal and lacks critical behavioral context for a destructive operation.
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 with just three words, front-loading the essential action and resource. There's no wasted language, making it efficient for quick comprehension.
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 mutation tool with no annotations, 0% schema coverage, and no output schema, the description is inadequate. It fails to address critical aspects like permissions, irreversibility, error conditions, or what happens to dependent resources, leaving significant gaps for safe and correct usage.
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 0% description coverage, so the single parameter 'projectId' is undocumented in the schema. The description adds no information about what 'projectId' represents, its format, or where to find it. This leaves the parameter's meaning ambiguous despite the low parameter count.
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 verb ('Delete') and resource ('a GitHub project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'archive_project_item' or 'delete_milestone', which are also deletion operations on related resources.
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. There's no mention of prerequisites (e.g., needing admin permissions), consequences (e.g., permanent deletion), or when to choose other deletion tools like 'delete_milestone' or 'archive_project_item'.
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 full burden but lacks behavioral details. It states the action ('Delete') which implies a destructive operation, but doesn't specify if deletion is permanent, requires specific permissions, has confirmation steps, or what happens on success/failure. This leaves critical behavioral aspects unclear 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's appropriately sized for a simple operation and front-loads the essential action and resource, 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?
For a destructive mutation tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It lacks behavioral context, parameter details, usage guidance, and expected outcomes, leaving too many gaps for effective tool 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%, so the description must compensate but adds no parameter information. It doesn't explain what 'projectId' and 'viewId' represent, their format (e.g., numeric IDs, names), or how to obtain them (e.g., from 'list_project_views'). This leaves both parameters semantically undefined.
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 ('Delete') and resource ('a view from a GitHub project'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'delete_project' or 'delete_automation_rule', but the specificity of 'view' provides adequate differentiation for a basic understanding.
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 doesn't mention prerequisites (e.g., needing an existing view), exclusions, or related tools like 'list_project_views' for selection or 'update_project_view' for modification instead of deletion.
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 full burden for behavioral disclosure. It states the tool 'automatically adds' metadata, implying a write/mutation operation, but doesn't clarify permissions required, whether changes are reversible, rate limits, or what happens if enrichment fails. For a tool with 7 parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two brief sentences that efficiently state the core functionality. Every word earns its place with no redundancy or fluff. It's front-loaded with the main purpose ('AI-powered issue enrichment') followed by specific actions.
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 complexity (7 parameters, no annotations, no output schema), the description is incomplete. It explains what the tool does at a high level but lacks crucial details: parameter meanings, behavioral traits (e.g., mutation impact), output format, or error handling. For a tool that likely modifies issues, this leaves too many unknowns for reliable agent 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 description coverage is 0%, so the schema provides no parameter documentation. The description doesn't mention any parameters, leaving all 7 (including 4 required) unexplained. It fails to compensate for the coverage gap, not even hinting at what 'projectId', 'issueId', etc., represent or how 'autoApply' affects behavior.
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's purpose: 'AI-powered issue enrichment' with specific actions like 'adds labels, priority, type, complexity, and effort estimates.' It distinguishes from siblings like 'triage_issue' or 'analyze_task_complexity' by focusing on automated enrichment rather than manual triage or standalone analysis. However, it doesn't explicitly differentiate from 'enrich_issues_bulk' regarding batch vs. single issue processing.
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. It doesn't mention prerequisites (e.g., needing an existing issue), compare to 'enrich_issues_bulk' for multiple issues, or specify when automated enrichment is appropriate versus manual updates. The description implies usage for AI-driven metadata addition but lacks explicit 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 provided, so the description carries the full burden of behavioral disclosure. It mentions 'using AI analysis and industry best practices,' which hints at generative behavior and external data usage, but doesn't specify details like output format, potential rate limits, authentication needs, or whether the generation is deterministic. For a tool with 9 parameters and no annotations, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and includes key details like 'comprehensive,' 'AI analysis,' and 'industry best practices,' making it easy to parse. Every part of the sentence 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?
Given the complexity (9 parameters, 5 required, no output schema, and no annotations), the description is incomplete. It doesn't explain parameters, output format, or behavioral traits, leaving the agent with insufficient information to use the tool effectively. The lack of annotations and output schema increases the burden on the description, which it doesn't meet.
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%, meaning none of the 9 parameters have descriptions in the schema. The tool description does not mention any parameters, failing to add meaning beyond the schema. Parameters like 'projectIdea', 'targetUsers', and 'includeResearch' are left unexplained, making it hard for an agent to understand what inputs are expected. This is inadequate given the low schema coverage.
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's purpose: 'Generate a comprehensive Product Requirements Document (PRD) from a project idea using AI analysis and industry best practices.' It specifies the verb ('Generate'), resource ('Product Requirements Document'), and method ('using AI analysis and industry best practices'), which is specific and actionable. However, it doesn't explicitly distinguish from sibling tools like 'enhance_prd' or 'parse_prd', which might handle similar PRD-related tasks, so it's not a perfect 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'enhance_prd' (which might modify an existing PRD) or 'parse_prd' (which might analyze a PRD), nor does it specify prerequisites or contexts for usage. The agent must infer usage from the purpose alone, which is insufficient for optimal tool 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'AI-powered' and 'automatically', hinting at automation, but lacks critical details: whether this is a read-only or mutating operation (likely mutating given 'creates'), permission requirements, rate limits, side effects (e.g., if it modifies existing data), or output format. For a tool with 6 parameters and no annotations, this is a significant 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 extremely concise—two short sentences with zero wasted words. It's front-loaded with the core purpose ('AI-powered roadmap generation from project issues') and adds a clarifying detail. Every sentence earns its place by conveying essential information efficiently.
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's complexity (6 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral context (e.g., mutation effects), parameter explanations, and output details. While conciseness is high, the description doesn't provide enough information for an agent to confidently invoke this tool without guessing at semantics or side effects.
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 schema provides no parameter details. The description adds minimal value: it implies parameters relate to 'project issues' and outputs like 'milestones, sprints, and phases', but doesn't explain any of the 6 parameters (e.g., what 'autoCreate' does or how 'sprintDurationWeeks' is used). With low coverage, the description fails to compensate, leaving parameters largely undocumented.
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's purpose: 'AI-powered roadmap generation from project issues. Creates milestones, sprints, and phases automatically.' It specifies the verb ('generation'), resource ('roadmap'), and source ('project issues'), and distinguishes it from siblings like 'create_roadmap' by emphasizing AI automation. However, it doesn't explicitly contrast with all similar tools like 'plan_sprint' or 'create_milestone', keeping it at 4 rather than 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., existing project issues), exclusions, or compare it to siblings like 'create_roadmap' or 'plan_sprint'. The agent must infer usage from the purpose alone, which is insufficient for optimal tool 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 full burden but only states what the tool does without behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are required, error handling, or response format, leaving significant gaps for a tool that likely accesses sensitive automation data.
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, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
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 with no annotations, 0% schema coverage, and no output schema, the description is insufficient. It doesn't explain what 'details' include, how to handle errors, or provide context about automation rules in this system, making it inadequate for safe and effective use by an AI agent.
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% with one required parameter 'ruleId'. The description mentions 'a specific automation rule' which implies the parameter identifies the rule, but doesn't explain what a ruleId is, its format, or where to obtain it, failing to compensate for the schema's lack of 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 states the verb ('Get details') and resource ('of a specific automation rule'), making the purpose understandable. It distinguishes from sibling 'list_automation_rules' by specifying retrieval of a single rule rather than listing multiple, though this distinction could be more 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 on when to use this tool versus alternatives like 'list_automation_rules' or 'get_issue' for related data. The description implies usage when details of a specific rule are needed, but lacks explicit context or prerequisites.
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 burden. It mentions the tool gets data based on today's date, but doesn't disclose behavioral traits such as whether it's read-only, what permissions are needed, how it handles missing data, or the return format. This leaves significant gaps for a tool with parameters.
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, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence earns its place by specifying the action, resource, and key constraint (today's date).
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 complexity (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral context, and output expectations, making it insufficient for an agent to reliably invoke the tool without additional assumptions.
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 undocumented parameters. It adds no meaning about the two parameters (projectId and fieldName), failing to explain what they represent, their expected values, or how they affect the output. This is inadequate given the coverage gap.
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 ('currently active iteration'), specifying it's based on today's date. It distinguishes from siblings like 'get_iteration_by_date' by focusing on the current iteration rather than a specific date, but doesn't explicitly mention this 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 on when to use this tool versus alternatives like 'get_iteration_by_date' or 'get_current_sprint' is provided. The description implies usage for retrieving the current iteration but offers no context about prerequisites, 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Get details') but doesn't describe what 'details' includes, whether it's a read-only operation, if it requires authentication, or any rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly. No extraneous information is included, which is appropriate for a 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?
Given the lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain the return values, error conditions, or behavioral traits needed for a read operation. For a tool with one parameter and no structured documentation, more context is required to be fully useful.
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 0% description coverage, with one undocumented parameter 'issueId'. The description doesn't add any meaning beyond the schema—it doesn't explain what 'issueId' represents, its format (e.g., numeric ID, URL), or where to find it. This fails to compensate for the low schema coverage.
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 verb ('Get') and resource ('details of a specific GitHub issue'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_issues' or 'enrich_issue', which would require more specificity about what 'details' includes or how this differs from bulk operations.
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 doesn't mention siblings like 'list_issues' for multiple issues or 'enrich_issue' for enhanced details, nor does it specify prerequisites such as needing an existing issue ID. This leaves the agent without context for tool 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool finds iterations by date but doesn't explain what 'iteration' means in this context, whether it's read-only or has side effects, error handling, or return format. This is a significant gap for a tool with no 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what an 'iteration' is, how parameters interact, or what the output looks like, leaving the agent with insufficient context to use the tool effectively.
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%, meaning none of the three parameters (projectId, date, fieldName) are documented in the schema. The description mentions 'date' but doesn't explain its format or purpose, and it omits 'projectId' and 'fieldName' entirely. It adds minimal value beyond the schema, failing to compensate for the coverage gap.
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 'Find which iteration contains a specific date' clearly states the tool's purpose with a specific verb ('Find') and resource ('iteration'), and it distinguishes the tool by focusing on date-based iteration lookup. However, it doesn't explicitly differentiate from sibling tools like 'get_current_iteration' or 'get_iteration_items', which might have overlapping functionality.
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 doesn't mention prerequisites, context (e.g., project management scenarios), or comparisons to sibling tools like 'get_current_iteration' or 'get_iteration_configuration', 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 full burden for behavioral disclosure. It states this is a 'Get' operation (implying read-only), but doesn't mention permissions, rate limits, error conditions, or what happens if the project/field doesn't exist. For a tool with 2 parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word contributes to understanding what the tool does. There's no redundancy or unnecessary elaboration.
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 with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain parameter meanings, return format, error handling, or behavioral constraints. While concise, it doesn't provide enough context for reliable tool invocation given the lack of structured documentation.
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 schema provides no parameter documentation. The description mentions 'iteration field configuration' but doesn't explain what 'projectId' or 'fieldName' parameters represent, their formats, or examples. While it hints at what data is returned, it adds minimal value beyond the parameter names themselves.
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 ('iteration field configuration') with specific attributes ('duration, start date, and list of all iterations'). It distinguishes from siblings like 'get_current_iteration' or 'get_iteration_by_date' by focusing on configuration rather than current/date-specific data. However, it doesn't explicitly contrast with these siblings in the text.
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_current_iteration' or 'get_iteration_by_date'. The description implies it retrieves configuration data, but doesn't specify use cases, prerequisites, or exclusions. The agent must infer usage from the tool name and description 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 full burden. It states a read operation ('Get') but lacks details on permissions, rate limits, pagination (despite a 'limit' parameter), return format, or error handling. For a tool with 3 parameters and no annotation coverage, this is insufficient behavioral disclosure.
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 zero waste. It efficiently conveys the core purpose without unnecessary elaboration, making it appropriately concise for a basic retrieval 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 3 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on parameter semantics, behavioral traits, and return values, leaving significant gaps for an AI agent to understand and invoke the tool correctly.
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 mentions 'specific iteration' which hints at 'iterationId', but doesn't explain 'projectId', 'limit', or their relationships. The description adds minimal value beyond the bare schema, failing to clarify parameter meanings or usage.
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 verb ('Get') and resource ('all items assigned to a specific iteration'), making the purpose understandable. It doesn't explicitly distinguish from siblings like 'get_current_iteration' or 'list_project_items', but the focus on iteration-specific items is reasonably specific.
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 'list_project_items' or 'get_current_iteration'. The description implies usage for iteration-specific retrieval but doesn't specify prerequisites, exclusions, or comparative contexts 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?
No annotations are provided, so the description carries the full burden. It states 'Get progress metrics' which implies a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error conditions, or what 'progress metrics' entails (e.g., completion percentage, issue counts). For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—'Get progress metrics for a specific milestone' is front-loaded and directly conveys the core action. It's appropriately sized for a simple tool, though conciseness alone doesn't make up for lack of detail.
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 complexity (a read operation with 2 required parameters), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't explain what 'progress metrics' returns (e.g., numerical data, structured object), how to interpret results, or handle errors. For a tool that likely outputs meaningful data, this leaves the agent guessing about the response format and usage context.
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%, meaning parameters 'milestoneId' and 'includeIssues' are undocumented in the schema. The description adds no meaning beyond the parameter names—it doesn't explain what 'milestoneId' should be (e.g., format, source), what 'includeIssues' does (e.g., adds issue details to metrics), or any constraints. With low coverage, the description fails to compensate, leaving parameters unclear.
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 verb 'Get' and the resource 'progress metrics for a specific milestone', making the purpose understandable. It distinguishes from siblings like 'get_milestones' (list) or 'get_sprint_metrics' (different scope), but doesn't explicitly differentiate from 'get_overdue_milestones' or 'get_upcoming_milestones', which might also involve metrics. The specificity is good but not perfect for sibling differentiation.
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 doesn't mention prerequisites (e.g., needing a valid milestone ID), exclusions, or comparisons to other tools like 'get_sprint_metrics' or general metric tools. Usage is implied by the name and purpose, but explicit context is missing.
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 full burden for behavioral disclosure. It states it 'gets details' but doesn't clarify if this is a read-only operation, what permissions are required, whether it returns structured data or raw text, or if there are rate limits. For a tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
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, efficient sentence with zero wasted words. It's front-loaded with the core purpose ('Get details'), making it easy to parse. Every part of the sentence contributes directly to understanding the tool's function.
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, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't address key contextual aspects like what 'details' include, error conditions (e.g., invalid projectId), or the return format. For a tool that likely returns structured project data, this leaves significant gaps for an AI agent.
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 the undocumented parameter 'projectId'. The description mentions 'a specific GitHub project' but doesn't explain what a projectId is, its format (e.g., numeric ID, string), or where to obtain it. This adds minimal semantic value beyond the schema's basic type information.
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 verb ('Get') and resource ('details of a specific GitHub project'), making the purpose unambiguous. It distinguishes this from siblings like 'list_projects' (which lists multiple projects) and 'create_project' (which creates new projects). However, it doesn't specify what 'details' include, leaving some ambiguity about the scope of information returned.
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 doesn't mention prerequisites (e.g., needing a project ID), contrast with 'list_projects' for browsing projects, or specify scenarios where this is appropriate (e.g., after identifying a project from a list). The agent must infer usage from the name and context 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 full burden of behavioral disclosure. It states the tool 'Get details', implying a read-only operation, but doesn't specify whether it requires authentication, rate limits, error conditions, or what details are returned. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with a single, clear sentence: 'Get details of a specific pull request'. There is zero waste, and every word contributes to the core purpose without unnecessary elaboration.
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 complexity (a read operation with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't cover parameter semantics, behavioral traits like authentication needs, or return values. For a tool in this context, it should provide more guidance to be fully helpful.
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 description adds no meaning beyond the input schema. Schema description coverage is 0%, with one parameter 'pullNumber' undocumented. The description doesn't explain what 'pullNumber' is (e.g., an integer identifier), its format, or where to find it. It fails to compensate for the low schema coverage.
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's purpose: 'Get details of a specific pull request'. It uses a specific verb ('Get') and resource ('pull request'), and the qualifier 'specific' implies it retrieves one item by identifier. However, it doesn't explicitly differentiate from sibling tools like 'list_pull_requests' or 'update_pull_request', which would require 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. The description doesn't mention sibling tools like 'list_pull_requests' for multiple pull requests or 'update_pull_request' for modifications. It also lacks context on prerequisites, such as needing an existing pull request number.
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. 'Get progress metrics' implies a read-only operation, but it doesn't disclose behavioral traits such as required permissions, rate limits, what 'progress metrics' includes (e.g., burndown charts, velocity), or whether it's a safe, non-destructive query. This leaves significant gaps for an agent to understand 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a metrics tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'progress metrics' entails, how results are structured, or any prerequisites, leaving the agent with insufficient context to use the tool effectively.
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%, meaning the input schema provides no descriptions for 'sprintId' or 'includeIssues'. The description adds no parameter semantics beyond implying a 'specific sprint' for 'sprintId'. It doesn't explain what 'includeIssues' does (e.g., whether it adds issue details to metrics) or provide format details, failing to compensate for the low coverage.
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 progress metrics for a specific sprint' clearly states the verb ('Get') and resource ('progress metrics for a specific sprint'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_current_sprint' or 'get_milestone_metrics', which might provide related but different information, so it doesn't reach the highest score.
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. With siblings like 'get_current_sprint' and 'get_milestone_metrics', there's no indication of whether this tool is for historical sprints, real-time metrics, or specific types of progress data, leaving usage ambiguous.
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 states it 'gets a list' (implying read-only) but doesn't mention permissions, rate limits, pagination, or what the output looks like. For a tool with three parameters and no output schema, this leaves significant gaps in understanding its behavior.
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, efficient sentence with no wasted words. It's front-loaded with the core purpose and avoids unnecessary elaboration, 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?
For a tool with three required parameters, no annotations, and no output schema, the description is insufficient. It lacks details on parameter usage, behavioral constraints, and output format, leaving the agent with incomplete context to use the tool effectively.
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 description coverage is 0%, so the description must compensate for all three parameters. It only vaguely references 'within a time frame' (hinting at 'daysAhead') but doesn't explain 'limit' or 'includeIssues'. This fails to add meaningful semantics beyond the bare schema, leaving parameters largely undocumented.
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 a list') and resource ('upcoming milestones') with a scope ('within a time frame'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_milestone_metrics' or 'list_milestones', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'list_milestones' or 'get_overdue_milestones'. It lacks context about prerequisites, timing, 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 full burden but only states the basic action without behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are needed, how results are returned (pagination, format), or any rate limits. The description doesn't contradict annotations (none exist), but provides minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core purpose immediately.
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 with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what 'automation rules' are in this context, what information is returned, or how to interpret results. While concise, it lacks necessary context for effective tool selection and 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 description coverage is 0%, so the description must compensate but adds no parameter information. It mentions 'for a GitHub project' which hints at the 'projectId' parameter's purpose, but doesn't explain what format the ID should be, where to find it, or any constraints. With 1 undocumented parameter, the description provides insufficient semantic value.
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 ('List all automation rules') and the target resource ('for a GitHub project'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_automation_rule' (singular) or explain what distinguishes listing from getting individual rules.
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 like 'get_automation_rule' or 'create_automation_rule'. The description mentions 'for a GitHub project' but doesn't specify prerequisites, context, or exclusions for usage.
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 full burden for behavioral disclosure. While 'List all comments' implies a read-only operation, it doesn't disclose important behavioral aspects like pagination behavior (implied by the 'perPage' parameter), authentication requirements, rate limits, error conditions, or what 'all' means in practice (e.g., chronological order, filtering capabilities).
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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple listing operation and gets straight to the point with zero waste.
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 with 2 parameters (one required), no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain parameter usage, return format, pagination, error handling, or how it differs from related tools. The agent would struggle to use this effectively without additional context.
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?
With 0% schema description coverage for both parameters, the description provides no semantic information about 'issueNumber' (what format? repository context?) or 'perPage' (what values are valid? default behavior?). The description mentions 'all comments' which implies the tool returns comments, but doesn't explain how parameters affect this behavior.
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's purpose with a specific verb ('List') and resource ('comments on a GitHub issue'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_issue' or 'list_issues' which might also provide comment information, so it doesn't reach the highest score.
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. With sibling tools like 'get_issue' (which might include comments) and 'create_issue_comment' (for adding comments), there's no indication of when this specific listing tool is preferred or what its scope limitations might be.
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. 'List all GitHub labels' implies a read-only operation, but it doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or what 'all' entails (e.g., across all repos or a specific one). This leaves key operational details unclear 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, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly without unnecessary elaboration.
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, no output schema, and low parameter coverage, the description is incomplete. It doesn't address key contextual aspects like return format, error handling, or usage constraints, leaving the agent with insufficient information to invoke the tool effectively.
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 ('limit') with 0% description coverage, meaning its purpose is undocumented. The tool description adds no parameter semantics beyond the schema, failing to explain what 'limit' does or how it affects the listing. This is inadequate given the low schema coverage.
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 'List all GitHub labels' clearly states the verb ('List') and resource ('GitHub labels') with the scope 'all'. It's specific about what the tool does, though it doesn't explicitly distinguish itself from potential sibling tools like 'list_issues' or 'list_milestones' beyond the 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as whether it applies to a specific repository or requires authentication. With many sibling tools available, this lack of differentiation is a significant gap.
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 states the action ('List all items') but doesn't clarify if this is a read-only operation, how pagination works (implied by the 'limit' parameter but not explained), what the output format is, or any rate limits. This leaves significant gaps in understanding the tool's behavior.
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 efficiently conveys the core purpose without unnecessary words. It's front-loaded with the essential action and resource, making it easy to parse. There's no wasted verbiage or redundancy.
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 complexity (a list operation with 2 parameters, no annotations, and no output schema), the description is insufficient. It doesn't explain what 'items' encompass, how results are structured, or handle edge cases like empty projects. For a tool in a rich ecosystem like GitHub with many sibling tools, more context is needed to ensure proper 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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'projectId' implicitly by referring to 'a GitHub project' but doesn't explain what format it expects (e.g., numeric ID, URL). It doesn't address the 'limit' parameter at all, leaving its purpose and usage unclear. The description adds minimal value 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 states the verb ('List') and resource ('items in a GitHub project'), making the purpose immediately understandable. It distinguishes itself from siblings like 'get_project' or 'list_projects' by focusing on items within a project. However, it doesn't specify what types of items (e.g., issues, pull requests) are included, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention sibling tools like 'list_issues' or 'get_iteration_items' that might overlap in functionality, nor does it specify prerequisites such as needing a valid project ID. This lack of contextual guidance leaves the agent to infer usage scenarios.
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 states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like pagination, rate limits, authentication needs, or what 'views' entails (e.g., types, formats). This is a significant gap for a 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, efficient sentence with no wasted words. It's appropriately sized for a simple list tool and front-loaded with the core action, though its brevity contributes to gaps 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?
Given the lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't address behavioral traits, parameter details, or return values, leaving the agent with insufficient context for a tool that likely interacts with a complex system like GitHub projects.
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 0% description coverage, with one required parameter 'projectId' undocumented. The description adds no meaning beyond implying a project context, failing to explain what 'projectId' is (e.g., numeric ID, URL) or where to find it. This doesn't compensate for the schema's lack of 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 states the verb ('List') and resource ('views in a GitHub project'), making the purpose unambiguous. However, it doesn't differentiate from siblings like 'list_project_items' or 'list_projects' beyond specifying 'views', which is somewhat helpful but not fully distinctive.
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 doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the name alone among many sibling list 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 provided, the description carries full burden for behavioral disclosure. While 'List all reviews' implies a read-only operation, it doesn't specify permissions required, pagination behavior, rate limits, or what format the reviews are returned in. The description provides minimal behavioral context beyond the basic operation.
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, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a simple list operation and front-loads the essential information.
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 with no annotations, no output schema, and 0% parameter documentation, the description is insufficiently complete. It doesn't address key contextual questions about permissions, return format, pagination, or error conditions that an agent would need to use this tool effectively.
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?
With 0% schema description coverage for the single parameter 'pullNumber', the description provides no additional parameter information. It doesn't explain what 'pullNumber' represents, where to find it, or any constraints on valid values. The description fails to compensate for the complete lack of schema 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 states the action ('List all reviews') and target resource ('on a pull request'), providing a specific verb+resource combination. However, it doesn't differentiate from potential sibling tools like 'get_pull_request' or 'list_pull_requests' that might also provide review 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?
The description provides no guidance on when to use this tool versus alternatives. There are no explicit when/when-not instructions, no mention of prerequisites, and no comparison to sibling tools like 'get_pull_request' that might also provide review data.
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 burden but provides minimal behavioral insight. It mentions the merge methods but doesn't disclose critical traits like required permissions, whether it's destructive (merging typically is), rate limits, or what happens on failure. This is inadequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and methods, making it easy to scan, though its brevity contributes to gaps 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 mutation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and expected outcomes, failing to provide sufficient context for safe and effective 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 description coverage is 0%, so the description must compensate but adds no parameter details. It doesn't explain what 'pullNumber' refers to, the purpose of 'commitTitle'/'commitMessage', or valid values for 'mergeMethod'. This leaves all 4 parameters poorly understood.
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 ('merge') and resource ('a pull request'), specifying the available methods (merge, squash, or rebase). It distinguishes from siblings like 'create_pull_request' or 'update_pull_request' by focusing on the merging operation, though it doesn't explicitly contrast with them.
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. It doesn't mention prerequisites (e.g., pull request must be in a mergable state), exclusions, or related tools like 'update_pull_request' for non-merging updates, leaving usage context unclear.
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 full burden for behavioral disclosure. It states 'Plan a new sprint' which implies a creation/mutation operation, but doesn't specify permissions required, whether it's idempotent, what happens on failure, or any rate limits. The mention of 'selected issues' hints at issue association, but lacks detail on how this differs from other issue-sprint tools.
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, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for the tool's apparent complexity and is perfectly 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 mutation tool with 2 parameters (one complex nested object), 0% schema coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain the sprint creation process, issue association mechanics, error conditions, or what the tool returns. The context signals indicate significant complexity that the description doesn't address.
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 undocumented parameters. It mentions 'selected issues' which maps to the 'issueIds' parameter, but doesn't explain the 'sprint' object or its nested properties (title, dates, goals). No format details, constraints, or examples are provided for any 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 action ('Plan') and resource ('a new sprint with selected issues'), making the purpose understandable. It distinguishes from siblings like 'create_sprint' by implying issue selection, but doesn't explicitly differentiate from other sprint-related tools like 'update_sprint' or 'get_sprint_metrics'.
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 'create_sprint' or 'add_issues_to_sprint'. The description implies usage for planning new sprints with issues, but offers no explicit 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Remove' implies a destructive mutation, but the description doesn't specify whether this is permanent deletion, reversible removal, what permissions are required, or what happens to the item after removal. Significant behavioral details are missing 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and gets straight to the point without unnecessary elaboration.
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 mutation tool with no annotations, 0% schema coverage, and no output schema, the description is inadequate. It doesn't explain the operation's consequences, required permissions, error conditions, or what happens to the removed item. The description should provide more context given the tool's complexity and lack of structured documentation.
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 schema provides no parameter documentation. The description mentions 'an item from a GitHub project' which hints at the itemId parameter, but doesn't explain what projectId or itemId represent, their formats, or where to find them. The description adds minimal semantic value beyond what's obvious from the parameter names.
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 ('Remove') and target ('an item from a GitHub project'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'archive_project_item' or 'unarchive_project_item', which might have similar removal functions but different behaviors.
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 'archive_project_item', 'delete_project', or other removal-related siblings. It lacks context about prerequisites, consequences, or appropriate scenarios for this specific removal operation.
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 full burden for behavioral disclosure. It states this schedules automated triaging to run periodically, implying a configuration/mutation action, but doesn't describe permissions needed, whether it's idempotent, what happens if conflicts arise, or any rate limits. For a tool that likely modifies system behavior, this is insufficient.
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, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for the tool's apparent complexity and front-loads the core action.
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, 0% schema coverage, no output schema, and 3 required parameters for what appears to be a configuration/mutation tool, the description is incomplete. It lacks details on behavior, parameters, outputs, and differentiation from siblings, making it inadequate for an agent to use correctly without guessing.
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 parameters are undocumented in the schema. The description adds no information about what 'projectId', 'schedule', or 'autoApply' mean, their formats, or how they affect the scheduling. It doesn't compensate for the schema gap, leaving all 3 parameters semantically unclear.
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 ('schedule automated issue triaging') and the resource ('issue triaging'), making the purpose understandable. However, it doesn't specifically differentiate from sibling tools like 'triage_all_issues' or 'triage_issue' which might be manual or one-time operations versus this scheduled automation.
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 'triage_all_issues' or 'create_automation_rule'. It mentions 'run periodically' but doesn't specify prerequisites, exclusions, or contextual triggers for choosing this tool over others in the sibling list.
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 mentions 'automatically triage,' implying a batch operation, but doesn't explain what 'triage' entails (e.g., labeling, assigning, prioritizing), whether it's destructive or safe, what permissions are required, or how errors are handled. For a tool with 4 parameters and no annotations, this leaves significant gaps in understanding its behavior.
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, efficient sentence that front-loads the core purpose. There's no wasted language or redundancy, making it easy to parse quickly. It appropriately sized for conveying the basic function without unnecessary elaboration.
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's complexity (4 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'triage' means operationally, how parameters interact, what the output looks like, or potential side effects. For a batch automation tool with multiple inputs, more context is needed to use it effectively.
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 schema provides no parameter details. The description mentions 'project' and 'untriaged issues,' which loosely relates to 'projectId' and 'onlyUntriaged,' but doesn't explain the purpose or format of any parameters (e.g., what 'autoApply' or 'projectContext' do). It fails to compensate for the lack of schema documentation, leaving most parameters unexplained.
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's purpose: 'Automatically triage all untriaged issues in a project.' It specifies the verb ('triage'), resource ('issues'), and scope ('all untriaged in a project'). However, it doesn't explicitly differentiate from sibling tools like 'triage_issue' (singular) or 'schedule_triaging', leaving some ambiguity about when to use each.
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 doesn't mention sibling tools like 'triage_issue' (for individual issues) or 'schedule_triaging', nor does it specify prerequisites, exclusions, or appropriate contexts. Users must infer usage from the name and description 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 behavioral disclosure. It mentions 'AI-powered' and the actions performed, but lacks critical details like whether this is a read-only analysis or applies changes, what 'autoApply' does, permissions required, or output format. This is inadequate for a tool with 7 parameters.
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—a single sentence with no wasted words. It's front-loaded with the core purpose and efficiently lists the three key actions. Every word 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?
Given the complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the tool returns, how 'autoApply' affects behavior, or the relationship between issue identifiers. For an AI-powered tool with multiple inputs, more context 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?
Schema description coverage is 0%, so the description must compensate for all 7 parameters. It provides no information about what parameters mean, their relationships, or which are essential for triaging. The description fails to add any semantic value beyond the bare 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 states the tool's purpose with specific verbs ('classifies', 'assigns', 'recommends') and resource ('issues'), making it evident this is an AI-powered triaging function. However, it doesn't explicitly differentiate from sibling tools like 'triage_all_issues' or 'enrich_issue', which appear related.
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. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone among many 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 provided, the description carries full burden for behavioral disclosure. It mentions the action ('Unarchive') and outcome ('Brings back'), but lacks critical details: whether this requires specific permissions, if it's reversible, what happens to the item's previous state, or any rate limits/errors. For a mutation tool with zero annotation coverage, this is insufficient.
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 with two short sentences that directly address the tool's purpose. Every word earns its place, with no redundant or vague phrasing. It's front-loaded with the core action and efficiently adds clarifying context.
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 this is a mutation tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover parameter details, behavioral traits like permissions or side effects, or expected outcomes. For a tool that modifies project state, this leaves significant gaps 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.
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 both parameters. It mentions 'project' and 'item' but doesn't explain what 'projectId' and 'itemId' represent, their expected formats (e.g., numeric IDs, URLs), or where to find them. This leaves the agent guessing about parameter semantics beyond basic naming.
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 ('Unarchive') and target ('an item in a GitHub project'), with the phrase 'Brings back a previously archived item' providing additional context about reversing an archival state. It distinguishes from 'archive_project_item' by specifying the opposite operation, though it doesn't explicitly contrast with other potential alternatives.
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, prerequisites, or constraints. While it implies usage for reversing archival, it doesn't specify conditions like permissions needed, whether the item must be archived first, or how it differs from similar operations like 'add_project_item' or 'update_project_item'.
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. While 'Update' implies a mutation operation, the description lacks details on permissions required, whether changes are reversible, error handling, or response format. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent 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?
Given the tool's complexity (a mutation operation with 4 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is insufficient. It does not compensate for the missing structured data, leaving critical gaps in understanding how to invoke the tool and what to expect in return.
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%, meaning none of the parameters are documented in the schema. The description does not add any semantic information about the parameters—it does not explain what 'draftIssueId', 'title', 'body', or 'assigneeIds' represent, their formats, or constraints. This leaves the agent with minimal guidance on how to use the tool effectively.
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 ('Update') and resource ('an existing draft issue in a GitHub project'), making the purpose immediately understandable. However, it does not differentiate this tool from sibling tools like 'update_issue' or 'update_project_item', which would require more specific context about what distinguishes a draft issue from other issue types.
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. With sibling tools like 'update_issue', 'create_draft_issue', and 'delete_draft_issue', there is no indication of prerequisites, constraints, or scenarios where this tool is preferred over others, 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 full burden but only states the basic action without disclosing behavioral traits like required permissions, whether the update is reversible, rate limits, or response format. It lacks details crucial for safe and effective use in a GitHub context.
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 zero waste, efficiently conveying the core purpose. Every word earns its place, 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?
Given the complexity of updating a GitHub comment (a mutation with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It lacks details on behavior, parameters, and expected outcomes, failing to compensate for missing structured data.
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 adds no meaning beyond the parameter names. It doesn't explain what 'commentId' refers to (e.g., numeric ID from GitHub) or what 'body' should contain (e.g., markdown text), leaving parameters semantically unclear.
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 ('Update') and target resource ('an existing comment on a GitHub issue'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_issue_comment' or 'delete_issue_comment' beyond the verb, missing explicit comparison.
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 'create_issue_comment' or 'delete_issue_comment', nor does it mention prerequisites such as needing an existing comment ID. The description assumes context without explicit instructions.
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 states the tool performs an update operation but doesn't mention required permissions, whether changes are reversible, rate limits, or what happens to unspecified fields. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words. It's appropriately sized and front-loaded, immediately conveying the core purpose without unnecessary elaboration.
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's complexity (5 parameters, mutation operation), lack of annotations, 0% schema description coverage, and no output schema, the description is insufficient. It doesn't provide enough context for safe and effective use, missing details on behavior, parameters, and expected outcomes.
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 0% description coverage, so parameters are undocumented in the schema. The description doesn't add any parameter semantics—it doesn't explain what 'milestoneId', 'title', 'description', 'dueDate', or 'state' represent, their formats, or constraints beyond the enum for 'state'. This fails to compensate for the schema's lack of 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 states the action ('Update') and resource ('a GitHub milestone'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other update tools in the sibling list (like update_issue, update_project, etc.) beyond specifying the 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?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites (like needing an existing milestone), when not to use it, or how it relates to similar tools like 'update_issue' or 'create_milestone'.
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 full burden for behavioral disclosure. It states 'Update' implying mutation but doesn't cover permissions needed, whether changes are reversible, rate limits, or what happens to unspecified fields. 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, efficient sentence with zero waste. It's appropriately sized and front-loaded, stating the core purpose directly without unnecessary elaboration.
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 complexity (5 parameters, 2 with enums, no annotations, no output schema), the description is incomplete. It doesn't explain parameter usage, behavioral traits, or output expectations, making it insufficient for an AI agent to reliably invoke this mutation tool.
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 by explaining parameters. It adds no meaning beyond the schema—doesn't clarify what 'projectId' refers to, what fields can be updated, or the semantics of enums like 'visibility' or 'status'. With 5 parameters (2 with enums) and no param info in the description, this is inadequate.
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 ('Update') and target resource ('an existing GitHub project'), which is specific and unambiguous. However, it doesn't distinguish this tool from other update tools in the sibling list (like update_issue, update_milestone, update_project_field, etc.), missing sibling differentiation.
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 doesn't mention prerequisites (e.g., needing an existing project ID), exclusions, or comparisons to sibling tools like 'create_project' or other update operations, leaving usage context unclear.
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 states 'Update a custom field', implying a mutation operation, but does not disclose any behavioral traits such as required permissions, whether the update is reversible, rate limits, or what happens to existing data. 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, clear sentence with no wasted words. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
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 complexity of a mutation tool with 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It does not provide enough information for an AI agent to understand how to invoke the tool correctly or what to expect in return. More details on parameters, behavior, and usage are 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?
Schema description coverage is 0%, meaning none of the 6 parameters are documented in the schema. The description does not add any meaning beyond the tool name—it does not explain what parameters like 'projectId', 'fieldId', 'options', or 'required' mean or how to use them. This fails to compensate for the lack of schema 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 states the action ('Update') and the resource ('a custom field in a GitHub project'), providing a specific verb+resource combination. However, it does not distinguish this tool from sibling tools like 'update_project' or 'set_field_value', which might have overlapping functionality, so it lacks sibling differentiation.
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. For example, it does not specify if this is for modifying existing fields only, or how it differs from 'create_project_field' or 'clear_field_value'. There is no 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is an update operation (implying mutation) but doesn't mention required permissions, whether changes are reversible, rate limits, or what happens to existing README content. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple update operation and front-loads the essential information.
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, 0% schema coverage, and no output schema, the description is inadequate. It doesn't explain what the tool returns, error conditions, authentication requirements, or important behavioral aspects. The description should provide more context given the lack of structured documentation.
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%, meaning neither parameter has documentation in the schema. The description mentions 'README content' which hints at the 'readme' parameter, but doesn't explain either parameter's purpose, format, or constraints. For a tool with 2 undocumented parameters, this minimal compensation is insufficient.
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 ('Update') and target resource ('README content of a GitHub project'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'update_project' or 'get_project_readme', but the specific focus on README content provides reasonable 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?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like needing an existing project), when not to use it, or how it differs from similar tools like 'update_project' or 'get_project_readme' in the sibling list.
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 full burden for behavioral disclosure. While 'Update' implies mutation, it doesn't specify what permissions are required, whether changes are reversible, what happens to existing view settings not mentioned, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant 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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information.
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 4 parameters (2 required), 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter usage, behavioral implications, or what to expect from the operation, leaving significant gaps for agent understanding.
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?
With 0% schema description coverage for all 4 parameters, the description provides no information about what 'projectId', 'viewId', 'name', or 'layout' mean or how they should be used. The description doesn't compensate for the complete lack of parameter documentation in 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 states the action ('Update') and target ('a view in a GitHub project'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'update_project_field' or other update tools, which would require more specific differentiation.
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 'create_project_view' or 'delete_project_view', nor does it mention prerequisites or context for updating views. There's no explicit when/when-not guidance or named alternatives.
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 states this is an update operation, implying mutation, but doesn't disclose permissions required, whether changes are reversible, rate limits, error conditions, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and lists the modifiable fields directly. Every word earns its place, 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?
Given this is a mutation tool with 4 parameters, 0% schema description coverage, no annotations, and no output schema, the description is incomplete. It covers the purpose and fields but lacks critical context like behavioral traits, parameter details, usage guidelines, and response information. For a tool that modifies pull requests, this leaves significant gaps for an AI agent.
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 schema provides no parameter descriptions. The description lists the updatable fields ('title, body, or state'), which maps to 3 of the 4 parameters, but doesn't explain 'pullNumber' (the required parameter) or provide any syntax, format, or constraints for any parameters. It adds some value but doesn't fully compensate for the coverage gap.
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 ('Update') and resource ('a pull request') with specific fields that can be modified ('title, body, or state'). It distinguishes from sibling tools like 'create_pull_request' and 'merge_pull_request' by focusing on modification rather than creation or merging. However, it doesn't explicitly differentiate from 'get_pull_request' in terms of read vs. write operations.
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 doesn't mention prerequisites (e.g., needing an existing pull request), exclusions (e.g., not for creating new pull requests), or comparisons to sibling tools like 'update_issue' or 'merge_pull_request'. Usage is implied by the verb 'Update' but lacks explicit 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 provided, the description carries the full burden of behavioral disclosure. 'Create' implies a write operation, but it doesn't specify required permissions, rate limits, error conditions, or what happens on success (e.g., returns the created label). For a mutation tool, this lack of detail is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. This is an example of optimal conciseness for a 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?
Given the complexity (a write operation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions or outcomes, and the parameters are undocumented. For a creation tool in a GitHub context, more context is needed to be fully helpful.
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 schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description doesn't mention any parameters, leaving all three (name, color, description) undocumented. However, since there are only 3 parameters and the tool name implies basic creation, a baseline score of 3 is appropriate, though the description adds no value 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 'Create a new GitHub label' clearly states the verb ('Create') and resource ('GitHub label'), making the purpose immediately understandable. However, it doesn't differentiate this from sibling tools like 'create_issue' or 'create_milestone' beyond specifying the resource type, which is why it doesn't reach a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention prerequisites (e.g., repository permissions), when it's appropriate (e.g., for organizing issues), or what other tools might be related (like 'list_labels' for viewing existing ones). This leaves the agent with minimal context for decision-making.
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. While 'Delete' implies a destructive, irreversible mutation, the description does not specify permissions required, side effects (e.g., whether related data is affected), error conditions, or confirmation steps. This leaves significant gaps in understanding the tool's behavior and risks.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, 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?
Given the complexity of a destructive operation with no annotations, no output schema, and low parameter coverage, the description is incomplete. It lacks critical details about behavior, parameters, and outcomes, making it insufficient for safe and effective use by an AI agent.
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 has 0% description coverage, with one parameter ('ruleId') undocumented. The description does not add any meaning about this parameter, such as what a ruleId is, how to obtain it, or its format. Since schema coverage is low, the description fails to compensate, resulting in inadequate 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 states the action ('Delete') and the resource ('an automation rule from a project'), which is specific and unambiguous. However, it does not differentiate this tool from sibling tools like 'disable_automation_rule' or 'delete_project', leaving room for potential confusion about when to use this versus those alternatives.
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 'disable_automation_rule' (which might temporarily deactivate instead of permanently delete) or 'delete_project' (which removes an entire project). It lacks explicit context, prerequisites, or exclusions, offering minimal usage 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Delete') which implies a destructive mutation, but doesn't mention critical details like whether deletion is permanent, what permissions are required, or what happens on success/failure. This leaves significant gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information.
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 mutation tool with no annotations, 0% schema description coverage, and no output schema, the description is inadequate. It doesn't address behavioral implications, error conditions, or what the tool returns, leaving the agent with insufficient context to use it safely and effectively.
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 schema description coverage is 0%, meaning the single parameter 'commentId' is undocumented in the schema. The description doesn't add any parameter-specific information beyond what's implied by the tool name, so it doesn't compensate for the schema gap. However, with only one parameter, the baseline is higher than for multi-parameter tools.
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 ('Delete') and target resource ('a comment from a GitHub issue'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'delete_draft_issue' or 'delete_milestone' beyond the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, prerequisites (e.g., permissions needed), or exclusions. It lacks context about sibling tools like 'update_issue_comment' or 'list_issue_comments' that might be relevant alternatives.
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 states the action ('Enable') but doesn't describe what enabling entails (e.g., whether it activates the rule immediately, requires permissions, has side effects like notifications, or what happens if the rule is already enabled). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior and implications.
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, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple tool. Every word earns its place by directly conveying the tool's function without unnecessary elaboration.
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's complexity (a mutation operation), lack of annotations, no output schema, and minimal parameter guidance, the description is incomplete. It doesn't address behavioral aspects like permissions, side effects, error conditions, or return values. For a tool that modifies system state, this leaves the agent with insufficient context to use it safely and effectively.
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 has one parameter ('ruleId') with 0% description coverage, meaning the schema provides no semantic context. The description doesn't add any parameter-specific information beyond implying that 'ruleId' identifies the rule to enable. It doesn't explain the format of 'ruleId' (e.g., numeric ID, UUID, name) or where to find it. With low schema coverage, the description compensates minimally, resulting in a baseline score.
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 ('Enable') and the target resource ('a disabled automation rule'), providing a specific verb+resource combination. It distinguishes from sibling tools like 'disable_automation_rule' and 'create_automation_rule' by focusing on enabling existing disabled rules rather than creating new ones or disabling them. However, it doesn't explicitly differentiate from 'update_automation_rule' which might also modify rule states.
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 doesn't mention prerequisites (e.g., the rule must exist and be disabled), when not to use it, or direct alternatives like 'update_automation_rule' for state changes. The agent must infer usage from the tool name and description alone without explicit 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves README content, implying a read-only operation, but does not specify if it requires authentication, rate limits, error handling, or the format of the returned content. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 directly states the tool's function without unnecessary words. It is front-loaded and efficiently conveys the core purpose, making it easy to parse quickly. There is no wasted language or redundancy.
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's simplicity (1 parameter, no annotations, no output schema), the description is minimal but inadequate. It does not cover parameter meaning, behavioral details like authentication or output format, or usage context compared to siblings. For a tool in a server with many sibling tools, more completeness is needed to guide effective use.
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 has 1 parameter with 0% description coverage, and the tool description does not mention any parameters. Since there is only one parameter, the baseline score is 4, but the description adds no value beyond the schema, so it is adjusted to 3. It fails to explain what 'projectId' represents or how to obtain it, which is a missed opportunity for clarity.
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's purpose: 'Get the README content of a GitHub project.' It specifies the verb ('Get') and resource ('README content of a GitHub project'), making it easy to understand what the tool does. However, it does not differentiate from sibling tools like 'get_project' or 'update_project_readme', which would require more specificity to score 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, such as needing a project ID, or compare it to sibling tools like 'get_project' (which might return general project info) or 'update_project_readme' (for modifying the README). Without such context, users may struggle to select the correct tool.
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 full burden for behavioral disclosure. While 'List all fields' implies a read-only operation, it doesn't specify whether this requires authentication, what format the output takes, whether there are pagination limits, or what happens with large projects. For a tool with zero annotation coverage, this is insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise - a single sentence that states exactly what the tool does without any wasted words. It's front-loaded with the core functionality and doesn't include unnecessary elaboration.
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 with no annotations, no output schema, and minimal parameter documentation, the description is inadequate. It doesn't explain what 'fields' means in the GitHub project context, what data structure is returned, or any limitations or requirements for using this tool. The description leaves too many contextual gaps for effective agent use.
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 description mentions 'in a GitHub project' which contextually relates to the 'projectId' parameter, but doesn't explain what format this ID should take or where to obtain it. With 0% schema description coverage and only one parameter, the description provides minimal additional semantic value beyond what's implied by the tool name and context.
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 ('List all fields') and resource ('in a GitHub project'), making the purpose immediately understandable. However, it doesn't distinguish this tool from similar sibling tools like 'get_project_field' or 'list_project_items', which would require explicit differentiation for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With many sibling tools available (like 'get_field_value', 'list_project_items', 'create_project_field'), there's no indication of when this specific listing operation is appropriate versus other field-related operations.
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 burden. It mentions supporting all field types, which adds useful context about capabilities, but doesn't disclose behavioral traits like error handling, permissions needed, rate limits, or what happens if parameters are invalid. This is a significant gap for a tool with no 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, efficient sentence with zero waste. It's front-loaded with the core purpose and includes additional useful detail about supported field types, making it appropriately sized and well-structured.
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's complexity (3 required parameters), lack of annotations, and no output schema, the description is incomplete. It covers the 'what' but misses critical context like parameter semantics, behavioral details, and return values, leaving gaps that could hinder correct tool 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%, so the schema provides no parameter details. The description doesn't add any meaning to the parameters (projectId, itemId, fieldId)—it doesn't explain what these IDs represent, how to obtain them, or their format. This leaves all three parameters undocumented, failing to compensate for the low coverage.
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 verb ('Get') and resource ('field value for a GitHub project item'), making the purpose specific and understandable. It distinguishes from siblings like 'set_field_value' and 'clear_field_value' by focusing on reading, though it doesn't explicitly name these alternatives.
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?
Usage is implied by the description's focus on reading field values, suggesting it's for retrieval rather than modification. However, it lacks explicit guidance on when to use this versus alternatives like 'list_project_fields' or 'get_project', and doesn't mention prerequisites 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, the description carries full burden. It states the tool disables a rule without deletion, which implies a state change (mutation) but doesn't disclose permissions needed, whether the change is reversible, side effects, or error conditions. Minimal behavioral context is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and adds a clarifying constraint ('without deleting it'). Zero waste, appropriately sized for the tool's simplicity.
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 mutation tool with no annotations and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, or output. Given the tool's straightforward nature, it's passable but leaves gaps in guidance and transparency.
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 0%, but the single parameter 'ruleId' is self-explanatory. The description doesn't add any parameter details beyond what the schema name implies. Baseline is 3 since the parameter is simple and the schema covers it structurally, though no semantic enrichment is offered.
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 ('Disable') and the resource ('an automation rule'), and specifies the effect ('without deleting it'). It distinguishes from 'delete_automation_rule' by noting preservation, but doesn't explicitly differentiate from 'enable_automation_rule' or other rule-related tools.
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 'enable_automation_rule', 'update_automation_rule', or 'delete_automation_rule'. The description implies it's for temporarily deactivating rules, but lacks explicit context or prerequisites.
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 full burden for behavioral disclosure. While it explains what draft issues are (native to Projects v2, no repository issue needed), it doesn't mention permissions required, whether this is a write operation (implied by 'Create' but not explicit), rate limits, or what happens on success/failure. For a creation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear, efficient sentences with zero waste. The first sentence states the core purpose, the second provides important contextual differentiation. Every word earns its place and the information is front-loaded appropriately.
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 creation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. While it explains the 'what' and provides some GitHub-specific context about Projects v2, it lacks crucial information about parameters, permissions, behavioral outcomes, and what the tool returns upon success.
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?
With 0% schema description coverage and 4 parameters (2 required), the description provides no information about any parameters. It doesn't explain what 'projectId' refers to, what format 'title' and 'body' should use, what 'assigneeIds' represent, or any constraints. The description fails to compensate for the complete lack of schema 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 clearly states the specific action ('Create a draft issue') and resource ('in a GitHub project'), with explicit differentiation from repository issues ('native to Projects v2 and don't require creating a repository issue first'). This distinguishes it from sibling tools like 'create_issue' which likely creates repository issues.
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 about when to use this tool (for Projects v2 draft issues) by contrasting it with repository issues, which helps differentiate it from 'create_issue'. However, it doesn't explicitly mention when NOT to use it or provide alternatives beyond the implied contrast.
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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