yt-mcp

Server Quality Checklist

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

Latest release: v1.25.0
Disambiguation3/5
The tool set is very large and many tools serve similar reporting/analytics purposes (e.g., get_handoff_snapshot, track_cross_dept_journey, get_stuck_handoffs; get_team_dashboard, get_multi_team_dashboard, get_team_pulse, get_multi_team_pulse). While descriptions are detailed, an agent may struggle to pick the right tool for a given intent due to overlapping coverage. Core issue/comment operations are clearly distinct, but the analytics layer blurs boundaries.
Naming Consistency4/5
Most tools follow a clear verb_noun snake_case pattern (get_issue, create_issue, update_issue, add_comment, delete_comment, list_projects, search_users). Deviations exist, such as monthly_time_report_by_user, user_time_summary, and bulk_update_preview/execute (which are still recognizable but not uniform). Overall the convention is consistent enough to be predictable.
Tool Count2/5
84 tools is far beyond what is typically considered well-scoped. The server attempts to cover the entire YouTrack domain, including deep analytics and niche workflows, but this creates a bloated surface that is overwhelming. The count is excessive even for a complex domain, and many tools could be consolidated (e.g., a single 'dashboard' tool with configurable views).
Completeness5/5
The tool surface is remarkably comprehensive: it covers CRUD for issues, comments, articles, work items, sprint/board management, search, user lookup, bulk operations, rollbacks, translation workflows, and extensive reporting. There are no obvious dead ends—every primary operation appears to have corresponding read/update/delete paths. This is a rare case where completeness is effectively a non-issue.
Average 4/5 across 84 of 84 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 55 commits in the last 12 weeks
- Last stable release on September 2, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'Create' with no disclosure of side effects, permissions, or behavior beyond the obvious write operation. Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds nothing about what creating a board entails or what happens on success/failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point, but the Args section largely duplicates the input schema. It is concise yet adds little structural value beyond repeating parameter names with terse descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema details provided and minimal context, the description omits return value information, usage scenarios, and any caveats. For a mutation tool with side effects, more context is needed for an agent to invoke it confidently.
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 Args list provides brief English explanations like 'Comma-separated project short names' and 'Column field (default: State)' that add meaning beyond raw schema property names. However, coverage is still shallow; no constraints, formats, or examples are given, so it only partially compensates for the 0% 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 states a clear verb ('Create') and resource ('agile board'), which distinguishes it from siblings like get_agile_board and delete_agile_board. However, it is essentially a restatement of the tool name with minimal added detail, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_agile_board or update_sprint. The description only states what the tool does, not when it should be chosen or what prerequisites exist.
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?
The description only states the action without disclosing any behavioral traits beyond what the annotations declare (e.g., that it is a non-read-only, non-idempotent write). It omits potential side effects, permission requirements, or failure modes. The full burden falls on the description since annotations are minimal, yet nothing is added.
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 concise and front-loaded with the purpose sentence, followed by a parameter list. Every sentence is useful, with no fluff. Minor formatting optimizations could group parameters but the content has no wasted words.
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 straightforward add-comment operation, the description covers the basic inputs, but it does not explain what the operation returns, how errors manifest, or any required permissions. The presence of an output schema partially compensates for return-value details, yet the writing nature of the tool and 0% schema coverage suggest more context could be provided.
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%, so the description must compensate. It does list all 3 parameters with brief clarifications: issue_id ('ID or URL'), text ('markdown'), instance ('youTrack instance (optional)'). This adds some value beyond the bare schema names, but the notes are minimal and do not elaborate on formats, constraints, or defaults in detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb-resource pair ('Add a comment to a YouTrack issue'), which is unambiguous and distinguishable from siblings like update_comment or add_article_comment. It identifies the resource and target system, though it does not explicitly contrast with add_article_comment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives (e.g., update_comment, find_comments). No prerequisites or context are given, leaving the agent to infer from the name alone that this is for creating a new comment on an issue.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already cover the side-effect profile (read-only, idempotent, non-destructive), so the description does not need to restate safety. However, it adds no behavioral context such as what fields are searched, how the optional instance is resolved, or what happens when max_results is exceeded; it is minimally acceptable but not enlightening.
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 short and front-loads the purpose, but the 'Args' section mostly repeats the schema's property names and defaults. It is not bloated enough to hurt, but the lower-value lines prevent a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search with schema and output schema available, this is close to sufficient. Still, the description leaves important selection context implicit, notably the semantics of query and the meaning of omitting instance, so an agent gets only a partial operational picture.
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 the Args block adds only near-tautological labels: 'query: Search string' and 'max_results: Max results'. The one small addition is identifying instance as a 'YouTrack instance (optional)', yet the description still omits query syntax and how the empty/default instance is interpreted.
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 opening phrase 'Search Knowledge Base articles' gives a specific verb and resource and clearly distinguishes this from sibling tools like search_issues because it targets KB articles rather than issues or users. It lacks only added scope or filtering context, which would push it to 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 given about when to prefer this tool over sibling alternatives such as search_issues or get_article. The description implies a query-based search use case but never states exclusions or conditions, leaving tool selection to inference.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds little behavioral context beyond that; it does not explain what 'quality indicators' means, how the time window works, or what the output format is. The 'since' parameter description gives some detail but the overall behavioral burden is not fully met.
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 concise and well-structured: a one-sentence overview followed by a clean parameter list. Every line is useful and there is no filler. Minor gap: the overview could be slightly more explicit about the quality indicators, but overall it is efficient.
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?
With an output schema present, return values do not need explanation. The parameter list covers required fields and defaults. However, the description lacks context about what 'quality indicators' refers to and does not state any limiting behavior (e.g., max results or time bounds). For a tool with moderate complexity, this is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args section explains each parameter's meaning (project, since, creator, limit, instance), including defaults and allowed formats for 'since'. This compensates well for the lack of schema descriptions and adds value beyond what the schema's titles/defaults convey.
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 a specific verb ('Report') and a resource ('recently created issues') with a distinguishing feature ('quality indicators'). It is clear what the tool does, but it does not explicitly differentiate itself from siblings like get_issues or search_issues beyond the 'creation activity' angle.
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 when-to-use or when-not-to-use guidance is provided. The description implies it is for reporting creation activity, but it does not contrast with alternatives (e.g., get_issues or search_issues) or mention any exclusions 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?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds no additional behavioral context such as response format, pagination, rate limits, or potential performance considerations. It only restates that it is a combined dashboard, which is already evident from the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, opening with a direct purpose statement and followed by a structured parameter list. It avoids unnecessary prose. The parameter list is functional but could be integrated into the schema descriptions to reduce redundancy; nevertheless, it is well organized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has annotations, an output schema, and parameter descriptions, the basic callable information is present. However, it lacks any usage context (e.g., when to prefer this over get_team_dashboard or get_multi_team_pulse) and does not mention potential limits or edge cases. This leaves some ambiguity for an agent deciding among similar dashboard tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description's Args section provides significant semantic value beyond the bare schema, explaining that projects are comma-separated short names, active_limit and blocked_limit specify top N counts, and group_by_product controls grouping. This compensates for the 0% schema description coverage. However, not all parameters receive equally detailed explanations (e.g., instance is only 'optional').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('get') and resource ('multi-team dashboard'), specifying it provides a 'combined dashboard for multiple projects in one call.' This clearly distinguishes it from single-team dashboard tools like get_team_dashboard. However, it does not explicitly differentiate from other multi-team tools such as get_multi_team_pulse, leaving slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusion criteria, prerequisites, or contextual triggers. The phrase 'in one call' hints at efficient batch retrieval, but there is no explicit instruction or comparison 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?
The description only restates the action ('Add a comment') and does not reveal any behavioral characteristics beyond the annotations. It does not mention that this is a write operation (already indicated by readOnlyHint:false), nor does it add info about error conditions, idempotency nuances, or side effects that the agent wouldn't already know from annotations. The description contributes no new 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 economical: a single line that states the purpose, followed by an 'Args' list with brief explanations. There is no redundant fill, and the key information is right up front. The structure is clean and easily scannable for an agent.
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 relatively simple tool (three parameters, one optional), the description covers the basics: what action is performed and concrete details about each parameter. However, it omits any mention of authorization requirements, expected response (attention though the output schema exists), or behavior in error cases such as if the article or article ID does not exist. Since this is a write tool, a note about modification permissions would have been ideal context.
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 description must compensate. The 'Args' section provides minimal semantics: article_id is described as 'Article ID or database ID' (suggesting at least a 长度 of the value), text is clearly markdown, and instance is declared optional with a default. While these are additional hints beyond the raw schema, they are thin and do not clarify value formats, constraints, or relationships between parameters, warranting a mid-level score.
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 specifies the action ('Add a comment'), the resource ('Knowledge Base article'), and inherently distinguishes it from its sibling 'add_comment' (which targets different entities like issues). The purpose is unambiguous and the scope is clear, meeting the threshold for a specific verb+resource description.
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 the alternative 'add_comment' or other issue-centric tools. It does not state that this is for knowledge articles only or explicitly exclude issue comments. The lack of any 'when to use' or 'when not to use' instruction, including no mention of prerequisites (e.g., the article must exist), leaves the agent to infer 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?
The description adds no behavioral context beyond the one-line function. Annotations already indicate non-read-only, non-destructive, and idempotent behavior, but the description does not explain side effects, permissions, or idempotency implications. The description carries minimal extra value.
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 compact with a clear one-liner followed by a structured parameter list. No redundant text or fluff; every line earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers parameters and the basic action, but lacks usage context, link type examples, or how this relates to remove_issue_link. Given the output schema exists and annotations cover safety, the description is adequate but not complete for a new agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the Args section in the description is essential. It provides meaningful definitions for each parameter (source/target IDs, relation type default, optional instance), compensating for 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 'Link two issues together' uses a clear verb and resource, making the core purpose obvious. It does not differentiate from sibling tools like remove_issue_link, but the name and action are unambiguous enough for basic selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical scenarios, or exclusions, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the bar for additional context is lower. The description adds that only 'accessible' projects are returned and implies no filtering, but it does not describe pagination, sorting, or any side effects. This modest addition earns a 3.
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 very short and front-loaded with the primary action. The Args block is somewhat redundant with the schema but is not verbose. Every word earns its place, though the structure could be improved by integrating parameter details into the main text rather than duplicating them.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with one optional parameter, an output schema, and safety annotations, the description provides the essential purpose. However, it lacks any detail on the instance parameter format or any note about potential pagination/limits. It is adequate but leaves room for an agent to misunderstand how to specify the instance.
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 parameter 'instance'. It only says 'instance: YouTrack instance (optional)', which adds 'YouTrack' but still does not explain what format the value should take (e.g., URL, name, or ID) or how it affects the results. The schema already shows default '' and non-required, so 'optional' is redundant.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'all accessible YouTrack projects', clearly identifying the tool's function. It distinguishes itself from sibling tools like list_tags and list_templates by explicitly targeting projects, and the scope 'all accessible' clarifies what will be 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?
There is no guidance on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or conditions for choosing list_projects over other listing or search tools. It only states the purpose and the optional instance parameter, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds the behavioral detail that it restores the previous value, which implies overwriting the current state. However, it does not mention potential irreversibility, permission requirements, or whether the operation can be undone, so it adds only partial context beyond the 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 concise, with a single functional sentence followed by a short Args list. It is well-structured and front-loaded with the primary purpose. No unnecessary text, though the Args list duplicates schema property names without adding substantial new meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown) which likely covers return values. The description explains the main action and parameter origins, but lacks information about when to use it versus bulk_rollback, any side effects beyond 'restoring,' or required permissions. For a destructive operation, missing these details leaves some context incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the burden of explaining parameters. It provides a brief but clear explanation for each: issue_id (ID or URL), activity_id (from get_issue_history), and instance (optional). This compensates reasonably well for the absent schema descriptions, though it could elaborate on formats or examples.
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 operation: 'Rollback a specific change by restoring the previous value.' It identifies the resource (an issue change) and the action (rollback), which is specific. It does not explicitly distinguish itself from the sibling tool 'bulk_rollback,' but the word 'specific' implies a single-change scope, which slightly aids 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?
No explicit guidance on when to use this tool versus alternatives. It mentions that activity_id comes from get_issue_history, which hints at a prerequisite, but does not state conditions for use or exclusions (e.g., use bulk_rollback for multiple changes). The agent is left to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate that this is a mutating, non-idempotent operation. The description adds the behavioral context of logging time, implying a time entry is created. However, it doesn't disclose potential side effects, such as whether calling it twice creates duplicate entries or whether existing time entries are affected. Since the annotations cover the basic safety profile, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and front-loaded with the core purpose. The Args block is a clean, efficient way to document six parameters, and each line is short and useful. There is minimal waste, though the parameter lines are somewhat redundant with the input schema titles.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all input parameters and the basic operation, but it does not explain the return value or side effects. An output schema exists per context signals, so the return type is presumably structured, but an agent would still benefit from knowing what the tool returns (e.g., created work item ID). For a write operation, this is a notable gap, but the core calling information is present.
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%, so the description must compensate. It does list all six parameters with concise explanations, such as 'issue_id: Issue ID or URL' and 'duration_minutes: Time spent in minutes,' which adds meaning beyond the schema titles. However, it doesn't explain constraints like duration_minutes range or date format details beyond the YYYY-MM-DD example. The parameter descriptions are adequate but not thorough.
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 starts with a clear verb and resource: 'Log time on a YouTrack issue.' This distinguishes it from many sibling tools like add_comment or create_issue, though it doesn't explicitly contrast with update_work_item or delete_work_item. Overall the purpose is specific and understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing required arguments, but there is no explicit when-to-use or when-not-to-use guidance. It doesn't mention alternatives like update_work_item or get_work_items, so an agent must infer when this tool is appropriate. The context of logging time is fairly clear, but the guidance is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a mutable, non-idempotent write operation that creates a new resource. The description adds minimal behavior context, such as the ability to nest via parent_article_id, but it does not disclose what happens after creation, whether a parent article must exist, or whether the instance parameter is required in multi-instance setups. It does not contradict the 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 reasonably concise and uses a clear Args list format that is easy to scan. The main purpose is stated up front, and each parameter gets a separate line. It could be slightly tighter by omitting obvious terms like 'Article title', but overall it is effective and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is an output schema and no nested objects, the agent can infer the return type. However, the description lacks important contextual details for a creation tool: it does not explain whether parent_article_id must reference an existing article, whether 'instance' is needed for multi-tenant setups, or how errors (e.g., duplicate summary, invalid project) manifest. It is adequate, but not comprehensive.
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%, so the description must compensate. It does explain the meaning of all five parameters: project, summary, content, parent_article_id, and instance. However, it adds little beyond the schema; no examples, formatting rules, or constraints are given for values like project short name or markdown content.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb, resource, and essential fields: 'Create a new Knowledge Base article' establishes what the tool does. It is distinguishable from siblings like create_issue and update_article because it explicitly targets Knowledge Base articles, but it does not explicitly contrast with update_article or search_articles, so it lacks strong 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description identifies the article context and lists required fields, implying creation of a Knowledge Base article. It does not explicitly state when to use this tool versus update_article or delete_article, nor does it mention prerequisites like needing an existing project or parent article, so usage guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=false, so the mutation trait is covered. The description adds some context about the structured fields format ('Section: value' separated by '|||') and optional instance, but doesn't disclose side effects, error conditions, or how templates interact with required fields. It neither contradicts annotations nor adds deep 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the main purpose, followed by a concise parameter list. Every line adds information, though the Google-style Args block is slightly verbose without adding meaning beyond what a shorter list would.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, an output schema exists, and annotations carry the basic mutation signal. The description covers parameter formats at a basic level but doesn't explain what the created issue returns, how template names map to actual templates, or what happens when fields are empty. This is adequate but has clear informational gaps.
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 description itself briefly defines each parameter, including template allowed values and the fields delimiter. This compensates minimally; however, it doesn't explain project short-name format, template behavior, product, or instance semantics beyond one-line labels.
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 ('a YouTrack issue using a predefined template'), and the parameter list distinguishes it from generic create_issue by emphasizing template and section values. It does not explicitly contrast it with create_issue, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by displaying a template field listing valid values and a fields format, but it doesn't state when to choose this instead of create_issue or other issue-creating siblings. No explicit alternatives or exclusion conditions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare non-read-only and non-idempotent behavior. The description adds useful call-time behavioral hints: board_name is a partial match and start/finish are optional ISO 8601 dates. However, it does not disclose side effects such as duplicate creation, board-not-found behavior, or validation failure consequences.
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 compact and efficient: a single purpose statement followed by a clean args list with no redundant prose. All necessary parameter semantics are front-loaded and easy to parse.
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?
Parameters are well covered, and an output schema exists so return format is not needed. However, key contextual gaps remain: no usage guidance, no mention of prerequisites, and no error or edge-case behavior. An agent can call it correctly but may not know when to choose it or what to expect on failure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by documenting all five parameters: board_name partial match, sprint_name purpose, start/finish format with examples, and instance optionality. This goes well beyond the bare parameter titles 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?
States a specific verb and resource ('Create a new sprint on an agile board'), making the primary action unambiguous. It is clear but does not explicitly differentiate from sibling tools like update_sprint, though 'create' contrasts with update and delete actions.
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 such as update_sprint or add_issues_to_sprint, nor any mention of prerequisites like an existing board or permission requirements. The agent must infer usage context from the name and arguments alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already convey that this is a safe, non-mutating read operation. The description correctly aligns with this by saying 'Get' (not modify). It adds a parameter default (max_results=20) and explains the instance parameter as optional, which supplements the schema. However, it does not disclose behavior like pagination limits, ordering, or which fields are returned beyond the output schema. Given the annotations cover the safety profile and the description provides minimal extra context, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and structured well: a clear one-line purpose followed by a compact argument list with inline explanations. It avoids redundant phrasing and front-loads the verb-resource clause. It could improve by adding usage context or a note on differences, but as a basic API description it is tight and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three top-level parameters, a simple purpose, and an existing output schema, the description provides enough to understand the core operation: it retrieves change history with optionally limited results. The output schema is present, so return structure is not needed in the description. However, it falls short of explaining how to handle large histories (pagination) or any edge cases with issue_id formats, but these are minor given the schema and limited scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 0% description coverage, the description text itself explicitly explains each parameter: issue_id as Issue ID or URL, max_results as max activities (default 20), and instance as optional YouTrack instance. This provides more semantic detail than the raw schema, giving agents sense of what values to pass. The only missing semantic is perhaps format or constraints (e.g., max_results enforcement), but the core meaning is well covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Get') on a specific resource ('change history of a YouTrack issue'). The verb-resource combination is specific. However, it does not explicitly distinguish this from sibling tools like get_issue_changes_summary or get_issue, though the 'history' wording implies a log of activities. The main gap is a lack of explicit differentiation, which prevents 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. It does not state any exclusion conditions (e.g., when to prefer get_issue_changes_summary for summaries) or mention any prerequisites. The only implicit signal is that it returns 'change history', but the user is left to infer the use case without explicit routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, which strongly covers safety and side-effect behavior. The description adds the board/column grouping context but does not disclose anything beyond that, such as how sprint names resolve or whether empty boards return an error. No contradiction exists.
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 concise, front-loaded with the main action, and every sentence earns its place. The Args list is efficient and provides necessary semantic detail without fluff. It is appropriately sized for a tool with three parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and annotations cover safety, the description is sufficient for basic invocation, but it lacks guidance for selecting this tool over similar sibling tools. It also does not state prerequisites such as whether the board must exist or what happens when the sprint is not found. These are notable gaps in an otherwise functional definition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the Args section in the description is the sole source of parameter meaning and compensates well. It clarifies that board_name accepts a name, ID, or URL; that sprint supports the special token 'current' and defaults to it; and that instance is optional. This adds real value beyond the bare schema, though details like allowed instance formats or sprint identifier syntax are omitted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get issues on an agile board grouped by column.' This makes the core function clear. However, it does not distinguish from sibling tools such as get_agile_board or get_active_sprint_issues, which might also surface board/sprint issues.
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 about when to use this tool versus alternatives. It does not mention any preconditions, exclusions, or competing sibling tools. The only implied context is that it returns issues grouped by column, but that is not explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is consistent with the annotations (a read-only, idempotent, open-world dashboard) and implicitly communicates read-only aggregation through 'dashboard' and 'summary stats.' It does nothing meaningful beyond that — it does not describe what defines 'active' vs 'blocked', how the summary stats are computed, or what the return format implies.
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 opening purpose sentence precedes an efficient Args block that maps each field and default directly. Each line earns its place with no filler or redundant prose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema covers the return format, so that omission is fine, and the safety profile is covered by annotations. But the definition doesn't characterize what 'top blocked' or 'top active' mean, what the 'summary stats' contain, or how instance scoping interacts. It's a serviceable but not complete spec for a composite-data tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides meaningful meaning for all six fields — project short name, top N for active/blocked, grouping by Product, comma-separated regex for exclusions, and optional youtrack instance. The main gap: exclude_patterns doesn't say what is being excluded, and 'active'/'blocked' are not defined.
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?
States a specific combined purpose — a dashboard of top active, top blocked, and summary stats for a project — with a clear verb-resource structure that sets it apart from separate top-issue tools in the sibling set. It doesn't explicitly name the sibling alternatives, but the 'combined' framing effectively distinguishes it from get_top_active_issues and get_top_blocked_issues.
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 offers no guidance on when to call this tool instead of alternatives like get_top_active_issues, get_top_blocked_issues, or get_multi_team_dashboard. The word 'combined' hints at the intended use, but there's no explicit when/when-not rule or mention of which sibling to reach for.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no behavioral details beyond the parameter defaults, but it doesn't contradict the annotations either. Since the bar is lower with annotations, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence followed by a compact parameter list. Every element earns its place, and the core purpose is front-loaded. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, has an output schema, and annotations cover safety. The description provides parameter semantics and a clear purpose, but it lacks usage context (when to call it) and doesn't mention any limitations or edge cases. For a poll tool, guidance on typical polling intervals might be expected, but its absence is not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a brief semantic for each parameter (e.g., 'query: YouTrack query filter', 'since_minutes: Minutes to look back'), which gives meaning beyond the raw schema. The explanations are concise and useful, though not deeply detailed.
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 a specific action ('Poll for recently changed issues') with a time-based scope ('within the last N minutes'), which distinguishes it from sibling tools like search_issues or get_issues. However, it does not explicitly contrast with alternatives, so it doesn't achieve full 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 such as search_issues or get_issues. It implies a purpose ('poll for changes') but offers no exclusions or conditions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral context (e.g., pagination, result limits, or error cases), but there is no contradiction with 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 compact with a clear functional statement followed by a straightforward Args list. No redundant phrases, though the Args section partially repeats schema defaults.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with three parameters and an output schema, the description covers the essential invocation points. It lacks examples or deeper context about query syntax, but the parameters are self-explanatory and the annotations provide safety context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a brief explanation for each parameter: query is a YouTrack search query, max_results has a default of 50, and instance is optional. This adds meaning beyond the raw schema, though details on query syntax are minimal.
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 action ('Search YouTrack issues') and specifies the search mechanism ('query syntax'). It is specific enough to understand the core purpose, though it does not explicitly distinguish this from similar siblings like get_issues or count_issues.
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 only usage hint is about named periods for relative dates, which is a query syntax detail rather than a decision rule for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context by mentioning 'assess its quality,' hinting that it does more than a simple existence check, but it does not explain what quality means or how it is evaluated. No contradiction with annotations exists.
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 concise: one line for the tool's purpose followed by a structured parameter list. No fluff or repetition. The front-loaded purpose sentence immediately gives the agent the tool's primary function, and the parameter explanations are compact.
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?
With an output schema present, the description need not detail return values. However, it lacks guidance on when this tool should be invoked relative to sibling verification/lookup tools, and it does not clarify what 'assess its quality' entails (e.g., criteria used). Adequate for basic invocation but leaves some contextual ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage for its 5 parameters, but the description compensates by explaining each parameter's meaning, including defaults and optionality. For example, it specifies that created_since accepts durations or dates with a default of '7d'. This is clear and actionable, though some format constraints (e.g., exact date syntax) could be more explicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('task matching keywords') and adds the action 'assess its quality,' which clearly indicates what the tool does. It does not explicitly contrast with sibling tools like search_issues, so it lacks full differentiation, but the core purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrasing 'Check if a task matching keywords was created' implies this tool is used for post-creation verification, but it never states when to prefer it over alternative lookup tools such as get_issue or search_issues. Usage context is only implicit, with no explicit exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds the type of data returned (state distribution, health metrics, resolved issues) but does not disclose any additional behavioral traits such as permission requirements or output shape. Since annotations cover the safety profile, a baseline of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-organized: a one-line summary followed by a clear list of parameter explanations. It contains no filler or redundant statements, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and strong annotations, the description covers the essential parameter semantics and the high-level result content. It does not explain when to use the tool or how it differs from related dashboards, but for a read-only reporting tool with a rich output schema, the provided information is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It does so by providing a short explanation for each parameter: project short name, period for resolved issues, comma-separated regex to exclude, and optional instance. This is sufficient for an agent to understand what each parameter means, though not deeply detailed.
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 produces a 'Project health report' with state distribution, health metrics, and recently resolved issues. The verb is implied by the tool name and the description focuses on the resource and content. It does not explicitly differentiate from similar reporting siblings like get_team_dashboard, but the scope is clear enough for an agent to understand its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternative reporting tools such as get_team_dashboard or get_issues_digest. The description only states what the tool does, not the conditions under which it should be selected over others. Sibling tools are not referenced at all.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, establishing a safe read operation. The description adds sorting behavior and grouping details but doesn't disclose return structure or edge cases. This is adequate but not extensive.
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 concise and well-structured with a clear one-line purpose followed by an Args list. Every sentence adds value, with no redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return value details are not needed. Annotations cover safety. The description covers all parameters and the core behavior. The main missing piece is usage guidance relative to sibling tools, but overall it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description carries the full burden of explaining parameters. It provides meaningful context for each parameter, including defaults and the 'per product when grouped' clarification for limit. It doesn't elaborate on regex syntax for exclude_patterns, but the basics are covered.
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 gets top blocked issues ranked by priority score, with a specific verb and resource. It distinguishes itself from siblings like get_top_active_issues by focusing on 'blocked' issues, though it doesn't explicitly name any 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 given on when to use this tool versus alternatives. The description only lists parameters without explaining the intended context or scenarios. Sibling tools like get_top_active_issues or get_at_risk_issues are not referenced, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which the description does not contradict. The description adds 'all' to indicate the scope (no filtering), providing some context beyond annotations, but it does not disclose other behavioral aspects like pagination or ordering.
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 minimal and directly front-loads the main purpose. It includes a clear 'Args' section for the parameter, with no redundant information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is an output schema and the annotations cover the safety profile, the description is adequate for calling the tool. However, it lacks usage context (when to use vs alternatives) and does not mention any edge cases or additional behaviors. It is sufficient but not rich.
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 has one parameter 'instance' with only a title and default, giving no semantic meaning. The description partially compensates by stating 'instance: YouTrack instance (optional)', which clarifies its purpose and optionality. However, it does not specify format or examples, leaving some ambiguity.
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 function as 'List all saved searches (queries)' with a specific verb 'List' and resource 'saved searches'. This distinguishes it from sibling tools like run_saved_search, which executes a search rather than listing 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention run_saved_search or any other related tool, nor any conditions or exclusions. Agents must infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already disclose that the tool is read-only, idempotent, and non-destructive, so the description need not restate those traits. It does add useful context by specifying the operation returns a count of matching issues rather than the issues themselves, and that the scope is defined by the given query. This is a meaningful behavioral trait beyond annotations, though it does not mention how instance selection or query limitations affect the count.
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 and well-structured. The main purpose is captured in a single front-loaded sentence, followed by a compact 'Args:' block. There is no redundant or filler content — every line provides directly actionable information for invoking the tool. This is an appropriate level of detail for such a straightforward operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity, the read-only and idempotent annotations, and the presence of an output schema, the description is largely complete for a successful invocation. The one element that could improve completeness is a note about the relationship between this tool and sibling search/list tools, plus a brief clarification on how to specify the 'instance' parameter. Apart from those points, the agent has enough information to call count_issues correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), so the description must compensate. The 'Args:' block does add some semantic value: it explains that 'query' is a YouTrack search query and that 'instance' is an optional YouTrack instance. However, these descriptions are minimal — they do not specify the expected format of the instance identifier, nor do they give examples of valid query syntax, leaving gaps that an agent must infer or learn from elsewhere.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Count' against a well-defined resource ('issues') and clearly scopes it with 'matching a YouTrack query.' This makes it immediately distinguishable from sibling tools like search_issues or get_issues, whose purpose would be to retrieve lists or individual issues. The phrase leaves zero ambiguity about the intended operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention that you should use this instead of search_issues or get_issues when only a count is needed, nor does it note any situations where the tool would be inappropriate. The intended usage is implied by the verb 'Count,' but no direct or alternative-routing guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which fully cover the safety and idempotency profile. The description adds no extra behavioral context beyond the basic 'list' action. Since the annotations already carry the burden, the description adds little value, but it does not contradict them either.
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: one line for purpose and a two-item argument list. Every sentence earns its place; no redundant or filler text. Front-loads the main purpose clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (list attachments), has a return schema, and annotations cover safety. The description provides essential action and parameter hints. It could mention potential pagination or ordering, but those are likely handled by the output schema. For a simple read-only list tool, this is sufficiently complete.
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 has 0% description coverage, so the description must compensate. It adds a valuable detail for 'issue_id': it can be an ID or URL. However, it does not explain what 'instance' means beyond 'optional', leaving ambiguity. With two parameters, only one gets meaningful enrichment, so partial compensation.
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 the resource 'attachments on a YouTrack issue'. It is specific enough to understand the tool's function, though it does not explicitly distinguish itself from sibling tools. However, the function is unique among siblings (only one other tool deals with attachments, but that one is get_attachment_url, which is different).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when you need to list attachments for an issue) but does not provide explicit guidance on when not to use or mention alternatives. Since there are siblings like add_attachment or get_attachment_url, more explicit routing would help, but the basic use case is understandable from the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds that the tool returns all issue tags with issue counts, but it does not mention pagination, scope boundaries, or data volume concerns beyond the word 'all'.
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 two short sentences with the core purpose front-loaded and no filler. The parameter note is directly integrated, 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple read-only tool with one optional parameter, strong annotations, and an output schema, so the description is nearly sufficient. The only gap is that usage selection among sibling tools is left to inference rather than explicitly addressed.
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 has only a title and default for the optional 'instance' parameter, with 0% description coverage. The description says 'instance: YouTrack instance (optional)', which adds a basic label but no details about format, accepted values, or behavior when omitted. It partially compensates for the sparse schema but does not fully enrich parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('List'), a clear resource ('issue tags'), and an additional detail ('with issue counts'). This distinguishes it from sibling list tools such as list_projects and list_templates, so an agent can identify its purpose immediately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool versus alternatives like search_issues or count_issues, and no explicit exclusions or prerequisites. The only usage cue is implicit from the tool name and one-line description, which is not enough for confident selection 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat safety. It adds the context of 'recent changes' and query matching, but these are essentially restatements of the tool's purpose and parameters. The description does not disclose any additional behavioral traits such as potential rate limits, authentication requirements, or output behavior beyond what annotations cover.
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 compact and well-structured: a single-sentence summary followed by a clean parameter list. Every sentence and bullet provides necessary information without unnecessary verbosity, and the main purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and annotations cover safety and idempotency, the description is largely complete for calling the tool correctly: it details the query, time range, limit, and optional instance. It lacks guidance on when to choose this tool relative to siblings, but that underlies the usage_guidelines score and does not significantly weaken the overall contextual picture for a simple read-only digest tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an explicit Args block that documents every parameter with format details and defaults. For example, it clarifies that 'since' accepts a duration like '24h' or a date like '2026-03-18', and that 'limit' is the max number of issues. This adds substantial meaning beyond the bare schema, which only provides types and titles, compensating for the 0% schema description 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 identifies the tool as retrieving a digest of recent changes for issues matching a query, which is a specific verb and resource. While this is reasonably specific, the description does not explicitly distinguish itself from sibling tools such as get_issue_changes_summary or search_issues, which could also relate to recent changes or queries.
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 information about when to use this tool over alternatives. It does not mention any conditions, exclusions, or related sibling tools, leaving it to the agent to infer usage context 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no extra behavioral context (e.g., pagination, sorting, or result format), but it does not contradict the 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 brief and front-loaded with the purpose, then lists parameter semantics in a clean format. Every sentence earns its place, though the Args section is somewhat repetitive of schema names but adds necessary meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with a read-only annotation profile and an output schema, the description is sufficient. It defines the search scope, parameters, and instance handling. Missing are edge-case behaviors or result size limits beyond the max_results default, but these are minor given the output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args section provides concise explanations for all three parameters (query, max_results, instance) with defaults and optionality. This compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search YouTrack users by name or login' states a specific verb and resource, and the scope is clear. It distinguishes itself from sibling tools like search_issues or search_articles by specifying user search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives. It only states what it does without mentioning any exclusions, prerequisites, or comparisons to sibling search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a non-read, idempotent, non-destructive mutation. The description adds that board_name and sprint_name are partial matches and issue_ids is comma-separated, which is useful. However, it does not explain whether issues are appended or replace the existing sprint contents, or how ambiguous partial matches are resolved. No contradiction with annotations exists.
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 compact and well-organized, with a one-line purpose followed by a clean parameter list. The phrase 'using YouTrack commands' adds little practical value and could be seen as filler, so it is not a perfect 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four primitive parameters, clear arg descriptions, and an output schema, the description covers the essential calling semantics. It omits possible error conditions and append-versus-replace behavior, but these are not critical for making a correct first call given the annotations and schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters are explicitly described in the Args block, which is essential given the 0% schema description coverage. It explains partial matching for board_name and sprint_name, gives a concrete comma-separated example for issue_ids, and marks instance as optional. This fully compensates for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Add issues to a sprint.' This clearly differentiates the tool from sibling operations like create_sprint, update_sprint, or bulk_update_execute. The only slightly vague phrase is 'using YouTrack commands,' but it does not undermine the clarity of the core action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, nor does it mention preconditions such as the board and sprint needing to exist. The implied use case is obvious from the name, but there are no explicit selection criteria, exclusions, or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context by disclosing that the tool reads a local configuration file, '~/.yt-mcp/managers.json', for approver mapping. It also details the classification buckets, revealing how results are categorized. No contradiction with annotations, but it does not mention what happens if the config file is missing or malformed.
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 front-loaded with a concise purpose sentence, followed by a compact list of classification buckets and parameter documentation. Every sentence carries useful semantic weight, but the list of six classification categories adds length. It is still well-structured and without redundancy, warranting a high score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the description covers inputs, defaults, a critical file dependency, and the high-level classification logic. Since an output schema exists, return shape is not required in the description. Missing failure-mode guidance (e.g., when managers.json is absent) and timezone/policy details prevent a perfect score, but overall it is largely complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that explains every parameter in plain language, adding meaning the input schema titles and types fail to provide. For example, it defines 'projects' as 'Comma-separated project shortnames; empty = all accessible' and clarifies 'strict' as 'only keyword+date comments count as approval.' The defaults mentioned in the description align with the schema defaults, making parameter semantics crystal clear.
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?
Description opens with a clear verb+resource: 'Audit Due-Date shifts in a period; classify each as compliant/unauthorized.' It also lists specific classification buckets, which distinguishes it from generic 'audit_issue_list' or 'get_deadline_impact'. However, it does not explicitly mention what distinguishes it from sibling tools such as 'audit_issue_list', so the agent must infer the distinction from context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to choose this tool over alternatives. It lacks explicit when-to-use or when-not-to-use statements, and no sibling tools are referenced for comparison. The intended usage is implied by the purpose statement, but the tool selection guidance is essentially absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations clearly mark destructiveHint and idempotentHint, and the description's 'Rollback all changes' aligns with these. The description adds a bit of scope ('all changes') but does not elaborate on side effects, reversibility, or failure behavior. Because annotations already carry the destructive warning, the description is minimally complemencing but not deeply transparent.
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 two sentences: a clear summary line and a formatted args block listing each parameter. There is zero redundant text, the key action is front-loaded, and the structure makes each fact easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return details are handled externally, and the description covers the essential input (the batch_tag) and optional instance. It omits mention of which specific operations a batch might include or failure modes, but for a rollback tool with strong annotations and an output schema, the description is sufficiently complete.
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 descriptions have 0% coverage, so the description must compensate. It explains batch_tag as 'Batch tag from bulk_update_execute' and instance as 'YouTrack instance (optional),' adding a light origin for batch_tag and the optionality of instance. However, it does not cover potential defaults or required values beyond the schema, leaving some parameters under-explained.
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 begins with a clear verb and resource: 'Rollback all changes from a bulk update batch.' It specifies the scope ('all changes') and ties it to a bulk update batch, distinguishing it from single-issue operations like rollback_issue. The reference to bulk_update_execute further anchors the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used after a bulk_update_execute by asking for its batch_tag, but it does not explicitly state when to use this over rollback_issue or when not to use it. It provides context but no exclusions or named alternatives, leaving the decision partially to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnly, idempotent, non-destructive, and open-world behavior. The description adds the 'all boards' scope but provides no additional behavioral detail such as filtering semantics or instance handling.
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?
Extremely economical: one clear sentence followed by a compact Args line. Every element earns its place and the core purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-optional-parameter list operation with a provided output schema and safety annotations, the description is nearly complete. The only missing piece is any distinction from sibling board tools, which is already covered in purpose clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must carry the parameter meaning. It does so by explicitly stating that the sole parameter 'instance' is optional and identifies it as a YouTrack instance, which is more than the schema's bare 'Instance' title.
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?
States a specific verb and resource ('List all agile boards') that clearly distinguishes from the sibling 'get_agile_board' by emphasizing the plural 'all'. The purpose is immediately unambiguous.
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 such as get_agile_board, get_sprint_board, or create_agile_board. The optional instance parameter is mentioned but there are no conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safe read-only nature is covered. The description adds that the tool returns status, assignee, and last update, but this is more about output content than behavior (e.g., no mention of pagination, rate limits, or error handling). It does not contradict annotations, so a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and well-structured: first line states the function, second line gives the use case, and then an Args block clarifies parameters. Every sentence earns its place, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present (though not shown) and rich annotations covering safety, the description provides enough information to call the tool correctly for a simple read operation. It could mention limitations or batch size, but it is effectively complete for the intended use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema description coverage is 0%, the description explicitly explains both parameters: issue_ids format (comma-separated IDs/URLs with an example) and instance optionality. This adds meaningful meaning beyond the raw schema, compensating for the lack of schema-level descriptions. Minor gap: no details on default instance 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 function: getting current status, assignee, and last update for a list of issues. This is a specific verb and resource, and the use case 'validating a list' adds context. However, it does not explicitly differentiate from siblings like get_issues or search_issues, though the focus on auditing is distinct enough.
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 a clear context for when to use this tool ('validating a list against current state'), which helps an agent understand the intended scenario. It does not mention alternatives or exclusions, but the purpose is clear enough to guide selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states that issues are not deleted, which is a critical behavioral guarantee beyond the annotations. The board_name partial-match behavior is also disclosed in the parameter description. Annotations already indicate destructive and idempotent behavior, so the description adds non-obvious context without contradicting them.
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 brief and front-loads the core action, then lists parameters. It avoids unnecessary fluff, though it could be slightly more structured with clear sections; however, every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the essential behavior (delete with no issue cascade) and parameter semantics. The annotations provide safety context, and an output schema exists. It is sufficiently complete for an agent to select and call the tool, though it lacks example usage or caveats.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful semantics for each parameter: board_name supports partial match and instance is optional. This compensates for the schema's lack of documentation, giving an agent enough to invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Delete an agile board') and adds an important qualifier that issues are not deleted, clearly distinguishing it from delete_issue. It is immediately obvious what the tool does and how it differs from related deletion 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, such as delete_issue or update_agile_board. There are no prerequisites, context, or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as destructive (destructiveHint=true) and non-read-only, so the description doesn't need to repeat that. It adds valuable context by stating 'Returns text for restoration', which tells the agent the deletion is reversible/recoverable. It also clarifies the 'instance' parameter is optional.
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 concise, with a clear first sentence and a compact arguments list. It avoids redundant phrases and front-loads the primary action. The inclusion of parameter descriptions is justified given the sparse schema, though it could be tightened.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but noted) and annotations that already cover safety (destructive, non-read-only), the description provides the key behavioral detail (restoration text) and parameter clarification. It lacks usage guidance relative to siblings, but for a straightforward deletion tool with good annotations, this is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a brief but meaningful explanation for each parameter: article_id can be an article ID or database ID, comment_id is the comment ID, and instance is optional. While it lacks details on format or defaults, it gives the essential semantics needed to invoke the tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the specific verb 'Delete' and the resource 'article comment', which clearly distinguishes it from sibling tools like delete_comment (which likely targets issue comments) and aligns with delete_article_comment's name. It also notes the return value for restoration, adding 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 such as delete_comment or update_article_comment. The description does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as destructive (destructiveHint=true). The description adds significant context beyond the annotations by stating that the deleted text is returned for restoration, which informs the agent about reversibility. While it doesn't discuss permissions or side effects, this extra detail is useful and consistent with the annotations.
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 compact and front-loaded with the core action, followed by the return behavior and parameter explanations. Every sentence contributes value without redundancy or filler. It is efficient and scannable.
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?
With an output schema present, return values are already covered. The description covers the essential purpose and parameters, but lacks broader context such as typical use cases, prerequisite conditions, or implications of deletion beyond restoration text. For a destructive operation, a note about irreversibility (even with text) would improve completeness, though not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It adds meaning beyond the schema by clarifying that issue_id can be an ID or URL, and that instance is optional. These details are not present in the schema and help the agent pass correct values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Delete' with a resource 'comment from a YouTrack issue', and additionally notes it returns the deleted text for restoration. This clearly distinguishes it from sibling tools like delete_article_comment or delete_work_item, making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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, nor does it mention any conditions that would make another tool preferable. The only context is the parameter list, which implies usage but does not explicitly instruct. This is a clear gap for an AI agent deciding between delete_comment and other deletion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, so the main risk is known. The description adds valuable behavior: 'Returns deleted details for restoration'—disclosing that the deleted data is returned and can be used to restore. It does not explain side effects or permissions, but the recovery aspect is a meaningful addition beyond the annotations.
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 functional sentences followed by a parameter list. No fluff, no redundancy. Front-loads the core purpose before the technical args. Every word earns its place.
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 destructive tool, the description covers the essential: what is deleted and that details are returned for recovery. However, it omits when to use or avoid, potential permissions required, and the exact impact scope (does it cascade to related data?). An output schema exists, which may help, but the description alone leaves several operational gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by listing each parameter with a concise meaning: 'issue_id: Issue ID or URL' clarifies the accepted format; 'instance: YouTrack instance (optional)' marks optionality. This is more informative than the bare schema titles, though examples or further constraints are absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Delete a work item.' This clearly distinguishes it from sibling tools like delete_issue or delete_comment by explicitly naming the resource type. The scope is unambiguous and directly aligned with the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or compare with related tools like update_work_item or add_work_item. The usage context is only implicit in the name and brief description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'full content' detail and parameter defaults (include_comments default True), but does not disclose any additional behaviors like response size limits, permission requirements, or error conditions. No contradiction with annotations.
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 concise and well-structured: a one-line summary followed by an Args list. Every sentence is informative with no filler, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with a rich output schema and strong annotations, the description is nearly complete. It covers parameters and purpose, but misses usage context compared to sibling tools (e.g., when to search vs. get) and any edge cases or performance notes. Given the low complexity, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It explicitly explains each parameter: article_id as 'Article ID or database ID', include_comments as 'Include comments' with default, and instance as 'YouTrack instance (optional)'. This gives meaningful semantics beyond the schema's bare types and defaults.
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 'Get a Knowledge Base article with full content', using a specific verb and resource. It distinguishes itself from sibling tools like search_articles by implying direct retrieval of a single article, and from create/update/delete article tools by being read-only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as search_articles or list_saved_searches. It does not mention exclusions or typical scenarios, leaving the agent to infer from the name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavior about response formats, including the default markdown view and the structured JSON variant containing instance_url.
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 main purpose is front-loaded and the format guidance is compact. The Args section partly duplicates the schema, but it adds behavioral meaning that the schema lacks, so the redundancy is minor.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only identity tool with an output schema and strong annotations, the description covers the essential behavior and parameter choices. The only notable gap is the lack of detail about the instance parameter, but the tool remains confidently invocable.
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 provides no parameter descriptions, so the description must compensate. It thoroughly explains the format parameter's values and output effects, but the instance parameter is only described as an optional instance with no guidance on accepted values 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 action: get the currently authenticated YouTrack user. The 'currently authenticated' qualifier differentiates it from user-search or mention-related tools, though it does not explicitly name sibling alternatives.
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?
It explains when to choose each format: JSON for downstream issue hyperlink construction and report markdown as the chat-friendly default. It does not explicitly discuss alternative tools, but the narrow purpose and format guidance provide clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, which cover safety. The description adds minimal contextual detail about return content ('with their sections') but does not disclose other behaviors like pagination or ordering. Since annotations carry the safety burden, this meets the baseline but doesn't go beyond.
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?
A single, clear sentence that states the action, resource, and return content with no wasted words. It is appropriately sized and immediately conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only list operation with a full output schema, the description is sufficient. No prerequisites, additional context, or behavioral caveats are needed beyond what annotations provide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially complete. The description need not explain parameters; per the rubric, a zero-parameter tool gets a baseline of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with a clear resource ('all available issue templates') and conveys the output includes 'their sections'. It is clearly distinct from sibling tools like create_issue_from_template, which creates an issue from a template, and list_tags, which lists tags.
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 create_issue_from_template or get_issue. The description implies a simple read-only listing, but there is no explicit statement of suitable scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true, which cover the main behavioral traits. The description adds no extra context about what happens if the link does not exist or whether this is reversible. With annotations carrying the safety profile, the description does not expand beyond them, but also does not contradict them.
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 concise and well-structured as an Args list. Every sentence adds value, with no filler or redundant information. The parameters are clearly mapped to their roles.
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?
While the description covers the essential parameters and behavior, it doesn't mention the output format or any special considerations for this destructive operation (e.g., permission requirements, side effects). The existing annotations cover safety but not operational context. For a mutating tool, a brief note on when removal is allowed or what happens on a nonexistent link would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful semantic additions: issue_id is described as 'Source issue ID or URL', target_id as 'Target issue ID or URL', and link_type as 'Relation type to remove' with a default. This goes beyond the raw schema and helps an agent construct correct arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Remove a link between two issues.' This clearly differentiates it from add_issue_link and other issue operations, leaving no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implicitly clear from the description and parameter names (e.g., linking two issues), but no explicit guidance is given on when to use this tool versus alternatives like add_issue_link or get_issue_links. The 'Remove' verb implies the use case, but the description doesn't articulate exclusions or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavior: partial match on name, default max_results of 50, and optional instance. It does not disclose exact output format (though an output schema exists) or empty-result/error behavior, so extra context is modest.
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 compact: a one-sentence purpose followed by a clear Args list. Every part earns its place, the main action is front-loaded, and there is no unnecessary detail. It is appropriately sized for a three-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only, idempotent tool with an output schema, the description covers the invocation essentials: partial-match name, default max_results, and optional instance. It does not mention how to discover saved search names via list_saved_searches or what happens if no search matches, leaving a small gap for an unfamiliar caller, but overall it is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining all three parameters in the Args block: name (partial match), max_results (default 50), and instance (optional). This directly helps an agent supply correct values and is exactly what the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Run') and resource ('saved search'), and clarifies the outcome ('return matching issues'). It distinguishes from raw query tools like search_issues because it operates on a named saved search. However, it does not explicitly compare with sibling tools, so it misses the highest level of differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for running pre-configured saved searches rather than ad-hoc queries, and notes partial match on the name. However, there is no explicit 'when to use vs. search_issues' or 'when not to use' guidance, nor a pointer to list_saved_searches for discovering available names. It is a functional statement rather than a clear decision guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the operation is not read-only, is idempotent, and non-destructive. The description adds meaningful context by stating 'Returns previous text for rollback,' which tells the agent about the undo capability beyond what annotations convey. It does not go into permissions or side effects, but this extra detail is valuable.
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 compact and front-loaded with the core purpose and key behavior ('Returns previous text for rollback') before listing parameters. Every sentence earns its place; the Args list is clear and indented. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For its complexity, the description is nearly complete: it states the action, the object, the return value, and clarifies all parameters. The main gap is not explicitly distinguishing between article comments and issue comments, which could confuse agents given sibling tools like update_comment. However, the description does mention 'article comment,' and the output schema exists, so this is a minor omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully. Each parameter receives an explanation beyond its name: article_id accepts an ID or database ID, text is in markdown, instance is optional, and comment_id is clearly labeled. This adds significant meaning for correct 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 a specific action ('update') and resource ('an article comment'). It does not explicitly contrast with sibling tools like update_comment or add_article_comment, so it lacks the explicit differentiation needed for a top score, but the resource is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus updating an issue comment (update_comment) or adding a new comment (add_article_comment). The description does not mention any prerequisites, exclusions, or alternative tools, leaving the agent to infer context solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no extra behavioral context such as URL expiry, authentication requirements, or whether partial match is case-sensitive. It doesn't contradict annotations, but it also doesn't enrich them, leaving it at a baseline 3.
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 compact and front-loaded. The one-line purpose is immediately followed by a clear Args section. No filler or redundant text. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with rich annotations and an output schema, the description covers the essential input semantics and tool purpose. It does not mention return value details, but the output schema exists to handle that. A brief note about URL validity or error cases would improve completeness, but overall the agent has enough to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It explicitly explains each parameter: issue_id can be ID or URL, attachment_name is a partial match, and instance is optional. This adds meaningful semantics beyond the bare schema field names, though it could be more detailed (e.g., example values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get the download URL for a specific attachment on an issue.' This clearly distinguishes it from siblings like list_attachments (which lists attachments) and other issue-related tools. The purpose is explicit and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does and lists parameter meanings, which implicitly conveys when to use it. However, it does not explicitly contrast with alternatives like list_attachments or explain when this tool should be preferred over other attachment-related tools. No exclusions or scenario guidance provided, so it falls at the 'implied usage' level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's non-mutating and repeatable nature is known. The description adds the category labels as output context, which is nice, but does not disclose any further behavioral traits (e.g., error conditions, auth requirements). Since the annotations cover the safety profile, 3 is fair.
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 concise and well-structured: a single purpose sentence followed by a clear arg list. No unnecessary filler, and the core intent is front-loaded. Everything earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (has output schema: true), so the description need not explain the return value format. It covers the purpose, parameters, and categorization semantics, which combined with metadata and schema is sufficient for an agent to call it correctly. The only minor gap is the lack of explicit return description, but that is covered by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% coverage, so the description must explain parameters. It does: issue_id is 'Root issue ID or URL', deadline is 'Deadline date for context (optional)', instance is 'YouTrack instance (optional)'. This is sufficient to use the parameters correctly, though the exact format or constraints (e.g., deadLine string format) are not given. That's a minor gap but overall clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear, specific verb and resource: 'Analyze what breaks if an issue slips past a deadline' and describes the output categorization (BLOCKED, AT RISK, DONE). This distinguishes it from sibling tools like get_at_risk_issues (which likely lists issues) and deadline_scorecard (which provides an overall metric), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (analyze a single issue's risk of slipping) but does not explicitly state when to choose this tool over alternatives, nor does it mention when not to use it. The context is clear from the description and name, but the guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive, so the description need not repeat safety traits. The description adds minimal behavioral context—only that all linked issues are returned for a specific issue—without detailing link directionality, supported link types, or any potential variability in results. This is adequate but not enriched beyond the annotations.
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 compact: a single purpose sentence followed by a minimal argument list. Every line earns its place, with no filler, and the key information is front-loaded in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with an output schema available, the description covers what is needed: the action, the target issue, and parameter semantics. It does not explain what kinds of linked issues are returned, but that is likely handled by the output schema, so the description remains reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description takes on the responsibility of explaining parameters. It clearly states that issue_id can be an Issue ID or URL and marks instance as an optional YouTrack instance, adding meaning beyond the raw schema types.
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 opens with the specific action 'Get all linked issues for an issue', clearly identifying the verb, resource, and object. This distinguishes it from sibling tools like add_issue_link, remove_issue_link, and get_issue by focusing on the read-only retrieval of linked issues rather than modification or single-issue details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to prefer this over alternatives such as get_issue, search_issues, or add_issue_link. However, the tool name and brief purpose imply its use when linked issues are needed, so the usage context is inferred rather than clearly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint: true, destructiveHint: false) already establish safety. The description adds behavioral detail beyond the schema by stating ranking by priority score and the 'per product when grouped' behavior for limit, which is not present in the schema. It discloses the grouping and exclusion semantics, providing useful 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 followed by a structured Args list. No unnecessary words or repetition. Every token contributes to the explanation, making it efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to explain return values. It covers all parameters and the core ranking behavior. However, it omits any mention of how the priority score is derived or potential rate limits, which might be useful but are not essential for a read-only, idempotent tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of parameter meaning. The Args block explains all 6 parameters, including defaults and formats (e.g., 'Comma-separated active states', 'regex to exclude'). This sufficiently compensates for the schema's lack of descriptions, though some entries are terse.
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 a specific verb ('Get'), resource ('top active issues'), and criteria ('ranked by priority score'), which distinguishes it from siblings like get_issues or search_issues. It leaves no ambiguity about the tool's core function.
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 explicit guidance is given on when to use this tool versus alternatives. The description does not mention exclusions or suggest when another tool (e.g., search_issues or get_top_blocked_issues) would be more appropriate. The intent is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, but the description adds a meaningful behavioral consequence: 'Returns details for restoration.' This tells the user that deletion can be undone if the returned details are retained, an important safety nuance not captured by the annotations alone. This value-added context earns a score above the baseline.
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 succinct, with a single-sentence purpose statement followed by a compact parameter list. It avoids excessive verbiage and no filler. The structure is front-loaded with the main function before the parameters, making it easy to skim. A small deduction for the slightly verbose parameter list formatting, which is acceptable but not perfect.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and the short parameter list, the description adequately covers the essential aspects: action, objects, and a note about return value. It doesn't mention error handling or permission requirements, but those are often expected to be outside the description scope if annotations/schema exist. The article knowledge base context is clear from the name and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It does so for both parameters: 'article_id: Article ID or database ID' clarifies the accepted value types, and 'instance: YouTrack instance (optional)' confirms the parameter's optionality. This is more than the schema shows, though not exhaustive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('Delete a Knowledge Base article'), making the tool's purpose unmistakable. It also adds a key detail—'Returns details for restoration'—which distinguishes it from other delete/functions among the siblings. Compared to delete_article_comment or delete_issue, this is clearly the one for KB articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates the action (deleting a KB article) but does not explicitly state when to choose this tool over, say, update_article or delete_issue. No alternatives are named and no conditions are given, so an agent must infer usage from context rather than from clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true, but the description adds key context: the default is a soft delete that marks the issue as Obsolete, and permanent=True is irreversible. This goes beyond the structured data and is not duplicative.
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 compact and well-structured: one sentence for the main action, one sentence for the critical default/irreversible warning, then a concise Args list. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the annotations and the existence of an output schema, the description provides all essential invocation details: what the tool does, how parameters behave, and the destructive implications. An agent can safely call the tool with the information provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain all three parameters. It does explain issue_id as 'ID or URL', permanent with its default and irreversible nature, and instance as optional. This is clear, though slightly terse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Delete a YouTrack issue' which is a specific verb and resource, unambiguous from siblings like delete_comment or delete_work_item. It also clarifies the soft-delete vs permanent delete distinction, adding precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives such as transition_issue to an Obsolete state or rollback_issue. It doesn't mention when not to use it or suggest better alternatives for specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds no further behavioral context beyond stating the operation itself, such as response format or authentication requirements, so it contributes minimal additional value.
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 two lines: a clear one-line summary followed by a concise parameter breakdown. It is front-loaded with the core purpose and contains no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, with only two parameters and comprehensive annotations. The output schema exists (though not shown), so return values need not be explained. The main gap is the lack of explicit differentiation from similar list-type tools, but overall the description is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite the schema_description_coverage of 0%, the description explicitly explains both parameters: 'name' can be a board name, ID, or URL, and 'instance' is an optional YouTrack instance. This fully compensates for the missing schema descriptions and adds meaning beyond the raw type declarations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'agile board details' and specifies three identifier types (name, ID, or URL). This clearly distinguishes it from siblings like get_agiles (which lists boards) and get_sprint_board (which is sprint-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: use this tool when you have a specific board name, ID, or URL to retrieve details. However, it does not explicitly state when to use an alternative (e.g., get_agiles for listing all boards) or provide exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context by stating the summary is 'compact' (implying it may not include every detail) and listing the specific change types included, but it does not disclose deeper behaviors like pagination or format constraints.
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 lean and well-structured: the purpose appears in the first sentence, and the argument list follows immediately. There is no redundant wording; every sentence adds information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with an output schema (not shown), the description covers the essential purpose and parameters. It is complete enough for an agent to invoke correctly; the only minor gap is the lack of explicit guidance on how this relates to similar change-related tools (e.g., get_issue_history).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description carries full responsibility for parameter meaning. It does so exceptionally: issue_id is clarified as 'Issue ID or URL', since is explained as an 'ISO date filter' with an example, and instance is noted as optional. This goes far beyond the bare schema and fully compensates for the lack of property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a specific verb ('Get') and resource ('compact summary of issue changes'), then enumerates exactly what it covers: state transitions, comments, time logged. This clearly distinguishes it from siblings like get_issue (full issue data) or get_issue_history (raw history).
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 purpose: an agent can infer that this tool is for obtaining an overview of issue changes. However, there is no explicit guidance on when to prefer this over related tools such as get_issue_history or poll_changes, nor any mention of alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnly=false and destructive=false, but the description adds valuable behavioral context: 'Returns previous values for rollback' and the 'keep' semantics (0 for duration, empty strings for date/description) clarify partial-update behavior. This goes beyond what annotations alone convey.
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 succinct one-line summary followed by a clearly indented Args block. Each line adds semantic value without redundancy, and the structure makes scanning trivial. No word is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to explain return values, and it covers all parameter meanings well. The only gaps are the absence of usage comparison to sibling tools and a lack of detail on valid 'instance' values, but the core operation is adequately described for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It explains every parameter: issue_id accepts an ID or URL, date specifies YYYY-MM-DD format, and duration/date/description all document the 'keep' interpretation of default values. This is a thorough, meaningful expansion over the bare schema.
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 opens with 'Update a work item,' clearly stating the action and resource. This is unambiguous and distinguishes the tool from siblings like add_work_item, delete_work_item, and get_work_items based on the verb alone.
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 about when to use this tool versus alternatives. It neither mentions sibling work-item tools nor states any exclusions or prerequisites, leaving the agent to infer usage from the tool name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare this as a read-only, idempotent non-destructive operation, so the description's main behavioral additions are valuable: crediting time to the work-item author rather than assignee, and keying users by login to avoid display-name collisions. These nuances go beyond what annotations provide and materially affect how results are interpreted.
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 well-structured: a concise opening statement, a short clarifying paragraph about grouping semantics, and a clearly formatted argument list. Every sentence adds useful information and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only report tool with an output schema and five optional parameters, the description covers all necessary context: aggregation basis, calendar month, group key semantics, defaults, and input formats. The presence of an output schema means return values do not need extra explanation, so the description is effectively complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden for parameter meaning. It compensates thoroughly with an Args section explaining each parameter: instance auto-detection, comma-separated projects, default year/month, and valid group_by values. This gives the agent everything needed to populate arguments correctly.
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 produces a monthly time report aggregated by the user who logged the time. It distinguishes itself by explicitly noting grouping is by work-item author, not issue assignee, which helps differentiate from other reporting tools. However, it does not name any sibling tool directly, so differentiation from similar reports like user_time_summary is only implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about what the report does and explains the grouping semantics, which helps the agent understand when this tool is appropriate. It does not explicitly state when not to use it or name alternatives, but the defaults and argument explanations imply typical usage. No direct exclusion or alternative comparison is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, which cover the safety profile. The description adds valuable behavioral context beyond those: it discloses that departments are 'auto-detected from project shortnames using generic role-based patterns', explains the semantics of thresholds (stale_days and avg_window_days), mentions how subtasks are included, and caps issues fetched (max_issues). This adds the behavioral nuance an agent needs for accurate invocation.
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 compact: a one-sentence overview followed by the Args list with per-parameter explanations. It is front-loaded with the primary purpose and the behaviors follow logically. The formatting is clear and the content earns its place; the 'Args:' section is a little long but necessary for parameter semantics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the critical operational details for a moderately complex tool with 6 parameters and output schema present. It explains behavior (detection, thresholds, subtask inclusion, cap) and parameter usage. The exact output format is delegated to the output schema, but the description could have briefly mentioned return types or pagination/analytics aggregate vs per-issue detail; however, the output schema presumably fills that. Overall it is nearly complete, with only a minor omission of an explicit mention that the journey is per issue versus aggregated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It does so thoroughly: each parameter is described with semantic meaning and intended usage (e.g., query as a YouTrack selector, stale_days for flagging current station, avg_window_days for rolling averages, follow_subtasks for hierarchy inclusion, max_issues cap, and an optional instance). The inclusion of a query example adds practical clarity far beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Track cross-department handoffs' followed by concrete outputs ('bottlenecks, dept load, avg transit times'). It clearly distinguishes itself from siblings like get_handoff_snapshot and get_stuck_handoffs by building 'a chronological journey of dept changes' per issue, which is a unique, specific purpose. An agent can select it without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, nor does it give exclusion conditions. However, the intent is decently implied by the purpose statement and the parameter example ('e.g. project: PROJ #Unresolved'), suggesting it is used for analytical cross-department journey reporting. No explicit 'when not to use' guidance is present, leaving this at an adequate but not strong level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide safety hints (readOnlyHint false, destructiveHint false, idempotentHint true). The description adds valuable behavior beyond that: it states the tool returns previous values for rollback and explains the empty-parameter semantics ('empty = keep' or 'empty = skip'), which is meaningful for an agent. It falls just short of full transparency by not addressing error cases or required permissions.
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 opens with a one-sentence purpose and then uses a clear, consistent Args list. Every line adds semantic value; there is no fluff or repetition. The structure makes parameter semantics easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 10 parameters and no schema descriptions, the description covers the purpose, all parameter semantics, return behavior (previous values for rollback), and empty-value conventions. An output schema exists to describe return structure, so the description is complete enough for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It compensates excellently by explaining each parameter's meaning and the special empty behavior for every optional field, plus providing a concrete command example. This level of detail lets an agent construct calls correctly without needing hidden knowledge.
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 'Update fields of a YouTrack issue' with a specific verb and resource, and enumerates which fields are updatable. It does not explicitly distinguish from sibling tools like transition_issue or update_work_item, but the focus on issue fields is reasonably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context for use is implied by 'Update fields of a YouTrack issue' — an agent can infer it is for modifying issue attributes. However, there is no explicit when-to-use vs alternatives, no exclusions, and no mention of using transition_issue for state workflows, leaving some selection ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context: it explains that a batch tag enables rollback, describes how preserve_original modifies the issue content (appends original below a delimiter), and notes that the summary is still replaced. No contradiction with 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 moderately sized but every sentence contributes useful information, including the block format and parameter explanations. The critical purpose is front-loaded. Slight redundancy in the preserve_original explanation could be tightened, but overall it is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 params, no schema coverage), the description provides a complete picture: it explains the input format, rollback mechanism, bilingual behavior, delimiter, and optional instance. An output schema exists, so return values need no description. The context is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates. It explains the format of the translations parameter, clarifies batch_tag is auto-generated if empty, describes the preserve_original behavior in detail, gives the delimiter default, and marks instance as optional. Every parameter is given meaningful semantic context beyond the raw schema.
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 begins with a specific verb and resource: 'Apply translated text to YouTrack issues.' It clearly distinguishes this from sibling tools like get_issues_for_translation or update_issue by targeting the translation application action. The format specification further reinforces the specific scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for applying translations and mentions rollback tagging, but it does not explicitly state when to use this tool versus alternatives like update_issue or bulk_update_execute. It lacks explicit exclusions or conditions that would help an agent decide between this and similar write operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read-only, non-idempotent, and non-destructive behavior. The description adds useful context about using the command parameter to set required custom fields at creation time, which is a behavioral nuance beyond schema annotations. No contradictions are present.
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 front-loaded with the core purpose, followed by a single purposeful tip about command, and a well-organized Args list. Every sentence carries necessary information with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool, the description covers purpose, key parameters, and the special behavior of the command parameter. Output schema exists, so return values are not missing. It does not mention potential prerequisites (e.g., project existence) or side effects, but annotations and schema cover the remaining critical context. Slight room for improvement in noting when a template might be preferred.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description provides concise explanations for every parameter (project, summary, description, product, command, instance) and gives an example for command. This fully compensates for the schema gap and greatly aids correct invocation.
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 'Create a new issue in a YouTrack project', which is a specific verb and resource. It distinguishes from update_issue and transition_issue by focusing on creation. The additional note about using the command for custom fields reinforces the creation-time behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the verb 'Create' and the target resource. However, it does not explicitly mention alternatives like create_issue_from_template when a template should be used, nor does it state when not to use this tool. Thus the guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds the behavioral detail of how the graph is constructed (via links, product overlap, mentions), but does not disclose any further behavior like result size, pagination, or performance implications. This is adequate but not rich.
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 concise: one sentence stating the purpose followed by a compact Args list. No redundant or filler content. The core functionality is front-loaded, and the parameter details are direct and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a graph-building read tool with strong annotations and an output schema, the description covers the essential inputs and method. It lacks a note about what the returned graph structure looks like, but the output schema likely handles that. The parameter meanings are fully specified, so an agent can invoke the tool without ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explicitly explains all three parameters: issue_id (Root issue ID or URL), depth (Link levels to follow, default 2), and instance (YouTrack instance, optional). This fully compensates for the schema's lack of descriptions, giving an agent everything needed to fill parameters correctly.
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 starts with 'Build a cross-product dependency graph from an issue', which specifies a concrete action and outcome. It then names the three mechanisms (links, product overlap, mentions), distinguishing it from related tools like get_issue_links or get_roadmap. This is a clear, specific purpose.
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 clearly indicates this tool is used for building a dependency graph from a given issue, implying a read/analysis scenario. It does not explicitly mention when not to use it or list alternative tools, but the context is clear enough for an agent to infer appropriate use versus simpler link-retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive). The description adds only a hint about the nature of returned data (required status and available values) but no additional behavioral traits such as authentication or rate limits. Since annotations carry the burden, a baseline of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the main purpose is in the first sentence, followed by usage guidance and parameter explanations. No wasted words, and each section earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the presence of an output schema, and annotations covering safety, the description provides everything needed to call it correctly: what it does, when to use it, and what the parameters mean. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description explicitly explains both parameters: 'project' as a project short name and 'instance' as an optional YouTrack instance. This compensates well for the missing schema descriptions, though it could add format or default details.
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 lists custom fields for a project, specifies the resource (custom fields) and includes what is returned (required status and available values). It effectively distinguishes this from sibling tools like create_issue by positioning it as a discovery tool.
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?
Explicitly instructs to use this before create_issue to discover required fields and valid values, giving clear contextual timing. It does not mention when not to use it or alternatives, but the primary use case is well defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide read-only, idempotent, and non-destructive hints. The description adds transparency by disclosing the default file-writing side effect (managers.suggested.json) and explaining the write parameter's role in controlling persistence. It also explains the auto-exclusion of PMs, which affects output. No contradiction with annotations is present, since the write is a local output artifact, not a mutation of the YouTrack system.
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 concise and well-structured. It opens with a one-sentence summary, adds a brief algorithmic explanation, and then lists parameters in a clean Args block. Every sentence adds value; there is no redundancy, and the structure makes scanning easy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that all parameters are optional with defaults, an output schema exists, and annotations cover safety, the description is nearly complete. It covers the algorithm, parameter semantics, and output side-effects. Minor gaps include not stating permission requirements for reading all accessible projects, the potential performance impact of large lookback windows, or behavior when no candidates are found. These are not critical for a competent agent calling the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no parameter descriptions (0% coverage), so the description is the sole source of semantics. It clearly explains all four parameters: lookback_days as activity window, projects as comma-separated shortnames with empty meaning all accessible, write as whether to persist or just print, and instance as optional YouTrack instance. This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise function with a clear verb and resource: 'Bootstrap a manager mapping from recent YouTrack activity.' It also breaks down the heuristic approach (detecting PMs, scoring remaining candidates), making the purpose unambiguous. No sibling tool offers this exact capability, so it is well differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when manager mappings need to be inferred from activity data, but it never explicitly says when to use it or when to avoid it. There is no mention of alternative tools (e.g., get_team_dashboard) or exclusions for cases where manager data is already available. Usage context is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering the core safety profile. The description adds minimal behavioral context beyond that, only stating the function itself without additional details like permission requirements or side effects. Given annotations are present, a score of 3 is appropriate — the description neither contradicts nor significantly enriches the behavioral picture.
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 concise but slightly verbose: it includes an args list that efficiently explains each parameter in one line, but the repetition of 'empty = keep' and 'None = keep' across multiple parameters adds a little redundancy. It is front‑loaded with the core purpose and the Args are structured clearly. Not overlong, but not as tight as it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is moderately complex with 7 parameters and 2 required ones, and the schema provides no descriptions. The description covers every parameter's semantics including edge cases. An output schema is confirmed to exist, so return values need not be explained. There is no missing information an agent would need to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It does so thoroughly: each parameter is annotated with its role, and the special semantics like 'empty = keep' and 'None = keep' are explicitly stated. Partial match behavior for board_name and sprint_name is also disclosed. This fully compensates for the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Update') and a specific resource ('existing sprint on an agile board'), clearly differentiating from the sibling tool 'create_sprint'. An agent can immediately understand the tool's purpose and scope.
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 clearly indicates it targets existing sprints ('Update an existing sprint'), implying it is not for creating new ones. However, it does not explicitly mention alternatives like 'create_sprint' or 'add_issues_to_sprint', nor does it state when to prefer this tool over them. The context is clear but no exclusions are listed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds valuable runtime behavior: the history-walk cost model for QA skip, the 'pattern matching' on decorated field names, and the fact that limit_per_category is ignored in JSON mode. This goes beyond what annotations convey.
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 longer than average but earns its length given 10 parameters. It front-loads the core action and category list, then gives behavioral context, then a cleanly labeled Args section. No repeated restating of parameter titles from the schema; each sentence adds semantic value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 10-parameter read-only tool with an output schema present, the description is nearly complete. It covers defaults, edge semantics (QA history verification, zero-cost when no QA field), output format differences, and aliases. An agent can confidently construct correct calls.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden. It explains every one of the 10 parameters with defaults and nuance (e.g., exclude_patterns is regex, category accepts aliases, format controls full-set behavior, instance is optional). This effectively compensates for the bare schema.
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 opens with a precise action and resource: 'Find at-risk issues' and immediately enumerates the distinct categories (overdue, qa_skipped, stalled, forgotten, unestimated, over estimate, ancient). This clearly distinguishes it from sibling search/reporting tools and gives an agent a concrete sense of what the tool computes.
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 explains detailed behavior for QA-skip detection, staleness thresholds, category filtering, and output formats. It doesn't explicitly contrast against alternatives like search_issues or get_issues, but it makes its own applicable context obvious (at-risk classification rather than general querying or listing). The 'Args' section also clarifies when JSON vs report output should be preferred ('programmatic consumers like a daily deadline bot').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint, so safety is covered. The description adds that it's a single API call, groups results by state, and highlights idle tickets, which is useful behavioral context. But it doesn't specify what happens when no projects are given beyond 'all accessible', or how states map to results.
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 compact and front-loads the core purpose, then uses a labeled Args block that is easy to scan. A slight deduction because the states default list is long and could be trimmed, but every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only snapshot with an output schema and clear sibling contrast, this is mostly complete. It could state that handoff values are YouTrack-specific or note the absence of pagination, but the core invocation knowledge is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must carry the meaning, and it does: projects, states, stale_days, active_within_days, and instance are all explained with defaults, formats (comma-separated), and special values. This fully compensates for the empty schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool takes a snapshot of tickets in handoff states, groups by state/dept, and contrasts it with track_cross_dept_journey. This gives a specific verb, resource, and scope that differentiates it from siblings like get_stuck_handoffs, search_issues, and track_cross_dept_journey.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly positions usage as a fast single-query view complementing the richer per-issue track_cross_dept_journey, and the argument docs give concrete guidance (e.g., active_within_days=14 for 'currently in flight'). This is strong when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, but the description adds valuable algorithmic detail: it scans only release/RC-titled tickets, orders in-flight releases, computes cadence based on lookback, and flags parked queues. This transparency goes beyond the basic safety profile and explains the tool's logic without contradiction.
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 front-loaded with a concise summary, then expands into a well-organized bulleted breakdown. Each sentence adds unique information, including the conditional ETA calculation and the parked-queue flag threshold. No redundancy or empty phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and the presence of an output schema, the description is complete. It covers scope, per-project behavior, computational method, and parameter meaning. An agent can confidently invoke it with defaults or custom parameters, and the output schema handles return-value details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), so the description carries full responsibility. It explains each parameter clearly: projects as comma-separated keys with blank meaning all, lookback_days as the shipped-release window with default 30, and instance as optional. This is comprehensive semantic guidance.
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 it scans release/RC-titled tickets across projects and reports in-flight releases, recent ships, cadence, and ETAs. It provides a specific scope and features that distinguish it from sibling reporting tools. The first line summarizes the resource and output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for release tracking but does not explicitly state when to use it over alternatives like get_roadmap or get_team_dashboard. There is no when-not-to-use or alternative guidance, leaving the choice to inference rather than direct instruction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is established. The description adds meaningful behavioral detail by specifying default filtering behavior (e.g., states empty = all unresolved, projects empty = all accessible), which goes beyond the annotations and helps the agent understand default behavior without invoking the 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 concise and well-structured. The one-line purpose statement is immediately followed by a clear parameter list in a consistent format. Every sentence and field earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, return format does not need explanation. All parameters are documented with defaults and empty-value behaviors, and the filtering scope is clear. For a read-only roadmap tool with full parameter coverage, nothing essential for a correct call is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args block fully compensates by explaining every parameter: projects, types, states, max_per_project, and instance, including defaults and the meaning of empty values. This gives the agent complete semantic understanding of each input.
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 a specific verb ('view') and resource ('cross-project roadmap'), and distinguishes it from sibling tools like get_team_dashboard or search_issues by emphasizing the roadmap view and filtering by type and state. This gives an agent a precise idea of what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied by the name and description ('cross-project roadmap view'), but there is no explicit guidance on when to choose this tool over alternatives, nor are any exclusions or alternative tool references provided. The agent must infer when a roadmap is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a non-obvious behavior: 'Returns previous text for rollback,' which goes beyond the annotations. Since annotations already mark it as a mutation (readOnlyHint=false) and non-destructive, the description adds useful context about the return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-line function summary, a note about the return value, and a compact parameter list. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple update tool with an output schema, the description fully covers all required inputs, the optional instance parameter, and the rollback behavior. No critical information is missing for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The Args section explains each parameter's meaning and format, including that issue_id can be an ID or URL, text is markdown, and instance is optional. This fully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('Update an existing comment') and adds distinguishing detail: it returns previous text for rollback. This clearly differentiates it from add_comment and delete_comment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: it modifies an existing comment, so it requires an existing comment ID. However, it does not explicitly state when to prefer this over alternatives or mention any exclusions, leaving the guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavior beyond this: parallel fetch across boards, output variability based on ids_only, and partial matching for board names. This extra context is helpful without contradicting annotations.
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 concise, front-loaded with the core purpose, and then follows a well-structured Args section. Every sentence serves a purpose without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main usage context, parameter semantics, and output formats. With annotations handling safety profile, the description is nearly complete. It might lack explicit edge-case handling (e.g., no active sprints), but overall it provides sufficient information for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, so the description fully compensates by explaining each parameter: boards (partial match, empty=all), exclude_states (comma-separated), ids_only (return format control), and instance (optional). This gives agents clear guidance on how to set each argument.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Collect issue IDs across current sprints of all boards'. It clearly distinguishes itself from sibling tools by focusing on sprint-based truth rather than state guessing. The purpose is immediately evident.
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 explicitly says when to use it: 'Use for "what's actually in flight" across the org — sprint-based truth, not state guessing' and mentions it feeds into translation/audit/digest flows. It provides clear usage context, though it doesn't explicitly name alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide idempotentHint=true and destructiveHint=false. The description adds meaningful behavioral context: it returns previous values for rollback, and empty parameters preserve existing values. This goes beyond the schema and annotations without contradicting them.
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 compact: one informative first sentence and a structured args list. Every line provides necessary information with no fluff or redundancy. The 'empty = keep' phrasing is efficient and unambiguous.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 4-parameter update tool with an output schema, the description covers all parameters and the rollback return behavior. It omits error scenarios, permissions, and explicit alternative routing, but annotations and schema fill many gaps. Overall it is complete enough for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden for parameter semantics. It clearly explains all four parameters: article_id as 'Article ID or database ID', summary as 'New title (empty = keep)', content with the same keep behavior, and instance as optional. This fully compensates for the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb 'Update' and resource 'Knowledge Base article', clearly distinguishing it from siblings like create_article, delete_article, and get_article. It also adds a distinguishing detail: 'Returns previous values for rollback', which clarifies the tool's unique purpose.
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 implicitly guides usage by explaining the 'empty = keep' semantics for summary and content, and marking instance as optional. However, it does not explicitly contrast with alternatives (e.g., when to use create_article instead of update_article) or state prerequisites like the article already existing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral context by specifying the exact three-way diff outcome (matched, missing-from-list, no-longer-matching) and explaining each category. It does not mention auth or rate limits, but those are less critical given the read-only annotations.
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 front-loaded with the core diff operation, followed by the result categories and then concise parameter explanations. Every sentence earns its place, and the structure is 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.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with three parameters and an output schema available, the description is complete: it explains what the tool does, what inputs it needs, what outputs to expect, and when it is useful. Nothing required for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully carries the parameter-documentation burden. It does so well: known_ids is explained as comma-separated issue IDs with an example, query is explained as a YouTrack query with an example, and instance is marked optional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb, 'Diff', and clearly names the two inputs: a known issue list and a YouTrack query. It further enumerates the three result categories, which makes the tool's purpose unmistakable and distinguishes it from retrieval-focused siblings like search_issues or count_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 'Useful for finding tasks you're not tracking, or items in your list that are stale' sentence provides clear context for when to choose this tool. It does not explicitly name sibling alternatives or state when not to use it, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable behavioral context by defining per-issue versus cumulative compliance, the meaning of missed_after_extension, and how strict mode affects approval counting. This goes beyond the annotations and clarifies edge-case semantics.
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 opens with a concise summary, then provides a clear list of parameter definitions with examples. Every sentence adds value; no filler or redundancy. The structure is easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only analytical tool with six parameters and an output schema, the description covers the tool's purpose, calculation semantics, and all parameter meanings. No critical information is missing, and the presence of an output schema means return values need not be restated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema description coverage is 0%, the description thoroughly explains every parameter: quarter format and default, user filtering, projects as comma-separated shortnames, strict mode meaning, exclude_standups, and instance optionality. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function as a per-assignee deadline compliance rollup for a calendar quarter. It distinguishes itself from cumulative tracking by specifying per-issue compliance and explaining the 'missed_after_extension' condition. This is specific enough to differentiate from sibling tools like get_deadline_impact.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for deadline compliance reporting but does not explicitly state when to use this tool versus alternatives. It does not mention any exclusions or conditions that would route an agent away from this tool. The parameter explanations provide context but not comparative usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses that the operation is 'cheap', requires no auth state, and can return either plain text or JSON. This adds actionable behavioral context that the annotations do not carry.
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 tightly written: the core purpose is the first sentence, followed by a short rationale, then a cleanly formatted args block. Every sentence earns its place and there is no extraneous filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only getter, the description covers the operation's purpose, use case, and parameter semantics sufficiently. An output schema is present, so return values need not be fully spelled out, and the few lingering unknowns (e.g., how an empty instance is resolved) are minor for a tool this simple.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must explain the parameters. It defines format values ('report' vs 'json') and notes they are optional; instance is only described as 'YouTrack instance (optional)', which is sparse but still supplies a minimal meaning absent from the schema. More detail about instance format (name/ID/URL) would lift this, so 4 is appropriate.
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 opens with a specific action and object: 'Return the base URL of the configured YouTrack instance.' This unambiguous verb+resource pairing makes the tool's purpose immediately clear and distinguishes it from all sibling tools, none of which return an instance URL.
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?
It states a concrete use case — downstream renderers that need <base>/issue/<ID> links — and notes it avoids a who-am-I call, helping an agent decide when a lightweight probe suffices. However, it names no alternative tools or conditions for not using this tool, so it falls short of an explicit when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, lowering the bar. The description adds valuable behavior details: how exclude_translated works via tags and bilingual structure detection, and how the delimiter signals already-translated state. This goes beyond the annotations to explain internal filtering logic.
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 well-structured, leading with a single-purpose sentence followed by an organized Args block. Each line adds essential information without redundancy. It is 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.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description needn't explain return values. It covers all parameter semantics, default behaviors, and the collaborative workflow with apply_translations. No critical information for correct invocation appears missing, making the description complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the Args section thoroughly explains every parameter: query, include_comments, max_results, exclude_translated, delimiter, and instance. It provides defaults, semantic meaning, and cross-dependencies (e.g., delimiter must match apply_translations), fully compensating for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches issues with non-ASCII text specifically for translation, using the verb 'Fetch' and a specific resource scope. This distinguishes it from generic issue tools like get_issues or search_issues, making its purpose unmistakable.
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 explicitly instructs to 'Call apply_translations with results,' providing a clear usage context and workflow. While it doesn't explicitly list alternatives or exclusion criteria, the targeted purpose effectively implies when to use this tool over general issue fetchers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds significant behavioral detail beyond that: parallel execution via asyncio.gather, graceful degradation for failed boards, an org-wide aggregate in the output, and default limit differences from the single-board version. This is exactly the kind of context that helps an agent predict side effects and performance.
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 longer than average but every sentence earns its place: the opening two sentences explain the core behavior and performance advantage, the middle covers failure handling and output structure, and the Args list is a dense, well-parsed reference. No fluff remains, though it could be tightened slightly by moving the Args block into a more compact form.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, aggregated reporting tool, the description covers everything an agent needs: what it does, how it handles failures, what the output contains (aggregate + per-board summaries), the output formats (report/json), and the exact semantics of every parameter. The existing output schema and annotations cover the rest. No critical gap is apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of parameter explanation. It does so comprehensively: every parameter (boards, horizon_days, lookback_days, limit, format, max_idle_days, max_overdue_days, instance) is described with its purpose, default, and special behaviors (e.g., 'Pass 0 to disable'). This far exceeds the bare schema and enables correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb 'get' with a clear resource 'multi_team_pulse' and immediately distinguishes it from sibling get_team_pulse by noting it operates in parallel across multiple boards with an aggregated org-wide view. This is a precise, non-tautological purpose that an agent can act on.
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 explicitly references get_team_pulse as the single-board counterpart and explains the parallel fan-out, making it clear this is the multi-board variant. It also notes that failed boards are listed but do not abort the operation, giving practical context. However, it does not explicitly state 'use this when you need multiple boards' as a hard rule, so it stops short of a full when/when-not guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint=true, readOnlyHint=false), the description adds critical behavioral context: it brands the operation as 'DESTRUCTIVE', mandates a preview step, and discloses that the batch is tagged for rollback. This gives the agent concrete risk-awareness and recovery expectations not present in the schema.
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 compact and front-loaded with the most safety-critical warning. It then lists parameters in a clean Args block with no filler. Every sentence earns its place: the warning, the rollback note, and the parameter definitions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive bulk operation, the description includes the essential safety workflow (preview first), rollback indication, and full parameter documentation. An output schema exists, so return-value details are not required. The tool's complexity is well covered by the combination of annotations and description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full weight for parameters. It explains query as a YouTrack search query, command as a YouTrack command, max_results with both default and an explicit upper bound (100) absent from the schema, and instance as optional. This meaningfully enriches the bare schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb ('Execute') and resource ('bulk update'), and immediately distinguishes itself from the preview sibling by warning 'call bulk_update_preview first'. It clearly identifies the operation as the execution phase of a bulk update, which an agent can readily differentiate from other update tools.
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 explicitly instructs to call bulk_update_preview first, which is a clear precondition and safety guideline. It also implies execution should follow preview, though it does not explicitly list alternatives or exclusions beyond this. The directive is actionable and precedes parameter details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's 'dry run' reinforces this. It adds valuable behavioral details about the max_result cap (default 50, max 100) that could affect the number of issues shown, beyond what the schema defines.
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 compact and well-structured: the purpose statement is front-loaded, followed by a clean parameter list. Every sentence contributes meaning without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and annotations cover the safety profile, the description provides all necessary context: purpose, sequencing relative to bulk_update_execute, parameter meanings, and the max_results limit. Nothing essential for an agent to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by explaining each parameter: 'query: YouTrack search query', 'command: YouTrack command to apply', 'max_results: Max issues to preview (default: 50, max: 100)', and 'instance: YouTrack instance (optional)'. This adds meaning beyond the bare titles.
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 'Preview which issues would be affected by a bulk update (dry run)', which is a specific verb, resource, and scope. It also distinguishes itself from the sibling tool bulk_update_execute by explicitly positioning itself as the pre-execution preview step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs 'Call before bulk_update_execute', giving a direct usage sequence. This makes it clear when to use this tool relative to its primary alternative, and the dry-run framing implies it is meant for validation before destructive execution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), it discloses the two-stage matching process, case-insensitive phrase matching with an all-words fallback, exclusion of workflow-bot nags and service stamps, and newest-first ordering. These behavioral details help the agent predict exactly what results will be returned and how the matching is performed.
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 front-loaded with the core purpose and the user-facing question it answers, then compactly explains the two-stage algorithm, filters, and ordering. Every sentence earns its place—there is no filler or redundant restatement of the tool name. The Args list is clear and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only search tool with an output schema, the description covers everything needed to call it correctly: matching mechanics, optional filters, ignored content, and result ordering. It doesn't need to describe return values because an output schema exists, and no critical behavioral or use-case information is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no per-property descriptions and only titles/defaults, so schema description coverage is 0%. The description's Args block compensates fully: it explains each parameter, highlights that 'text' is required, clarifies that 'author' adds a commenter filter, notes 'project' limits to a project key, gives the default for 'max_results', and marks 'instance' as optional. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource: 'Find issues by what their COMMENTS say,' and gives the concrete use case 'the ticket where someone wrote …'. It clearly differentiates from broader search tools like search_issues by focusing on comment text, and from comment-mutating siblings (add_comment, update_comment, delete_comment) by being a read-only find operation.
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?
It provides a clear use case and defines when to use it: any time you need to locate tickets based on comment content. It also offers detailed guidance on how the search works (full-text query with optional commenter filter, local matching, fallback behavior). However, it does not explicitly name the sibling tool to choose when searching issue fields (e.g., search_issues) or state exclusions, leaving some to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so safety is covered. The description goes well beyond by explaining the default markdown render, the normalized JSON structure, raw YT passthrough with fields, bot comment hiding, and truncation behavior—all of which are non-obvious behaviors an agent needs to predict outcomes.
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?
Although long, the description is tightly organized: a one-sentence purpose, then format explanation, then fields override behavior, then an Args list. Every sentence adds useful information, and the most critical details are front-loaded. No wasted words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 7-parameter tool with an output schema, the description covers all relevant aspects: output formats, field normalization, override behavior, comment handling, truncation, and even consistency with other tools. With an output schema present, it appropriately avoids detailing return values and instead focuses on behavioral nuances.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full responsibility for parameter meaning. The Args section thoroughly explains each of the 7 parameters, including defaults, valid values (format='report'/'json'), and nuanced interactions (fields with format, comment_chars truncation). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Get full details of a YouTrack issue', using a specific verb and resource. It then clearly distinguishes the two output formats (markdown vs normalized JSON) and explicitly states the JSON shape matches what pulse and handoffs use, making it easy to differentiate from sibling list/search tools.
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 gives clear context for when to use the default report format versus JSON, and explains when 'fields' should be used for power callers needing specific YT response fields. It does not explicitly name alternative tools for other use cases, but the usage context is well implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (read-only, idempotent, open-world, non-destructive), the description explains the local merge and heuristic for approximating replies, and explicitly discloses filtering of bot posts and notification-template pings along with a reported dropped count. This is significant behavioral context not visible in annotations or schema.
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 well-structured, front-loaded with purpose, then implementation details, then parameters. Every sentence adds meaningful information, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and presence of an output schema, the description covers operations, filtering, and parameters thoroughly. Minor gap: it doesn't explicitly describe the output shape beyond 'analyzed locally' and 'dropped count is reported', but the output schema exists to cover that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage for parameters, but the description's Args section explains 'days' as lookback window, 'max_results' as max items per section, and 'instance' as YouTrack instance. That fully compensates for the schema gap.
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: retrieving mentions and likely replies from comments that need the user's attention. It uses specific verbs and resources ('Mentions', 'Possible replies') and distinguishes it from generic comment or issue tools. The first sentence alone tells an agent exactly what this tool surfaces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly defines when to use this tool: when the user needs to see what needs attention in comments. It also differentiates from siblings by naming the underlying queries and the local analysis heuristic. It does not explicitly say 'use X instead, but the distinction between mentions/replies and other comment/issue tools is clear from the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, non-destructive. The description adds critical behavioral context: truncation of text by default, token cost concern, and the exact preview length (200-char). This is exactly the kind of value beyond annotations that helps an agent decide whether to pass include_text.
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 well-structured: a one-line summary, a context paragraph explaining the truncation behavior, and a clear Args list. Every sentence adds value, and the important caveat about truncation is front-loaded before parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description need not detail return values. It fully covers the operation's purpose, key behavioral quirks, all parameters, and optionality. There is no missing information an agent would need to call this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden. It explains each parameter: issue_id can be ID or URL, instance is optional, since/until use YYYY-MM-DD, include_text toggles full notes vs preview. This is more meaningful than the schema's bare types and defaults.
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 starts with a specific verb and object: 'Get time tracking work items for an issue.' It clearly identifies the resource (work items) and the scope (issue). Though it doesn't name a sibling, it is specific enough to distinguish from other work-item tools like add_work_item or delete_work_item.
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 explains when to use include_text=True, and implies default behavior. It gives context about the token cost that justifies not including full text. It does not explicitly compare with alternative tools, but the usage context is clear for a retrieval operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false), the description discloses the method: it applies set_fields field-by-field before attempting the state change, and if a gate blocks, it returns the exact workflow rule text rather than inventing values. This transparently explains the operation's order and error-handling 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 detailed but every sentence contributes value: it explains the problem, the approach, the fallback behavior, and then lists parameters with syntax examples. The structure is front-loaded with the primary purpose and then delves into context, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (gate-aware transitions with optional field setting), the description covers prerequisites, behavior, error reporting, and parameter syntax. An output schema exists, so return details are not required in the description. Nothing essential is missing for an agent to invoke this correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full responsibility for parameter meaning. It explains each parameter clearly: issue_id can be an ID or URL, state is a bare state name, set_fields uses command syntax with examples ('Dev Estimation 2d QA Estimation 1d'), and instance is optional. This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Change an issue's State') plus the resource (issue) and the gate-aware behavior that distinguishes it from plain update_issue or raw state changes. It clearly communicates the core function without ambiguity.
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 explains when this tool is useful: when workflow gates block transitions, it sets fields first and then transitions, reporting the blocking rule if it still fails. It implies a use case where raw update or a simple state change would be ineffective, though it does not explicitly name sibling alternatives or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint and idempotentHint, but the description adds valuable behavioral details beyond structured data: matching by work-item author and date, the default month range, the cap on unbounded scans, and YouTrack's error message for unknown users. This gives the agent a realistic model of runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: a one-line summary, a focused paragraph on matching and default behavior, then a clear Args list. Every sentence carries useful information; no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 params, 1 required) and the presence of an output schema, the description covers all essential operational details: defaults, range handling, all-time queries, error behavior, and parameter purposes. Nothing an agent needs for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description fully compensates by explaining every parameter: user (login or id, required), instance (auto-detected), since/until (date format and defaults), and top_issues (default count). This adds substantial meaning over the bare schema titles and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with a precise verb-object summary: 'Time summary for one user: total logged plus per-issue breakdown.' It clearly identifies the resource (one user) and the specific output (time summary with breakdown), which distinguishes it from sibling summary tools like monthly_time_report_by_user.
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 explains key usage context: defaults to current calendar month, warns against unbounded scans, suggests explicit early 'since' for all-time, and notes unknown-user error behavior. It does not explicitly name alternative tools or state when not to use this tool, but the guidance is clear enough for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds substantial context beyond those: how columns are classified, what data is fetched, the visibility limitation for unmapped state values, and the heuristic flags. No contradiction with 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 long but well-structured with a summary, scope section, flags, and arguments. Each section earns its place, though a few phrases could be tightened (e.g., repeating 'by design' clarifications). Slight over-explanation but not enough to lose a point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, behavior, scope, parameters, output format, and edge cases. An output schema exists, and the description mentions the JSON payload structure but doesn't need to enumerate it. Nothing essential is missing for an agent to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It explains every parameter with defaults, purpose, and justification (e.g., max_idle_days with measured noise data, format options). This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Team pulse for a board' with what it returns (shipped, upcoming, insights). It clearly distinguishes itself from sibling tools like search_issues and get_team_dashboard by scoping to board columns and mentioning alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use guidance is provided, including a 'Scope' section that warns about unmapped states and explicitly recommends 'search_issues' for full project scans. This is a clear directive on when this tool is appropriate and when it is not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses important operational behavior: file_path mode reads local file bytes and is restricted by an allowlist and environment variable, content mode uses UTF-8 encoding, and content_base64 enables binary uploads. It also explains filename defaulting and MIME auto-detection overrides.
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?
Although lengthy, the description is well structured with clear mode sections and an Args list. Every sentence adds necessary information about usage, security, alternatives, or parameter behavior, so the length is justified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with seven parameters, two operational modes, and a security constraint, the description covers everything an agent needs to invoke it correctly. It explains input formats, required parameters, defaults, encoding, and the relationship to add_comment, and an output schema exists for return-value details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden, and it succeeds. Every parameter is explained with mode relationships, defaults, required conditions, and behavior—particularly the file_path vs content modes, filename requirements, and content_base64 semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Attach a file to a YouTrack issue.' It then clarifies two distinct input modes and explicitly differentiates this tool from add_comment, making sibling distinction clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: prefer add_comment for plain-text or markdown reports, and use add_attachment for binary artifacts or downloadable files. It names the alternative and the condition that selects between them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds substantial behavior beyond annotations: composing an OR query, reusing get_issue's field set, normalizing output, defaulting include_comments to false for performance, and a ~100 ID limit. These details meaningfully inform an agent's expectations.
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 dense but every sentence earns its place, with a front-loaded purpose statement and a clear Args breakdown. No redundant or vague wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers invocation details, defaults, performance rationale, output shape, and limits. An agent has everything needed to call the tool correctly, especially with the output schema already present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the Args section thoroughly explains every parameter: ids format and limits, fields override semantics, format values, include_comments default, and instance optionality. This fully compensates for the schema's silence.
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 opens with 'Batch-fetch multiple issues in one round-trip,' a specific verb and resource that clearly states functionality. It also distinguishes itself from singular get_issue and search-based alternatives by emphasizing batch retrieval of known IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Useful when you already have a known ID list' and contrasts with the one-request-per-issue approach, implying when not to use it. It also provides practical guidance on splitting large ID lists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and idempotentHint annotations, the description explains the algorithm step-by-step, including the critical behavior that items with fresh comments but no state change are surfaced as stuck. It also clarifies the output grouping by transition pattern, which is valuable behavioral context not available in the schema or annotations.
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 structured effectively: a one-sentence definition, a differentiation paragraph, a numbered algorithm, an output description, and a parameter list. It is detailed but every section serves a purpose, and the most critical information (purpose) is front-loaded. There is no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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, nuanced algorithm), the description is complete. It covers the business problem, the exact detection logic, the output format, and all parameter semantics. Since an output schema is present, the description doesn't need to repeat return field details, but it explains the grouping concept sufficiently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 0% description coverage, the description's Args section fully documents each parameter: board_name (partial match, ID, or URL), stuck_days (default 4), lookback_days (default 30), limit (default 10), format (report vs json), and instance (optional). This compensates completely for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific definition: 'Tasks that crossed a team boundary and haven't moved since.' It names the resource (stuck handoffs) and the action (get), and explicitly distinguishes itself from sibling tools by explaining their different scopes and behaviors, leaving no ambiguity about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool vs alternatives: 'Distinct from get_handoff_snapshot... and track_cross_dept_journey...' It explains what those alternatives do and why this one is different, providing clear guidance on selection. It also implies the use case (identifying stuck handoffs) effectively.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![yt-mcp MCP server](https://glama.ai/mcp/servers/velesnitski/yt-mcp/badges/card.svg)](https://glama.ai/mcp/servers/velesnitski/yt-mcp)

Score Badge

Copy to your README.md:

[![yt-mcp MCP server](https://glama.ai/mcp/servers/velesnitski/yt-mcp/badges/score.svg)](https://glama.ai/mcp/servers/velesnitski/yt-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/velesnitski/yt-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server