taskdog-mcp
Server Quality Checklist
Latest release: v0.26.0
- Disambiguation5/5
Each tool targets a distinct resource and action combination. Lifecycle verbs like start_task, complete_task, pause_task, cancel_task, and reopen_task are clearly differentiated by their state transitions, and list_tasks vs get_executable_tasks are distinguished by the latter's focus on AI-executable work.
Naming Consistency5/5All tool names follow a consistent verb_noun snake_case pattern (e.g., list_tasks, create_task, delete_task, optimize_schedule). Retrieval tools use get_ for single items and list_ for collections, and state-changing verbs are consistent throughout.
Tool Count2/5With 26 tools, this exceeds the 25-tool threshold for 'too many.' While the domain is broad, several utilities like get_task_notes, set_task_tags, and the various statistics tools could potentially be consolidated.
Completeness5/5The tool surface provides comprehensive task lifecycle management: create, read, update, delete/archive/restore, all status transitions, dependencies, tags, notes, audit logs, statistics, scheduling optimization, and decomposition. No obvious gaps exist for a task management system.
Average 3.9/5 across 26 of 26 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 5 of 5 community issues answered or closed in the last 6 months
- 205 commits in the last 12 weeks
- Last stable release on
- 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.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must carry the full behavioral burden. It gives format examples and says tags 'replace existing,' but it does not clarify whether omitted/null fields are left unchanged or explicitly cleared, nor does it mention validation rules (e.g., priority range, planned_start vs planned_end ordering) or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear one-sentence purpose followed by a bullet list of parameters. It is concise enough for the parameter count, though the 'Returns' line is somewhat redundant given the output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter mutation tool with no annotations, the description lacks critical context: partial update behavior, null semantics, validation constraints, and when to use alternative update tools. It also duplicates the return value despite an output schema being present, making it incomplete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 9 parameters are listed with brief format examples (e.g., ISO datetimes, duration as hours) and the note that tags 'replaces existing.' However, the description does not explain the meaning of null defaults (no change vs clear) or the significance of fields like is_fixed and priority, leaving semantic gaps beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Update an existing task,' which is a clear verb+resource statement. It distinguishes from create_task and delete_task, but does not differentiate from siblings like set_task_tags or update_task_notes, which also modify tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus the many sibling tools. There is no mention of alternatives, exclusions, or scenarios where a more specific tool (e.g., set_task_tags) would be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the critical behavioral trait that tags are replaced (not appended), and it mentions the return value. However, it does not address permissions, side effects on other data, or handling of empty tag lists. This partial but important disclosure earns a mid-range score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main purpose. The Args/Returns format is efficient and skips unnecessary fluff. However, the Args section largely duplicates schema information, which is a minor inefficiency that prevents a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given 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 core action and return type. But the absence of any usage context, error conditions, or relationship to sibling tools leaves gaps. An output schema exists, so return details are not required, but the lack of annotations and usage guidance makes it only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds minimal semantics: it restates the parameter names and provides brief definitions ('ID of the task', 'New list of tags') that barely exceed the schema titles. It does not explain formats, constraints, or edge cases, so it fails to compensate for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Set tags for a task (replaces existing tags).' This specifies the verb, resource, and key behavior (replacement). While it doesn't explicitly differentiate from sibling tools like update_task, the function is uniquely about tags, making the purpose clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It does not mention prerequisites, exclusions, or when another tool (e.g., update_task_notes) might be more appropriate. The description is purely operational with no contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior, but it only states the action and return value. It does not explicitly mention that the task is unarchived, whether the operation is reversible, what permissions are required, or what happens if the task is already active, making it insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose. It uses a clear Args/Returns structure with no redundant information, making every sentence purposeful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though an output schema exists, the description lacks essential context about what 'archive' means, how restore interacts with task states, and what the restored task data contains. It also does not reference sibling tools or edge cases, leaving the tool under-specified for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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. However, 'task_id: ID of the task to restore' merely restates the parameter name without adding meaningful semantic details like format constraints, examples, or how the ID relates to other task operations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Restore') and the target resource ('an archived task'), making it distinct from sibling tools like delete_task or create_task. The scope is explicitly limited to archived tasks, which differentiates it from similar operations like reopen_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use restore_task versus alternatives such as reopen_task or how to handle tasks that are not archived. The description lacks any context about prerequisites, side effects, or exclusions, 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention read-only safety, error handling, permissions, or any side effects. The 'Returns' line only vaguely indicates content, leaving behavioral aspects undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured, presenting the purpose, args, and returns in a clean format. Every word earns its place, though it borders on under-specification due to its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema, the description is adequately complete for a simple getter. It covers the core action and return type, though it could benefit from noting edge cases or read-only behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema property 'task_id' already has a title 'Task Id', and the description's 'task_id: ID of the task' adds no new meaning. With 0% schema description coverage, the description was expected to compensate, but it merely restates the parameter name without explaining format, constraints, or usage details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves notes for a task, using a specific verb ('Get') and resource ('notes for a task'). This distinguishes it from sibling tools like get_task and update_task_notes, leaving no ambiguity about its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when notes for a task are needed, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. For a simple getter, the intended use is fairly obvious, but no direct guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden of behavioral disclosure, but it only says the tool 'updates' notes and returns a confirmation. It does not mention whether notes are overwritten, any permission requirements, side effects, or idempotency considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is minimal and well-structured with a clear summary, argument list, and return type. Every sentence adds essential information without unnecessary elaboration, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool, the description covers purpose, arguments, and return value. However, it omits operational context such as whether the task must exist, how updating notes interacts with other task fields, or potential error conditions, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains both parameters: task_id and content, clarifying that content is markdown. This adds meaningful semantics beyond the raw schema, though it stops short of providing detailed formats or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update notes for a task', identifying the specific verb (update) and resource (task notes). It is unambiguous and distinct from siblings like get_task_notes, though it does not explicitly distinguish itself from update_task, which could also modify notes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 update_task or get_task_notes. It lacks contextual scenarios, prerequisites, or exclusions, leaving the agent without information on usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses that 'hard=True' permanently deletes and 'hard=False' archives, which explains the two outcomes. However, it does not disclose whether permanent deletion is irreversible or any side effects on dependencies, audit logs, or related tasks. The return confirmation message is also mentioned, but deeper behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a clear structure with Args and Returns. Every sentence adds value, and the content is appropriately front-loaded with the core purpose. There is no unnecessary verbosity or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential purpose, parameters, and return type, which is a good baseline for a simple deletion tool. However, it lacks contextual details like when to choose soft vs hard delete, and how this relates to sibling tools like 'restore_task'. The presence of an output schema reduces the need to explain return values, but usage guidance gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 explains 'hard' clearly (permanent vs soft delete), but 'task_id' is only described as 'ID of the task to delete'—adding no nuance beyond the parameter name. Given there are only two parameters and one receives meaningful explanation, the description provides partial compensation for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the core action clearly with 'Delete a task.' It also distinguishes between permanent delete and archive (soft delete) via the 'hard' parameter, which adds nuance beyond a simple delete. However, it does not explicitly differentiate from sibling tools like 'cancel_task' or 'pause_task', which may have similar lifecycle effects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The 'hard' parameter implies two modes, but there is no mention of use cases such as 'use archive for reversible deletions' or 'use permanent delete for data cleanup'. It also fails to mention that archived tasks might be restorable via 'restore_task', a sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. The verb 'Get' implies a read-only operation, but it does not explicitly confirm safety, mention authentication or limitations, or explain the scope of 'statistics' beyond the period parameter. The return content is partially specified ('etc.'), leaving some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with Args and Returns sections. It is front-loaded with the purpose and every sentence contributes meaning, avoiding redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter stats tool, the description covers the purpose, parameter semantics, and return content adequately. The presence of an output schema reduces the need to detail return fields. Slight gap: it does not mention when to prefer this over get_tag_statistics, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only provides type and default for 'period'. The description adds the valid values (all, 7d, 30d) and clarifies its meaning as a time period, compensating for the 0% schema description coverage. This is valuable semantic information beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as 'Get task statistics' and provides return details (counts by status, completion rates), distinguishing it from sibling get_tag_statistics which focuses on tag-specific statistics. The verb+resource is specific, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like list_tasks or get_tag_statistics. The description lacks context on use cases, prerequisites, or exclusions, leaving the agent to infer appropriate selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action and return type, without specifying whether the removal is permanent, what happens if the dependency does not exist, or any side effects. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with a clear purpose sentence and Args/Returns sections. No unnecessary words or redundancy, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple 2-parameter tool with an output schema, and the description covers the essential operation and return format. However, it lacks usage context, such as being the inverse of add_dependency, and lacks details about edge cases. It is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the schema by explaining 'task_id' as 'ID of the task with the dependency' and 'depends_on_id' as 'ID of the dependency to remove.' However, the latter phrasing is ambiguous—it could be interpreted as a relationship ID rather than a task ID, which creates potential confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Remove a dependency between two tasks,' which is a specific verb and resource. It clearly distinguishes this tool from siblings like add_dependency, 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The tool's use is implied by its purpose, but there is no explicit guidance on when to use it versus alternatives (e.g., add_dependency) or any prerequisites like the dependency must exist. No exclusions or conditional scenarios are mentioned.
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?
No annotations are provided, so the description carries the burden. It discloses the status change and return value, but does not mention reversibility, permissions, or side effects on related tasks or dependencies. This leaves significant behavioral unknowns for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded with the core action, and includes only necessary details. No redundant text or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description covers the basic action and return. However, it lacks contextual guidance on tool selection and potential side effects, so it is not fully complete for real-world decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains task_id as 'ID of the task to cancel', which adds a minimal gloss over the schema's bare integer field. With 0% schema description coverage, this is helpful but lacks additional context like required format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool cancels a task and changes its status to CANCELED, which is specific and distinguishes it from delete_task or pause_task. However, it does not explicitly name alternative tools, so it stops short of the highest clarity rating.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The verb 'cancel' implies when to use the tool, and the status change to CANCELED hints at its intended use. Yet there is no explicit guidance on when to use cancel over pause, complete, or delete, especially with many relevant 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?
No annotations are provided, so the description must carry the behavioral disclosure burden. It discloses the return type (tag statistics including task counts per tag), which implies a read-only aggregate operation, but it does not explicitly confirm lack of side effects, permissions, or rate limits. This is a minimum viable disclosure for a simple getter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, each earning its place. It front-loads the primary purpose and then provides a helpful return-value summary. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (no params) and the existence of an output schema, the description is mostly complete. It mentions the key outcome (task counts per tag) and the 'all tags' scope. The only gap is lack of differentiation from get_statistics, but this doesn't significantly undermine completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and schema coverage is 100% (empty schema). The description adds semantic meaning by clarifying the scope is 'all tags', which is useful context beyond the empty schema. Baseline for 0 params is 4, and this is appropriately scored.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets statistics for all tags, with a specific scope ('all tags') and a detail on the return value ('task counts per tag'). This distinguishes it from sibling tools like list_tasks and get_statistics by focusing on tag-specific aggregation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention that get_statistics might be a broader alternative or when a tag-specific stat is preferred. No exclusions or prerequisites are stated.
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 are absent, so the description carries the transparency burden. It discloses that return includes 'Task details including notes', which is useful output context. However, it does not explicitly state whether the operation is read-only, what happens if the task does not exist, or whether special permissions are required. The verb 'Get' implies a read operation, but that is implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a short intro plus an Args section and a Returns section. There is no fluff, redundant phrasing, or unnecessary details. Every line contributes meaningful information, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter getter with an output schema, the description covers the core behavior and return highlight (notes). It lacks guidance on edge cases, error behavior, and alternative tools, but given the low complexity and presence of an output schema, it is reasonably complete. A higher score would require more explicit usage context or failure-mode disclosure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that says 'task_id: The ID of the task to retrieve', adding semantic meaning beyond the schema's bare integer type. Even though the context signal reports 0% schema coverage, the description itself actually documents the parameter, and it does so clearly and concisely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get detailed information about a specific task', which is a specific verb+resource combination. It distinguishes itself from siblings like list_tasks (which lists multiple tasks) and get_task_notes (which only fetches notes) by focusing on a single task's full details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives such as list_tasks or get_task_notes. The word 'specific' implies a contrast with list_tasks, but no direct comparison or exclusions are provided. This 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.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the burden of behavioral disclosure. It explains the dependency relationship and that it returns confirmation with updated task info, but it does not mention edge cases like duplicate dependencies, invalid task IDs, or cyclic dependency checks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured, with the purpose front-loaded in the first sentence and clear Args/Returns sections. Every sentence adds value without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description covers the essential behavior, parameter roles, and return value. It lacks details on error handling or duplicate dependency behavior, but the low complexity makes it reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides clear meanings for both parameters beyond the schema titles: task_id is the dependent task, and depends_on_id is the prerequisite task. This compensates for the 0% schema description coverage and helps the agent understand which ID goes where.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action with a specific verb and resource: 'Add a dependency between two tasks.' It further distinguishes the direction of the dependency by explaining 'must be completed first,' which sets it apart from sibling tools like remove_dependency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the semantic meaning of the dependency (the task depends on another that must be completed first), which implies when to use it. However, it does not explicitly mention alternatives or exclusions, such as when to use remove_dependency instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool creates a task and returns the created data with an ID, and it provides behavioral notes on parameters (e.g., is_fixed prevents optimizer movement). However, it does not disclose potential side effects, permission requirements, or failure modes, which a fully transparent description might include.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a one-sentence purpose, a bulleted parameter list, and a returns line. It is appropriately sized for an 8-parameter tool, with every line adding value, though the parameter list is necessarily lengthy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all parameters with type/format details, names the required field, and states the return value. Given the presence of an output schema, it does not need to elaborate on return structure. It lacks discussion of edge cases or side effects, but for a create tool with clear parameter docs, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides detailed semantics for all 8 parameters, including units, formats, examples, and domain meaning (e.g., priority: 'higher = more important'; estimated_duration: 'in hours'). Since the schema provides only types and defaults with 0% coverage, this description fully compensates and exceeds baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the specific verb+resource combination 'Create a new task,' which clearly distinguishes this tool from sibling tools like update_task, delete_task, and list_tasks. The 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 Guidelines3/5Does 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. It relies on the verb 'create' to imply usage, but offers no exclusions or alternative tool references, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states the core effect (status changes to PENDING) and the return type (updated task data), but does not mention permissions, reversibility, or side effects on related fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of three short sentences plus a structured Args/Returns block. 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.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter mutation tool, the description covers the main action, precondition, and return value. It could be more complete by distinguishing from restore_task (likely for deleted tasks) or noting whether it only applies to non-deleted tasks, but overall it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 defines task_id as 'ID of the task to reopen', which adds minimal meaning beyond the parameter name itself. The parameter is self-explanatory, but the description adds little extra depth.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reopens a completed or canceled task and changes its status to PENDING. This specific verb+resource combination distinguishes it from sibling tools like start_task or restore_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly mentions the tool is for completed or canceled tasks, giving clear context for appropriate use. However, it does not name alternatives or explicitly state when not to use it, so it lacks the full 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?
No annotations are provided, so the description carries the burden. It discloses that the operation returns metadata and specifies the return structure, but it does not explicitly state that the operation is read-only or free of side effects, though listing algorithms is naturally non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the primary action. It includes a returns section that duplicates the output schema, but this is acceptable for clarity and does not waste words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of a no-parameter listing tool with an output schema, the description is sufficient. It explains what algorithms are returned and the purpose. It could mention that this is a safe read-only call, but absent that, it is still complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema covers everything. Per rubric, 0 params gives a baseline of 4; the description correctly includes no parameter information because there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List available schedule optimization algorithms' with a specific verb and resource. It distinguishes from sibling tools like list_tasks or get_statistics, as it is uniquely about algorithms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: callers can use it to choose an algorithm for their workload, likely before using optimize_schedule. It does not explicitly name alternatives or exclusions, but the purpose is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the status change and that start time is recorded, which is helpful. However, it does not mention side effects, permission requirements, or failure behavior if the task is not in PENDING state, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear one-line summary followed by the state change explanation and formatted Args/Returns sections. Every sentence adds value, and the information is front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple state transition tool, the description covers the main function and return value. However, it lacks explicit mention of preconditions (task must be PENDING) or error scenarios, which could be important given the sibling tools and the presence of an output schema. The description is adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has only one parameter, task_id, with no description. The description adds semantic meaning by explaining it as 'ID of the task to start', which clarifies its role. Since the parameter is well-named and simple, this is sufficient, though it could be more detailed about accepted formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Start working on a task' and specifies the exact state change from PENDING to IN_PROGRESS. This distinguishes it from sibling tools like pause_task, complete_task, and cancel_task, which handle other state transitions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the task must be in PENDING state in order to change to IN_PROGRESS, providing clear context for use. It does not explicitly mention alternatives or exclusions, but the state transition guidance is sufficient for selecting this tool over siblings.
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?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does state the key effects (status change to COMPLETED, end time recording), but it does not mention prerequisites, idempotency, or behavior if the task is already completed. This leaves some gaps for a state-changing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections: purpose statement, Args, and Returns. Each sentence earns its place with no filler or redundancy. It is concise and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, effect, parameter meaning, and return value ('Updated task data with completion confirmation'). An output schema exists, so the description need not detail the return structure. It lacks edge-case behavior, but for a simple state-change tool, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 compensate. It explains task_id as 'ID of the task to complete,' which adds semantic meaning beyond the bare schema type (integer). For a single straightforward parameter, this is adequate and helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action with a specific verb and resource: 'Mark a task as completed' and further details the behavioral effect ('Changes status to COMPLETED and records end time'). This distinguishes it from sibling tools such as start_task, pause_task, cancel_task, and reopen_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to mark a task as completed. It does not explicitly mention when not to use it or name alternatives, but the context is unambiguous given the sibling tool names and the status transition described.
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?
With no annotations, the description discloses that the tool resets status to PENDING and clears timestamps, adding behavioral context beyond the tool name. However, it doesn't mention prerequisites (e.g., task must be in progress), reversibility, or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main action, followed by a clear Args and Returns structure. Every sentence serves a purpose with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple tool with one parameter and an output schema, covering purpose, parameter meaning, and return value. It lacks explicit comparison to sibling tools but that is more of a usage guideline issue.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description defines task_id as 'ID of the task to pause,' providing meaning that the input schema lacks (since schema description coverage is 0%). This is sufficient for a single-parameter tool, though it doesn't add additional constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Pause') with a specific resource ('a task') and explicitly states the effect (reset to PENDING, clears timestamps). This clearly distinguishes it from sibling tools like cancel_task or complete_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for pausing tasks but provides no explicit when-to-use guidance or contrasts with alternatives such as cancel_task, start_task, or restore_task. The context is clear but no exclusions or alternative comparisons 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?
There are no annotations, so the description carries the transparency burden. It discloses that past dates are allowed and describes the clear flags and their effects (e.g., 'use calculated value' for clear_duration). However, it does not state what happens when conflicting values are provided (e.g., both actual_start and clear_start), nor does it explicitly warn that existing values are overwritten.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured with Args and Returns sections. It provides necessary detail without unnecessary words, earning a top score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters and no annotations, but the description covers purpose, parameter semantics, return value, and a key constraint (past dates). It lacks explicit conflict-resolution rules between set and clear flags, making it not fully complete, but close.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description's Args section comprehensively explains all 7 parameters with examples (ISO format, duration notation like '0.5 = 30min'). 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fix') and identifies the resource ('actual start/end timestamps for a task'), clearly distinguishing it from sibling task-management operations like start_task or update_task. The phrase 'for historical accuracy' adds context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It states 'Used to correct timestamps for historical accuracy' and 'Past dates allowed', giving clear context for when to use. However, it does not explicitly name alternative tools or when not to use, so it falls just 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.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return content ('including old and new values'), but does not mention error behavior (e.g., what happens if the log_id does not exist), authentication needs, or rate limits. For a simple read operation, the information is partially transparent but lacks failure-mode disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a one-sentence purpose followed by an Args section and a Returns section. Every sentence provides necessary information without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only one parameter and an output schema, so the description needn't elaborate on return structure. It covers what the tool does, the parameter meaning, and the key return contents. However, it omits any mention of error scenarios or prerequisites, which would make it fully complete for an unannotated tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema property 'log_id' has no description, the tool description explicitly documents 'log_id: The ID of the audit log entry to retrieve.' This adds complete meaning beyond the schema's bare integer type and required flag, fully 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Get detailed information about a specific audit log entry.' It uses a specific verb with a resource and scope, distinguishing it from sibling tools like list_audit_logs (which lists entries) and get_task (which retrieves a different resource type).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need details for a single audit log entry by its ID. It doesn't explicitly name alternatives or when-not-to-use, but the wording 'specific audit log entry' clearly contrasts with listing, making the intended use clear. No exclusions are given, so it earns a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains parameter semantics (e.g., 'date-only value covers the whole day', 'failed: If True, only show failed operations') and declares a return shape ('Dictionary with logs list and metadata'). However, it does not mention ordering, timezone handling, pagination beyond the limit, or how filters combine, leaving some behavior ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a one-line summary, a bullet-style Args block, and a Returns line. It covers all parameters without unnecessary verbosity, and every line adds value. The docstring-like format is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 optional parameters and an output schema, the description is quite complete. It explains all parameters and gives a high-level return shape. However, it omits some behavioral details such as sorting order and whether filters are ANDed, which would be useful for a listing tool, but the presence of an output schema mitigates the need for a full return specification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite the input schema having no parameter descriptions, the description thoroughly documents all 7 parameters. It provides concrete examples for operation and since, clarifies the date-only behavior of until, and states the meaning of limit and failed. This fully compensates for the schema's lack of description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'List audit logs with optional filtering', which immediately states the action (list) and resource (audit logs). This clearly distinguishes it from the sibling get_audit_log, which is singular and likely fetches one record. It also adds a list of filters, making the scope explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear this tool is for listing audit logs, with specific options for filtering by task, operation, client, time range, failure status, and limit. It implies usage when you need a filtered log view, but it does not explicitly mention when not to use it or point to alternatives like get_audit_log for single-log retrieval.
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?
No annotations are provided, so the description carries the burden. 'List' clearly implies a read-only operation, and the Returns section adds context about the response structure. It does not mention authentication or pagination, but for a list tool this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a one-line summary, Args list, and Returns line. Every sentence is informative with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality, parameters, and return type. It could mention pagination or result limits, but given that an output schema exists and the tool is straightforward, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description thoroughly documents all 5 parameters: include_archived, status, tags, sort_by, reverse, and lists valid sort fields. This adds significant meaning beyond the bare schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all tasks with optional filtering' with a specific verb and resource. It distinguishes itself from siblings like get_task (single task retrieval) and get_statistics (analytics) by focusing on listing with filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies its usage for listing tasks with optional filters. However, it does not explicitly name alternatives or exclusions (e.g., 'use get_task for a single task'), so it lacks explicit when-not-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?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly states the destructive effect: "Removes the tag and all its associations with tasks." It also discloses the return value (confirmation with tag name and affected task count). It does not explicitly mention irreversibility, but "delete" inherently implies it, and the description covers the main side effect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: purpose statement, side-effect detail, args, and returns. Every sentence adds value with no verbosity or redundancy. It is appropriately front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete tool with one parameter and no annotations, the description covers all necessary aspects: the operation, the side effect (removing associations), the parameter, and the return value. The output schema exists but the description independently summarizes the return, providing sufficient context for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema only provides a type and title for tag_name. The description compensates fully by stating "tag_name: Name of the tag to delete," adding semantic meaning beyond the schema. This is a single-parameter tool, and the description makes the purpose of that parameter explicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb+resource: "Delete a tag from the system," and further specifies that it removes the tag and all associations with tasks. This distinguishes it from siblings like set_task_tags (which manages task–tag associations) and delete_task, 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 Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool (permanently remove a tag and its associations) and provides the key context that all task associations are removed. It does not explicitly name alternatives or exclusions, but the sibling list contains no other tag-deletion tool, so the intended usage is clear. A minor gap is not mentioning that to only detach a tag from a task, one should use set_task_tags.
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?
With no annotations available, the description discloses key behavioral traits: it returns only PENDING or IN_PROGRESS tasks and sorts them by priority. This goes beyond the schema, but it doesn't explicitly state read-only behavior or other side effects, so a 4 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear summary, usage note, and parameter breakdown. Every sentence adds value and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the key aspects: what it returns, filtering options, and usage intent. It doesn't need to detail the output format since an output schema is available.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description fully compensates by explaining both parameters: 'tags: Filter by tags (e.g., ['coding', 'ai-executable'])' and 'limit: Maximum number of tasks to return'. This adds meaning the schema lacks and includes an example for tags.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get tasks that AI can potentially execute' and specifies 'Returns PENDING or IN_PROGRESS tasks sorted by priority', which distinguishes it from sibling tools like list_tasks. This is a specific verb+resource with clear scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this to find tasks to work on', providing a clear context for when to use this tool. However, it does not explicitly name alternatives or exclusions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains key behaviors: subtasks can be linked with sequential dependencies, grouped by tag, archive_original controls whether the original task is archived, create_dependencies controls dependency creation, and priority inheritance is described. It also clarifies the data model around relationships. No contradictions with annotations 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized: a one-line summary, a supporting paragraph, a useful domain note, structured Args, and Returns. The sentence 'This tool helps break down complex tasks into manageable subtasks' is largely redundant with the first line, but overall the length is warranted given the number of parameters and the need to explain subtask structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with five parameters including a nested subtask array, the description is highly complete. It covers all parameters, their defaults, the return value ('Decomposition result with created subtask IDs'), and the crucial domain context about Taskdog's lack of parent-child hierarchy. The presence of an output schema reduces the need to detail return values further, making this description sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only titles and types (0% description coverage), so the description fully compensates by explaining each parameter: task_id, subtasks with sub-fields (name, estimated_duration, priority, tags), group_tag, create_dependencies, and archive_original. It also explains defaults and behavior of parameters, making the tool usable despite the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Decompose a large task into smaller subtasks,' a specific verb+resource that clearly states the tool's function. It distinguishes decompose_task from sibling tools like create_task or update_task by focusing on breaking down a task into subtasks with dependencies and grouping options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that the tool is for breaking down complex tasks into manageable subtasks. It also includes a domain note about Taskdog lacking parent-child relationships, recommending dependencies + tags + notes instead. However, it does not explicitly name alternatives or state when not to use this tool versus other task-management tools.
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?
With no annotations, the description fully discloses default behavior, override logic, and return values. It even characterizes each algorithm (e.g., 'greedy (front-load)') and notes the start_date default to server time. This is comprehensive behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, followed by behavior explanations and Args/Returns sections. Every sentence adds value, and the long algorithm list is necessary for correct tool use.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, 9 algorithms, no schema descriptions or annotations), the description covers all necessary aspects: parameters, defaults, edge cases, and output structure. It also directs users to list_algorithms() for further discovery, completing the contextual picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates fully by explaining every parameter in Args, including examples, formats, and defaults. The algorithm parameter lists all accepted values with brief semantic descriptions, far exceeding schema capabilities.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The opening line 'Auto-generate optimal task schedules' clearly states the verb and resource. The description goes on to detail scheduling behavior, algorithm options, and exceptions, making it distinct from sibling task CRUD tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains defaults ('weekdays only', 'skips tasks that already have a planned_start') and conditional parameter usage (force_override, include_all_days). It references list_algorithms() for discovery but does not explicitly compare with alternative scheduling approaches or tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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