Coach AI

by 94aharris

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation3/5
Most tools have distinct purposes, but there is notable overlap between brain_dump_tasks and parse_task_list (both parse natural language tasks, with brain_dump_tasks also creating them), and between sync_daily_note and sync_from_daily_note (both sync tasks from daily notes, with unclear differentiation). Other tools like add_todo and break_down_task are clearly distinct, but the overlaps could cause confusion in selection.
Naming Consistency4/5
Tool names predominantly follow a consistent verb_noun or verb_adjective_noun pattern (e.g., add_todo, list_todos, create_daily_note), with clear and descriptive naming. Minor deviations exist, such as get_user_context (verb_noun_noun) and start_my_day (verb_possessive_noun), but overall the naming is predictable and readable across the set.
Tool Count2/5
With 28 tools, the count is excessive for a personal productivity/coaching server, leading to potential overwhelm and redundancy. While the domain is broad, many tools (e.g., sync_daily_note vs. sync_from_daily_note) could be consolidated, and the high number detracts from a streamlined user experience, indicating poor scoping.
Completeness5/5
The tool set comprehensively covers the personal productivity and coaching domain, including full CRUD for todos and goals, daily note management, task parsing, planning workflows (daily/weekly), user context tracking, and synchronization features. There are no apparent gaps; agents can manage the entire lifecycle from task creation to completion and reflection.
Average 3.7/5 across 28 of 28 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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Add a glama.json file to provide metadata about your server.
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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.
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides almost none. It does not confirm the read-only nature (beyond the verb 'List'), describe output format, explain empty result handling, or mention sorting/ordering behavior despite having an output schema that likely returns collections.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately terse with zero redundancy. The purpose is front-loaded in the first sentence, followed by a structured Args section. Every line earns its place; there is no fluff or unnecessary verbosity despite the minimal content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and the existence of an output schema, the description is minimally adequate. However, the lack of annotations, sibling differentiation, and behavioral context leaves gaps that prevent it from being fully self-sufficient for an agent to use optimally.
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 successfully compensates by documenting the single parameter in the Args section. It provides semantic meaning ('Filter by'), valid enum values ('active' or 'all'), and default behavior that the schema omits, effectively bridging the documentation gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the basic action ('List') and resource ('goals'), but provides no scoping details or differentiation from sibling tools like 'list_todos' or 'set_goal'. It meets the minimum threshold of clarity but lacks the specificity to distinguish when to query goals versus todos.
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 use this tool versus alternatives (e.g., 'list_todos' for tasks or 'set_goal' for creation). It also fails to advise when to use 'active' vs 'all' filters, leaving contextual decisions to the agent without support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden but offers minimal behavioral context. It states the tool creates a section but does not specify what happens if the section already exists (error, overwrite, or append), whether the operation is idempotent, or any side effects beyond returning a 'Confirmation message'.
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 docstring format with Args/Returns sections is structured and scannable. The first sentence provides immediate clarity. While the Args/Returns headers add slight verbosity, they effectively organize information given the lack of schema descriptions. No extraneous sentences are present.
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 4-parameter tool with zero schema descriptions and no annotations, the description adequately covers parameter semantics and return type. However, it lacks critical context regarding error conditions (duplicate sections, missing daily note) and fails to clarify the relationship with similar sibling tools, leaving 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?
Given 0% schema description coverage, the description effectively compensates by documenting all four parameters in the Args section: 'section_name' purpose, 'content' as initial content, 'date_str' format (YYYY-MM-DD) and default behavior, and 'emoji' with clear examples. This provides necessary semantic context missing from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Add[s] a new section to the daily note' with specific verb (Add/Creates) and resource (section). However, it does not differentiate from the sibling tool 'write_daily_note_section', leaving ambiguity about whether this tool appends to existing sections or strictly creates new ones.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'write_daily_note_section' or 'create_daily_note'. There is no mention of prerequisites (e.g., whether the daily note must exist first) or conditions that would trigger selection of this specific tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it states the action ('Mark... as complete'), it fails to disclose if the operation is idempotent, reversible, or if it triggers side effects like logging to log_accomplishment. It also does not mention the return value, though an output schema 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 appropriately brief and front-loaded with the action statement. The Args section is structurally clear and necessary given the schema's lack of descriptions. No sentences are wasted, though the Args formatting is slightly redundant with standard schema documentation patterns.
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 single-parameter mutation tool with an output schema, the description is minimally sufficient. It covers the core action and parameter, but given the lack of annotations and the presence of related workflow tools (log_accomplishment, set_todo_timeframe), it omits relevant contextual details about integration with the broader task management workflow.
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%, leaving the description to compensate. The Args section successfully documents the single parameter (todo_id: 'The ID of the todo to complete'), providing necessary semantic context that the schema lacks. It does not add format constraints or example values, but adequately covers the single required parameter.
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 ('Mark') and resource ('todo') with a clear outcome ('as complete'). It inherently distinguishes from siblings like add_todo, delete_todo, and list_todos through the verb choice, 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like delete_todo (permanent removal) or set_todo_timeframe (scheduling). It does not mention prerequisites (e.g., todo must exist) or side effects.
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 provided, so the description carries full burden. It fails to disclose what the tool returns (despite having an output schema), whether setting a goal replaces existing ones, or any side effects. Only behavioral hint is the example values for timeframe and category.
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 core purpose is front-loaded in the first sentence. The 'Args:' section is compact and efficient, though the docstring-style formatting is slightly less readable than prose. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 3 parameters and existing output schema, the description adequately covers input semantics but lacks behavioral context. Since an output schema exists, the omission of return value description is acceptable per guidelines, but the absence of workflow context (how goals interact with todos/tasks) leaves 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?
With 0% schema description coverage, the description compensates effectively by documenting all 3 parameters. It provides clear descriptions for 'goal' and 'category', and adds concrete examples for 'timeframe' and 'category' that clarify expected input formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Set') and resource ('goal'). However, it doesn't differentiate from sibling tools like 'add_todo' or 'break_down_task', leaving ambiguity about when to use goals versus tasks in this productivity system.
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 provided on when to use this tool versus alternatives like 'add_todo' or 'set_week_theme'. No mention of prerequisites, constraints, or relationships to the goal management workflow (e.g., whether goals must be unique).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. While it mentions 'positive reinforcement' as an outcome, it fails to disclose persistence characteristics (is this stored permanently? retrievable?), whether it triggers side effects (notifications, summaries), or what the output schema contains despite the tool having an output 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 efficiently structured with three distinct components: the action statement, the value proposition, and the parameter documentation. No words are wasted, and the front-loaded purpose immediately clarifies intent despite the informal 'Args:' formatting.
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 single-parameter logging tool, the description is minimally adequate but incomplete. It omits any mention of the return value despite the presence of an output schema, and doesn't address whether logged accomplishments can be retrieved, edited, or deleted later. Given the tool's simplicity, this is viable but leaves 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?
With 0% schema description coverage (the 'description' property has no description field), the tool description compensates by explicitly documenting the parameter under an 'Args:' section ('What the user accomplished'). It successfully adds necessary meaning the schema lacks, though it could enhance further with format examples or length constraints.
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 logs user accomplishments and mentions the benefit (tracking progress and positive reinforcement). However, it doesn't differentiate from siblings like `complete_todo` which also marks task completion/accomplishments, leaving ambiguity about when to use this general-purpose logger versus specific task completion.
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 like `complete_todo` (for task completion), `add_user_fact` (for persistent user data), or `add_daily_note_section` (for daily journaling). Without explicit when-to-use criteria, the agent may confuse this with other logging/tracking siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return value ('Confirmation message') but fails to specify critical mutation details: whether this appends to existing context or overwrites, whether multiple context entries accumulate, or if the operation is idempotent. The word 'Add' implies non-destructive creation but lacks specificity.
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 uses a structured Args/Returns format that efficiently organizes information. The lead sentence establishes purpose immediately, and the parenthetical examples add value without verbosity. No redundant or filler text is present.
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 three-parameter tool with simple scalar types, the description is adequate but not comprehensive. It compensates for zero schema coverage and acknowledges output existence, but gaps remain regarding behavioral nuances (accumulation vs. replacement of context notes) and interaction patterns with the task lifecycle.
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?
Given 0% schema description coverage, the description effectively compensates by documenting all three parameters. Notably, it specifies the enumerated values for context_type ('progress, why, blocker, link') which the schema omits (declaring only type: string). This provides essential semantic constraints missing from the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add context note to task') and provides concrete examples in parentheses ('where left off, why doing it, etc.') that distinguish this from simply updating task metadata. It differentiates from siblings like add_todo or complete_todo by specifying 'context note' as the resource being manipulated.
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 parenthetical examples imply usage scenarios (tracking progress, rationale), but there is no explicit guidance on when to use this versus alternatives like add_daily_note_section or write_daily_note_section. No 'when-not-to-use' or prerequisite conditions are specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. While it mentions facts help 'personalize recommendations,' it fails to disclose persistence guarantees, duplicate handling, storage limits, or what the output schema contains.
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?
Uses an 'Args:' section to document parameters efficiently, includes concrete examples, and avoids redundancy. Structure is clear with purpose stated upfront followed by usage examples.
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?
Adequate for a two-parameter tool with an output schema (which excuses return value documentation), but lacking behavioral details like idempotency or conflict resolution that would be necessary for a production mutation 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?
With 0% schema description coverage, the description compensates effectively by providing semantic examples for 'fact' and explicitly listing the six valid enum values for 'category' ('preferences', 'challenges', etc.) that 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 clearly states the tool 'remembers' a 'fact about the user' and lists specific types (preferences, patterns, challenges, strengths, routines). The scope is distinct from siblings like add_task_context or add_daily_note_section, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides examples of what to store ('Works best in mornings') and implies usage through categories, but lacks explicit guidance on when NOT to use it versus add_task_context or get_user_context, and doesn't mention prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'retrieves' implies a read-only operation, the description fails to disclose what determines 'relevant' context (filtering logic), the approximate data volume returned, whether it aggregates data from multiple sources, or its relationship to the `add_user_fact` sibling tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two efficiently structured sentences that are front-loaded with the core action and resource. The second sentence adds value by specifying the data source ('stored facts') and use case ('personalize responses'), though it partially overlaps with the first sentence's content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description appropriately omits detailed return value specifications. However, given the ecosystem of sibling tools (particularly `add_user_fact`), the description should clarify that this retrieves facts previously stored by that tool. The term 'relevant' also raises unanswered questions about scoping or filtering that could confuse an 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?
The tool has zero parameters with 100% schema description coverage. Per the scoring rubric, this establishes a baseline score of 4. No additional parameter semantics are required or provided in the description, which is appropriate for this simple parameter-less getter.
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 'Get[s] relevant context about the user (facts, patterns, preferences)' and clarifies it 'retrieves stored facts.' It effectively distinguishes itself from sibling mutation tools like `add_user_fact` and task-management tools through the specific resource 'user context/facts' and the verb 'Get/retrieves.'
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 implicit guidance by stating the purpose is 'to help personalize responses,' suggesting when to invoke it (before generating personalized output). However, it lacks explicit guidance on when NOT to use it, prerequisites, or how it differs from `get_recommendation` or reading daily notes directly.
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 documents the return value ('Confirmation message') and crucially enumerates valid timeframe values (this_week, next_sprint, etc.) that the schema lacks as enums. However, it omits mutation details (overwrite behavior), error handling for invalid todo_ids, and side effects.
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 uses a structured docstring format with clear Args and Returns sections. The opening sentence is concise and specific. Every sentence serves a purpose given the lack of schema annotations, though the Returns section may be redundant if an output schema exists.
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 tool with zero schema description coverage and no annotations, the description adequately covers parameter semantics and valid values. However, given the presence of sibling batch operations and the potential for errors (invalid todo_id, invalid timeframe), the description lacks completeness regarding error states and operational constraints.
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?
Given 0% schema description coverage, the description compensates effectively by documenting all three parameters. Most critically, it provides the enumerated valid values for the 'timeframe' parameter that the schema only types as 'string', preventing invocation errors. The todo_id and reason descriptions are minimal but sufficient.
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 assigns a temporal timeframe to a todo using the specific verb 'Assign'. While it doesn't explicitly name sibling alternatives like batch_assign_timeframes, the singular 'todo' and specific verb distinguish it from batch operations and creation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as batch_assign_timeframes, or whether to set timeframe during initial todo creation with add_todo versus using this update operation. No prerequisites or constraints 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?
With no annotations provided, the description carries the full burden. It successfully communicates the destructive nature via 'permanently,' but omits other behavioral details such as error handling (e.g., what happens if the ID doesn't exist), cascading effects, or confirmation requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief and front-loaded. The main action is stated immediately, followed by a standard Args docstring section. No extraneous text is present.
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 single-parameter deletion tool, the description is minimally adequate. It notes the permanent nature of the operation. However, given the lack of annotations and schema descriptions, it could benefit from mentioning error cases or side effects, even though an output schema exists (excusing it from detailing return values).
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, so the description compensates via the Args block documenting 'todo_id: The ID of the todo to delete.' This provides necessary semantic context missing from the schema, though it could further clarify constraints (e.g., 'must exist').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and resource ('todo') with the modifier 'permanently' indicating irreversibility. However, it does not explicitly differentiate from the sibling tool 'complete_todo' (which likely marks items as done without removing them).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use deletion versus completion (complete_todo) or other alternatives. The description lacks 'when to use' or 'when not to use' instructions.
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?
Since no annotations are provided, the description carries the full burden. It discloses the filtering capability with specific enum values, implying a read operation. However, it omits safety confirmations (read-only nature), pagination behavior, or ordering of results despite the tool having an output schema.
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?
Front-loaded single sentence states the core purpose efficiently. The 'Args:' format is slightly unconventional for MCP descriptions but remains clear and wastes no words on the single parameter explanation.
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?
Adequate for a simple single-parameter list operation. The existence of an output schema (per context signals) excuses the lack of return value description in the text, and the parameter semantics are covered sufficiently for agent invocation.
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% (status property lacks description field). The description compensates effectively by documenting the valid enum values ('active', 'completed', 'all') and default behavior, though it redundantly repeats the default value already present 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 specific verb 'List' and resource 'todos' with scope 'filtered by status'. However, it does not explicitly differentiate from sibling 'list_goals' or clarify when to query todos versus other task-related entities.
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?
Provides no guidance on when to use this tool versus alternatives like 'list_goals' or 'brain_dump_tasks', nor does it mention prerequisites such as existing todos or daily note setup.
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?
Since no annotations are provided, the description carries the full burden. It explains that tasks are extracted and synced to 'the system,' implying a write side effect, but fails to disclose safety properties (destructive vs. safe), idempotency guarantees, or what 'sync' specifically entails (create, update, or delete operations).
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?
Well-structured with clear front-loading: a one-line summary, behavioral explanation, usage guidance, and Args section. No redundant or wasted sentences, though the 'Args' header could be omitted in favor of natural language integration.
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?
Adequately covers the input parameter and basic purpose given the output schema exists (excusing it from explaining return values). However, for a synchronization tool with implied side effects, the description omits important behavioral context like error handling, transactionality, or conflict resolution strategies.
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 fully compensates by documenting the single parameter in the Args section: it specifies the YYYY-MM-DD format and clarifies that it defaults to 'today' when omitted, adding critical semantic meaning absent from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'reads' and 'syncs tasks' using specific verbs, and clarifies it 'extracts tasks from your daily note and ensures they're in the system.' It distinguishes from pure reading tools (like read_daily_note_full) by emphasizing the syncing aspect, though it could better differentiate from the similarly-named sibling 'sync_daily_note'.
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?
Provides implied usage context ('Call this to refresh Coach AI's view of your daily note') which suggests when to invoke it. However, it lacks explicit guidance on when NOT to use it or which sibling tools to use instead (e.g., read_daily_note_full for non-syncing reads).
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 and successfully discloses the auto-population behavior (pulling yesterday's tasks, goals, quick wins). However, it omits critical mutation behavior: whether calling twice overwrites existing notes, appends, or errors.
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?
Well-structured with the primary action stated first, followed by bulleted auto-population details that earn their place, and ending with parameter specifics. The 'Args:' section is slightly informal but functional. No wasted sentences.
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?
Appropriate for the tool's complexity. Since an output schema exists, the description correctly focuses on input behavior and content generation logic rather than return values. Covers the essential auto-population features, though missing idempotency details.
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 (only 'title': 'Date Str'), and the description fully compensates by specifying the YYYY-MM-DD format, optional nature, and default behavior (today). This adds necessary semantic meaning missing from the structured 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?
Clear verb ('Create') and resource ('daily note') with specific mechanism ('smart population') that distinguishes it from manual section editing tools like write_daily_note_section. The bullet points clarify what 'smart population' entails, though it could explicitly differentiate from sibling 'start_my_day'.
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?
Implies usage context through the auto-population features (incomplete tasks, active goals), suggesting when to use it versus manual tools. However, lacks explicit 'when not to use' guidance or comparison to similar creation tools like 'start_my_day'.
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 burden. It adequately explains the fuzzy matching logic and return value ('Summary of tasks synced and any warnings about unmatched checkboxes'), but fails to disclose that this is a destructive write operation (modifying todo completion status) or clarify the unsupported 'bidirectional' claim.
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?
Structure is logical with Args/Returns sections, but the 'NEW TOOL' label is implementation noise that doesn't help agents. The 'Bidirectional sync' claim creates confusion since only the Obsidian→Database direction is described. Otherwise 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?
Adequate for basic operation: explains the matching behavior and output. However, lacks error handling details (what if daily note doesn't exist?) and the bidirectional claim remains unexplained. Given the complexity of fuzzy matching and file I/O, more behavioral context would be helpful.
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% (no descriptions in JSON schema), but the text compensates effectively via the 'Args' section documenting date_str as 'Optional date in YYYY-MM-DD format (defaults to today)'. Clear format specification and default behavior are provided.
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?
Excellent specificity: states the exact action (sync completed tasks), source (Obsidian daily note with markdown checkboxes - [x]), target (database), and mechanism (fuzzy matching). Clearly distinguishes from generic todo tools by specifying the Obsidian integration pattern.
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?
Provides workflow context ('Obsidian-first workflow: work in your daily note...then sync back'), implying when to use it. However, fails to differentiate from sibling tool 'sync_from_daily_note' which has a nearly identical name, risking incorrect 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?
With no annotations provided, the description carries the full burden. It successfully documents the append vs replace behavior and default date handling, but omits critical behavioral details like what happens if the section doesn't exist, whether the operation is idempotent, or specific error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Uses clear docstring format (Args/Returns) that efficiently organizes information. The first sentence establishes purpose immediately. Minor redundancy exists between the opening sentence and the 'Use this to...' sentence, but both add value (general action vs specific examples).
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 moderate complexity (4 parameters, 0% schema coverage, no annotations), the description adequately covers the parameter contracts and return value. It successfully explains the core mutation logic (append vs replace) necessary for safe invocation, though edge case behavior remains undocumented.
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?
Excellent compensation for 0% schema description coverage. The Args section documents all four parameters (section, content, date_str, append) with clear semantics, examples ('Notes', 'Coach AI Insights'), format specifications (YYYY-MM-DD), and default value explanations.
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 core action ('Write or append content') and target resource ('specific section in the daily note'). It implicitly distinguishes from sibling 'add_daily_note_section' by emphasizing writing/appending to existing sections rather than creating new ones, though an explicit contrast would strengthen this further.
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?
Provides concrete content examples ('summaries, insights, reflections') suggesting when to use the tool, but lacks explicit guidance on when to choose this over 'add_daily_note_section' or when to use append=True vs False. No prerequisites or error conditions 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 provided, so description carries full burden. Explains what content is analyzed (tasks, accomplishments, notes) and output format (insights, recommendations), but omits behavioral traits like whether this is read-only, idempotent, expensive/computationally heavy, or has side effects.
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?
Well-structured with clear Args/Returns sections. Front-loaded purpose statement. Slightly verbose second sentence ('Analyzes the day's tasks...') which repeats information implied by 'summary', but overall efficient with no wasted words.
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?
Appropriate for complexity: 1 optional parameter, output schema exists (so return value documentation in description is supplementary rather than required). Could improve by noting whether tool requires existing daily note or creates silently, but covers core functionality.
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 has 0% description coverage (only type/default). Description compensates effectively by specifying date format (YYYY-MM-DD) and default behavior ('defaults to today'), which schema only shows as null. Adds essential semantic meaning beyond raw schema fields.
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?
Clear specific verb 'Generate' + resource 'end-of-day summary'. Distinguishes from siblings like read_daily_note_full (raw reading) by emphasizing analysis/insights, and from write_daily_note_section by being a generation tool rather than direct writing.
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?
Provides implied usage context ('can be added back to the daily note or used to plan tomorrow'), but lacks explicit when-to-use guidance versus alternatives like read_daily_note_full or start_my_day. No mention of prerequisites (e.g., whether daily note must exist).
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 disclosure burden. It mentions the return value ('Summary of updates') and shows input format via the example, but omits critical behavioral details such as error handling (partial vs atomic failures), overwrite behavior, 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 is excellently structured with clear sections (purpose, Args, Example, Returns) and zero wasted words. Information is front-loaded with the core purpose, followed immediately by the parameter specification and illustrative example.
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 single complex parameter and existence of an output schema, the description provides sufficient context through the JSON example to enable correct invocation. However, it lacks enumeration of valid timeframe strings or error behavior details that would make it fully complete for a batch mutation operation.
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%, requiring the description to compensate. It successfully documents the JSON structure through the Args section and concrete example, clarifying that assignments_json contains objects with todo_id and timeframe keys. It does not enumerate valid timeframe values, preventing a perfect 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 states 'Bulk assign timeframes to multiple todos' with the specific context '(for weekly planning)'. The term 'Bulk' effectively distinguishes this from the sibling tool 'set_todo_timeframe', indicating this handles multiple items in one operation.
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 contextual usage via '(for weekly planning)', but does not explicitly state when to use this versus the singular 'set_todo_timeframe' or mention prerequisites like valid todo_id requirements. The guidance remains implied 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?
With no annotations provided, the description carries the full burden. It discloses the database mutation ('create the subtasks in the database') and LLM dependency ('Use LLM'), plus the unusual two-call behavioral pattern. However, it lacks details on error handling, idempotency concerns, or what happens if the todo_id doesn't exist.
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 uses clear structural sections (Workflow, Args, Returns) that front-load the most critical information. The 4-step workflow is necessary given the tool's complexity. Only minor redundancy exists in describing the return value when an output schema is present, but this is justified given the 0% schema coverage elsewhere.
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 (two-phase LLM interaction with database mutations), the description adequately covers the invocation pattern, parameters, and return behavior. While it mentions the output schema exists, it appropriately documents the dual return type (prompt vs confirmation) given the poor schema coverage, providing sufficient context for correct 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?
The schema has 0% description coverage (no descriptions on properties), but the description compensates with an 'Args:' section that documents both todo_id ('ID of the task to break down') and subtask_count ('Target number of subtasks (default: 5)'). It adds the semantic meaning missing from the schema structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool uses an LLM to 'decompose large task into smaller subtasks,' specifying the verb, resource, and method. It distinguishes itself from sibling tools like add_todo by emphasizing the AI-driven decomposition aspect, though it could clarify what constitutes a 'large' task warranting this treatment.
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 provides explicit workflow guidance with a numbered 4-step process: call tool to get prompt, send to Claude, receive JSON, and automatic database creation. It clearly explains the two-phase invocation pattern (first call returns prompt, second call creates subtasks), which is critical for correct sequencing.
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 value structure ('Full note content with metadata and all sections') and default parameter behavior ('defaults to today'). However, it omits error handling (what happens if the note doesn't exist?), side effects, or performance characteristics.
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 efficiently structured with a clear opening statement, followed by value proposition, then explicit Args and Returns sections. Every sentence earns its place 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?
Given that an output schema exists (per context signals), the brief return description is sufficient. The single optional parameter is well-documented in the description. It could be improved by mentioning error cases (e.g., missing notes) or authentication requirements.
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 date_str property lacks a description field), the description adequately compensates by specifying the format ('YYYY-MM-DD') and default behavior ('defaults to today'). It successfully adds necessary semantic meaning missing from the structured 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 clearly states the tool 'Read[s] the entire daily note including all content and sections' — specific verb (Read) + resource (daily note) + scope (entire vs partial). The phrase 'complete access' and 'all sections' effectively distinguishes it from the sibling 'read_daily_note_section'.
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 use cases ('analysis, summarization, or extracting information'), implying when to use it. However, it lacks explicit guidance on when NOT to use it versus the sibling 'read_daily_note_section' for targeted section access, or prerequisites like note existence.
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 input format constraints (YYYY-MM-DD, 'without ## or emoji') and the return value, but omits error handling (what happens if the section doesn't exist?), side effects, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a one-line summary, usage context, Args block, and Returns block. No redundant information; every sentence adds value beyond the structured fields.
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 two-parameter read operation with an output schema available, the description is adequate. It compensates well for the schema's lack of descriptions, though it could be improved by mentioning error conditions or the 'Notes' default value.
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?
Despite 0% schema description coverage, the Args section effectively documents both parameters: date_str includes format and default behavior ('today'), and section includes formatting constraints. Deducted one point for failing to document that the section parameter defaults to 'Notes'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read') and resource ('specific section from the daily note'), distinguishing it from sibling tools like read_daily_note_full. Concrete examples ('Notes', 'Tasks', 'Focus for Today') further clarify the 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?
While it provides examples of valid section names, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'use read_daily_note_full to retrieve the entire note'). The usage guidance is implied but not directive.
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 burden and effectively discloses auto-categorization behaviors (theme detection from keywords, time extraction from notes, quick win detection). However, it omits transactional details like idempotency or error handling behaviors.
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?
Well-structured with clear sections, but contains significant redundancy between the 'New fields' bullet section and the 'Args' parameter definitions. The auto-categorization list could also be more compact.
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?
Thoroughly covers both single and batch input modes for the 10-parameter tool. Given the existence of an output schema (per context signals), the description appropriately focuses on input semantics, though it could briefly mention validation constraints.
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% (no parameter descriptions in schema), but the Args section comprehensively documents all 10 parameters including valid enum values for timeframe, energy_required, and theme_tag, fully compensating 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 'Add todo(s)' with specific resource identification and distinguishes from siblings like complete_todo or delete_todo by emphasizing 'enhanced temporal and context fields' and structured data entry.
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?
Clearly delineates internal usage patterns (SINGLE MODE vs BATCH MODE) with specific parameter requirements for each, but fails to differentiate from sibling alternatives like brain_dump_tasks or parse_task_list which also handle task creation.
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 provided, so description carries full burden. Effectively discloses parsing behavior (multiple formats supported), extraction logic (smart detection of #high, [30min], etc.), and batch mutation behavior ('Create todos immediately'). Lacks error handling details or rate limits, but strong on functional behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Lengthy but well-structured with clear headers (Workflow, Supports multiple formats, Smart extraction, Example). Information-dense given complexity; the example code block efficiently demonstrates syntax. Minor verbosity in format examples is justified by 0% schema coverage.
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?
Comprehensive for a complex NLP tool: covers input formats, extraction patterns, parameters, and return value (summary with suggestions). Output schema exists per context signals, so brief return description is appropriate. Could strengthen by mentioning relationship to delete_todo for undoing batch creations.
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 (titles only). Description fully compensates via 'Args' section documenting all 4 parameters: text (natural language task list), auto_create (immediate creation toggle), and defaults for priority/timeframe. Critical for agent to understand 'auto_create' controls the destructive/creation behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Opens with specific value proposition ('ADHD-friendly brain dump') and core mechanism ('paste a list of tasks and get them into the system'). Distinguishes from siblings like add_todo (single task) and parse_task_list via emphasis on bulk creation, natural language parsing, and smart metadata extraction (priority, timeframe, energy).
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?
Implies usage context through 'ADHD-friendly' and workflow description (bulk unstructured input vs. careful single entry), but lacks explicit when-to-use guidance distinguishing it from parse_task_list or add_todo. No mention of prerequisites or when auto_create should be false.
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 implies a read-only operation but does not clarify critical behavioral details: does it verify file existence or merely construct a path? Does it return an error if the note is missing? The mention of 'checking if it exists' hints at validation logic that is left undefined.
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?
Well-structured with clear separation: one-line purpose statement, usage context, and Args block. Information is front-loaded with no 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?
Given the tool has an output schema (not shown but indicated) and only one optional parameter, the description is appropriately complete. It covers the essential behavioral context for a simple path-retrieval tool, though it could explicitly state that it returns the path without creating the file.
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 fully compensates by specifying the date format ('YYYY-MM-DD') and default behavior ('defaults to today'), providing essential semantic information absent from the structured 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 uses a specific verb ('Get') with a clear resource ('file path to today's...daily note'), explicitly distinguishing this from sibling tools like create_daily_note (which creates) and read_daily_note_full (which reads content).
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?
Provides concrete use cases ('opening the note in Obsidian', 'checking if it exists') that signal when to invoke the tool. However, it does not explicitly name alternatives like read_daily_note_full or clarify when to prefer this over other daily note operations.
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 successfully discloses what data sources are analyzed (todos, goals, recent activity, known facts), but fails to explicitly confirm whether this is read-only, if it updates any internal state, or details about the recommendation format.
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?
Three sentences efficiently structured: first defines the action, second explains the analytical mechanism, third provides the user-centric value proposition. No redundant or wasted text.
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 zero parameters and the presence of an output schema (which handles return value documentation), the description adequately explains the business logic and data sources. It could be improved by explicitly stating the read-only nature given the lack of annotations, but it is sufficiently complete for selection and invocation.
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 zero parameters, which per the guidelines establishes a baseline of 4. The description adds value by explaining what implicit inputs are considered (current todos, goals, etc.), providing context that compensates for the empty parameter set.
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[s] a personalized recommendation' and distinguishes it from CRUD siblings (add_todo, list_todos, etc.) by specifying it synthesizes todos, goals, recent activity, and known facts to suggest the next action. The scope and mechanism are specific 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context ('What should I do now?', 'decision paralysis') that signals when to invoke this over simple list operations. However, it lacks explicit 'when not to use' guidance or named alternatives (e.g., when to use list_todos vs. this 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?
No annotations are provided, so the description carries the full disclosure burden. It mentions the return value ('Confirmation message'), but fails to clarify critical behavioral traits like whether this operation overwrites existing weekly themes, merges with them, or validates the Monday date constraint beyond the parameter description.
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 well-structured with clear Purpose-Args-Returns sections. While the docstring format is slightly more verbose than pure prose, it efficiently packs necessary parameter documentation without redundant language. Front-loading is effective with the main purpose 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?
Given the tool has 3 parameters, no annotations, and an output schema, the description successfully covers the purpose, all parameters with examples, and the return type. The only gap preventing a 5 is the lack of behavioral context regarding side effects or persistence semantics.
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?
With 0% schema description coverage, the description fully compensates by documenting all three parameters in the Args section: it specifies formats (YYYY-MM-DD, JSON object, comma-separated), provides concrete examples for themes_json, and notes optionality for focus_todo_ids.
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 specific action verbs ('Configure', 'Sets') and clearly identifies the resource (work themes for days of the week). It effectively distinguishes itself from sibling tools by explicitly stating it 'influences task selection in start_my_day()', establishing a clear functional relationship.
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?
Provides clear context by linking the tool's output to 'start_my_day()' consumption, helping the agent understand the workflow relationship. However, it lacks explicit temporal guidance (e.g., 'use at the beginning of the week') or exclusions (when not to use it).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 explains what the tool returns (suggested focus items, themes, summaries) but fails to disclose whether this tool is read-only, modifies existing todos/notes, or creates side effects. It doesn't clarify if calling it multiple times is safe or idempotent.
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 well-structured with a clear opening statement, bulleted outputs, and labeled sections (Args, Returns). While slightly verbose with the bullet list, every element earns its place by clarifying the tool's deliverables. Front-loading is effective with the ritual definition first.
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 has an output schema (mentioned in context signals), the description appropriately summarizes rather than duplicates return value details. It adequately covers the single optional parameter and explains the complex aggregation behavior (pulling last week's data, generating suggestions) for a planning tool of this type.
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 0% description coverage (no property descriptions). The description fully compensates by documenting the single parameter with format details ('YYYY-MM-DD'), semantic constraints ('Monday date'), and default behavior ('defaults to next Monday'), providing complete guidance beyond the 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 clearly defines the tool as a 'Weekly planning ritual' with specific actions (review last week, plan this week). It distinguishes itself from sibling 'start_my_day' through explicit weekly scope and detailed outputs (strategic vs sprint breakdown, daily themes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage cues ('Perfect for: "Plan my week" or "Weekly review"'), implying when to invoke it. However, it doesn't explicitly contrast with sibling 'start_my_day' or state when NOT to use this versus other planning 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?
With no annotations provided, the description carries the full burden and discloses significant behavioral details: side effects (syncs yesterday's completed tasks, creates today's note), algorithm specifics (deterministic selection of 1 critical + 1-2 important + 2-3 quick wins), and return type (briefing). Deducted one point for missing edge case disclosure (idempotency, behavior when run multiple times, or overwrite logic if note 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?
Well-structured with clear sections: workflow overview, algorithm details, usage examples, and argument documentation. The bullet points for the selection algorithm are dense with useful information. Minor deduction for marketing language ('ENHANCED - Obsidian-first') that adds limited technical value, though the overall density is high with minimal waste.
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 (multi-source data aggregation, algorithmic selection, document creation, briefing generation) and lack of annotations, the description provides sufficient operational context. Since output schema exists (per context signals), the brief return description is adequate. Minor gap regarding existing daily note handling (append vs. overwrite) prevents a 5.
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% (date_str has no description in schema), but the description compensates adequately by specifying 'Optional date in YYYY-MM-DD format (defaults to today)'. This provides the essential technical specification missing from the schema, though it could enhance value by explaining use cases for non-default dates (backdating, future planning).
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 explicitly states the tool performs 'smart task selection and daily note creation' using a specific deterministic algorithm. It clearly distinguishes from siblings like 'create_daily_note' (simple creation vs. intelligent selection) and 'list_todos' (viewing vs. curating) by detailing the multi-step workflow involving yesterday's sync, backlog analysis, and priority-based organization.
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?
Provides explicit positive guidance with 'Perfect for: "Start my day" or "What should I focus on today?"' giving clear invocation signals. However, lacks negative constraints (e.g., when to use 'create_daily_note' instead for empty notes) or explicit sibling comparisons despite having many related tools like 'start_my_week' or 'generate_daily_summary'.
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 provided, so description carries full burden. Discloses critical safety trait 'does NOT create them,' explains extraction capabilities (priority, timeframe, energy patterns), and specifies return type 'JSON string of parsed todos.' Could mention error handling for malformed input.
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?
Well-structured with clear sections (purpose, usage, formats, extraction, Args, Returns). Examples of supported formats are valuable and necessary for a parser tool. Slightly verbose but every sentence earns its place by clarifying extraction patterns or workflow context.
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?
Despite having output schema, description appropriately explains return values given no annotations. Covers parsing behavior, workflow integration with sibling tools, and parameter semantics comprehensively. Minor gap: doesn't mention error cases or size limits for the text parameter.
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% (no descriptions in schema), but tool description compensates by documenting all 3 parameters: 'text: Natural language task list,' 'default_priority: Default priority,' 'default_timeframe: Default timeframe.' Also enriches 'text' parameter with extensive format examples (bullet points, checkboxes, etc.).
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 specific action 'Parse natural language task list into structured todos' and explicitly distinguishes from siblings with '(does NOT create them)', immediately clarifying it differs from add_todo and brain_dump_tasks.
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?
Provides explicit workflow guidance: 'Use this to preview what will be created before committing,' names specific next step 'use add_todo(todos_batch=...) to create them,' and offers alternative 'use brain_dump_tasks() for a one-step workflow.'
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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