Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It discloses directional behavior and inverse link creation via bidirectional, and details link type semantics. However, it omits preconditions (e.g., notes must exist), error behavior, and side effects on the notes, which is a notable gap for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized into clear sections: overview, link types, best practices, and args. Every sentence serves a purpose, and the link type enumeration is necessary for correct usage. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With five parameters, no annotations, and no output schema, the description covers the core aspects: purpose, parameter semantics, and usage guidance. However, it doesn't mention what the tool returns (e.g., created link ID) or state that source and target notes must already exist. These omissions slightly reduce completeness for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is the sole explainer. The 'Args' section gives explicit meanings for all five parameters, and the 'Link Types' section elaborates each allowed value for link_type. This is far more informative than the schema's bare titles and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Create a semantic link between two notes,' clearly identifying the action and object. It distinguishes this tool from sibling tools like slipbox_remove_link and slipbox_get_linked_notes by focusing on creation. The directional semantics and link type list further clarify its specific purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'Best Practices' section provides actionable guidance: always add a description, use bidirectional=true for substantive relationships, and create links immediately after notes. However, it doesn't explicitly state when not to use this tool or mention alternatives (e.g., other link-related tools), so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does so well. It discloses key traits: atomicity ('exactly one idea'), content preservation ('Store content exactly as the user provided it. Do NOT rewrite'), and note-type-specific requirements (literature requires references or use fleeting). It stops short of describing error/duplicate behavior, but the disclosed rules are substantial and useful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long but well-organized with clear sections: intro, note types, authoring, best practices, and Args. Every section adds substantive value, and the front-loaded purpose makes the tool's role clear immediately. Slight verbosity exists (e.g., note type bullet details), but it is structured and scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 params, multiple note types with special rules) and no output schema, the description covers all necessary usage aspects: note type definitions, references requirement, authoring constraints, best practices, and parameter documentation. It is sufficiently complete for an agent to invoke the tool correctly without additional external knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions (0% coverage), but the description's 'Args:' section explains every parameter with meaning, defaults, and format examples (e.g., tags: 'poetry,revision,craft'). This fully compensates for schema gaps and adds rich detail that the raw schema lacks.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Create a new atomic Zettelkasten note.' It clearly distinguishes creation from sibling tools by explicitly referencing slipbox_create_link and slipbox_search_notes and by outlining note-type semantics. This is unambiguous and action-oriented.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides strong when-to-use guidance: 'Search first (slipbox_search_notes) to avoid duplicating existing notes' and 'After creating, immediately link to related notes using slipbox_create_link.' It also explains conditional usage for note types (e.g., using 'fleeting' as a staging type when references are missing), which helps the agent choose the correct type of creation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full transparency burden. It discloses the core behavior (creating a structure note, organizing cluster notes, and creating bidirectional links), which is valuable. However, it does not mention edge cases (e.g., what happens if the cluster ID is invalid), permissions, or whether the operation is reversible, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a clear one-line purpose, a brief expansion of what it does, a key prerequisite, and a compact Args list. All sentences contribute value, and it is appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides the essential context: what the tool creates, how links work, and the prerequisite. With no output schema and no annotations, it could further describe the return value or error behavior, but for a creation tool it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero descriptions, so the description fully compensates by explaining each parameter: cluster_id with an example, title as an override, and create_links with its default behavior. This adds significant meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Create a structure note from a detected cluster.' It clarifies the tool's function (organizing cluster notes, creating bidirectional links) and is distinct from siblings like slipbox_create_note or slipbox_get_cluster_report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to run slipbox_get_cluster_report first to see available clusters and IDs, providing clear context on when to use this tool. While it does not enumerate alternatives or exclusions, the prerequisite guidance is strong, so it earns a 4.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden of disclosure. It adds the behavior that an error is returned if no link exists, which is beyond the schema. However, it doesn't mention other behavioral aspects like reversibility or side effects on notes, so it's minimal but not inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus a minimal Args block, with no filler or redundant information. It front-loads the purpose and then gives the key differentiator.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (two params, no output schema), the description covers the purpose, parameter semantics, and key behavioral distinction. It is sufficient for a focused tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides only names and types, with 0% description coverage. The description's Args section explains that source_id is the note containing the link and target_id is the note being linked to, adding necessary semantic meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Delete a specific link from one note to another,' which clearly states the verb, resource, and scope. The 'Unlike slipbox_remove_link' sentence distinguishes it from the closest sibling, clarifying its specific behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly contrasts with slipbox_remove_link by noting the error-on-missing-link behavior, which guides the user on when to choose this tool over the alternative. This is a clear usage guideline, though it doesn't mention other tools or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that deletion is permanent and also removes all links to and from the note. This is critical behavioral information beyond the basic delete action, making the tool's effects transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: main action first, followed by a warning and alternative suggestion, then a simple args list. Every sentence provides useful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple delete operation with one parameter and no output schema, the description covers the core action, the permanent effect, cascading link removal, and an alternative. This is sufficiently complete for an agent to select and invoke the tool appropriately, given the sibling context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. However, the only parameter documentation is 'note_id: The ID of the note to delete', which merely restates the parameter name without adding meaningful semantic detail (e.g., format, how to obtain the ID, or constraints). This adds minimal value over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Delete a note permanently' with a specific verb and resource. It also differentiates from the update alternative by suggesting 'updating note_type to fleeting' for uncertain cases, which distinguishes it from sibling tools like slipbox_update_note.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to avoid this tool: 'Consider updating note_type to fleeting instead if uncertain.' This clearly tells the agent when not to use deletion and points to an alternative action, serving as a usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. It discloses the key behavioral trait: the action is 'Permanently' dismiss, implying irreversibility. It also specifies the effect on maintenance suggestions. It does not detail other side effects, but for a simple dismiss action this is sufficient and adds meaningful context beyond the name/schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the first sentence states the action, the second gives usage context, and the final part documents the parameter. Every sentence adds value without unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one parameter, no output schema), and the description covers purpose, usage, and parameter meaning. It is sufficiently complete for an agent to select and invoke the tool correctly without ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides only 'cluster_id' with a type and title, with 0% description coverage. The description compensates by explaining what the parameter is: 'The cluster ID to dismiss' and provides a concrete example ('poetry-craft-revision'). This gives the agent a clear understanding of the expected format and semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear, specific verb+resource: 'Permanently dismiss a cluster from maintenance suggestions.' This clearly distinguishes it from sibling tools like refresh_clusters or create_structure_from_cluster. The purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'when a cluster has been reviewed and determined not to need a structure note, or when the user doesn't want to be reminded about it.' This gives concrete scenarios and implicitly tells when not to use it (when a structure note IS needed), differentiating it from alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 explains that centrality is based on incoming and outgoing links, but does not disclose whether the operation is strictly read-only, what the return format is, or any prerequisites (e.g., indexed notes). This is adequate for a simple query but leaves some behavioral aspects implicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: a one-sentence purpose, a brief definition of 'central', and an Args block. Every sentence adds value with no repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description explains what the tool does and what 'central' means, but it does not describe the output format (e.g., list of note IDs vs. notes with scores) or any dependencies like an index. While the main use case is clear, the return behavior is not specified, leaving a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explicitly documents the only parameter 'limit' as 'Maximum results (default: 10)', which fully clarifies its purpose and default value. Since the schema itself provides no description and has 0% coverage, the description compensates completely for this gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Find the most connected notes in the Zettelkasten.' It uses a specific verb ('find'), resource ('notes'), and scope ('most connected'), and distinguishes itself from sibling tools like find_similar_notes and find_orphaned_notes by focusing on connectivity/hub status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for use: 'Good candidates for hub notes' implies the tool is for identifying pivotal notes in the knowledge network. It does not explicitly name alternatives or exclusions, but the context is unambiguous and sufficient for basic selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of conveying behavioral traits. 'Find' implies a read-only operation, and the description adds context about why orphaned notes matter and what to do with them. However, it does not explicitly state safety (e.g., no modifications) or output format, leaving some ambiguity for a zero-parameter tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, tightly written with no fluff. The first sentence states the purpose, and the second adds valuable context and guidance. Every sentence earns its place, making it exceptionally concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only tool with no output schema, the description is complete. It states what it finds, why it matters, and when to use it. No further details are necessary for an agent to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema covers everything. According to the baseline rule for 0 params, a score of 4 is appropriate. The description adds no parameter info (correctly, as there are none).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Find') and resource ('notes with no connections to other notes'). It distinguishes itself from sibling tools like find_similar_notes and find_central_notes by defining 'orphaned' explicitly, leaving no ambiguity about what it does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context ('Review these periodically') and suggests follow-up actions (link or delete). However, it does not mention alternatives or when-not-to-use, so it falls short of the highest bar which requires explicit exclusions or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the transparency burden. It discloses the algorithm (shared tags, links, content overlap), the meaning of threshold (minimum similarity 0.0-1.0), and the limit parameter behavior. It does not describe return format or edge cases, but these are relatively minor for a read-only similarity finder.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then provides the similarity basis, a use-case sentence, and a compact Args list. Every sentence earns its place; there is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup tool with no output schema, the description covers purpose, algorithm, and all parameters. It does not state the return format or sorting order, but given the tool's low complexity and clear parameter explanations, the description is sufficiently complete for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully compensate. It does: note_id is 'ID of the reference note', threshold is 'Minimum similarity score 0.0-1.0 (default: 0.3)', and limit is 'Maximum results (default: 5)'. This adds crucial meaning absent from the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Find notes similar to a given note', which uses a specific verb ('Find') and resource ('notes') and clearly distinguishes this from search, central, or orphaned note tools. The similarity basis (shared tags, common links, content overlap) further clarifies its exact role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The line 'Useful for discovering connections you might have missed' gives clear context for when to use this tool. It does not explicitly name alternatives or state when not to use it, but the context is strong enough to guide tool selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the behavior of returning an alphabetically sorted list, which is a useful behavioral trait. It does not explicitly state side effects, but for a getter tool, the absence of mutation is implied, and the description adds value beyond the bare 'Get all tags' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each earning its place: the first states the purpose, the second describes the output, and the third gives usage context. It is front-loaded with the core action and contains no redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple getter with no output schema, the description adequately explains what the tool returns (alphabetically sorted list) and why to use it. It covers the essential contextual information for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema is completely covered (100%). The description adds no parameter information because there are none to explain. Baseline for zero parameters is 4, which is appropriate here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'all tags in the Zettelkasten', with a specific detail that the list is alphabetically sorted. It distinguishes itself from sibling tools by focusing solely on tag retrieval, which none of the other siblings do directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context: 'Use this to find existing tags before creating new notes to maintain tag consistency.' It gives a clear when-to-use scenario but does not mention when-not-to-use or name alternatives, as there are no direct sibling alternatives for this function.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses caching (uses cached analysis by default, refresh=true to regenerate), cron behavior, and scoring factors. This is strong, but it omits potential performance implications of refresh or any side effects, leaving a minor transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized: a clear one-line purpose, a brief explanation of clusters, a bulleted list of scoring factors, and a concise Args block. Every sentence adds value and the structure makes scanning easy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives strong context (what clusters are, how scoring works, defaults, refresh semantics) and implies return structure via parameters like limit and include_notes. However, without an output schema, it doesn't fully describe the returned cluster objects, leaving some ambiguity about the exact fields returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description fully compensates by defining each parameter with type, default, and purpose (min_score, limit, include_notes, refresh). This is exactly what an agent needs to invoke the tool correctly and goes beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Get pending cluster analysis for structure note creation.' It clearly distinguishes from siblings like slipbox_create_structure_from_cluster (which creates) and slipbox_refresh_clusters (which refreshes) by focusing on retrieval of pending analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains the intended use case: high-scoring clusters are good candidates for new structure notes. It also provides context on cached vs refresh behavior and cron automation. However, it doesn't explicitly name alternatives or say when *not* to use this tool, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It explains the direction modes (outgoing, incoming, both) which is helpful, but it omits return format, pagination, error handling, or whether links are recursive. This is a moderate level of transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-organized, using bullets for directions and a clear Args block. Every sentence contributes useful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with two simple parameters and no output schema, the description covers purpose, usage context, direction semantics, and parameter meaning. It lacks details on the return structure or possible failures, but is reasonably complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It does so in the 'Args' section, defining note_id as 'ID of the note to explore from' and direction as 'One of outgoing/incoming/both (default: both)'. This adds clear meaning beyond the bare schema fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Get notes linked to or from a specific note.' This specifies both the verb and the resource, and it distinguishes the tool from sibling tools like search_notes or find_similar_notes by focusing on graph links.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The line 'Use this to explore the knowledge graph around a note' provides clear use-case context. It doesn't explicitly mention alternatives or when not to use it, but the primary scenario is well communicated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does disclose return content ('full note content including metadata, tags, and links') and identifier semantics ('either the note ID ... or exact title'). However, it does not mention behavior on non-existent notes or potential ambiguity between ID and title formats, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, starting with the primary purpose, then outlining return value and usage. The Args section is clear and every sentence serves a purpose with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (single parameter, no output schema), the description covers the core aspects: what it does, how to use the parameter, what to expect in return, and when to use it. Missing details about error handling are minor for a retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no description for the parameter, so the description compensates by explaining that 'identifier' can be either a note ID (with example) or an exact title. This adds meaningful semantics beyond the raw schema field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Retrieve a note by ID or title', which is a specific verb and resource. It distinguishes from sibling tools like search, update, and delete by specifying a read operation for a single note.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit guidance: 'Use this to read note contents before creating links or updates.' This gives a clear context for when to use the tool, though it does not mention alternatives or when not to use it, such as for searching by keywords.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the safety and behavior burden. It discloses the core behavior: filtering by created_at or updated_at via the use_updated flag, with defaults for limit. It also clarifies that dates are optional, implying unfiltered listing when omitted. No destructive side effects are implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: a one-line summary, a usage note, and a structured list of arguments. No redundant text or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool, the description covers the purpose, usage context, all parameters with defaults and format, and the alternative date field. It could mention ordering or behavior with no dates, but these are implicit. Overall it is sufficiently complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates by explaining each parameter: start_date and end_date in ISO format, use_updated as a filter switch, and limit as maximum results with defaults. This is exactly what an agent needs to invoke the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'List notes by creation or update date,' a specific verb and resource, clearly distinguishing from siblings like search_notes or get_note. It explicitly describes the date-based filtering functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'Useful for reviewing recent work or finding notes from a specific period,' providing clear use-case context. It does not explicitly name alternative tools or mention when not to use it, but the guidance is sufficient for a straightforward list tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden for behavioral disclosure, but it only states the action and a trigger condition. It does not disclose whether the rebuild is destructive, what side effects it has, or what the outcome looks like (e.g., whether it overrides existing index state or updates in place).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences. The first states the action, and the second provides the when-to-use guidance. No filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema), the description covers the essential context: what it does and when to use it. It could mention potential side effects or whether it is safe to run, but for a straightforward rebuild operation it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline for parameter semantics is 4. The description adds no parameter-specific details, but none are needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Rebuild the database index from markdown files') with a specific verb and resource, distinguishing it from sibling tools like refresh_clusters or get_note.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use the tool: if notes were edited outside the MCP server or if the database seems out of sync. It provides clear context but does not mention exclusions or alternative tools, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must carry the behavioral disclosure burden. It states that the tool regenerates analysis and saves to a file, implying a write operation. The specific output path is given, but it does not mention whether it overwrites the existing file, whether it is idempotent, or any potential side effects. There is no explicit statement about mutation or reversibility.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a one-sentence purpose followed by a bulleted list of analysis criteria. Every sentence earns its place, with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-argument tool with no output schema, the description covers the purpose, input data, analysis dimensions, and output file. It does not explicitly describe the report format or return value, but saving to a file is sufficiently clear. The sibling tools (get_cluster_report, create_structure_from_cluster) provide additional context for how the output is used.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description adds value by explaining the implicit inputs: all notes, tags, connections, and structure note coverage. This gives meaning beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Regenerate cluster analysis and save report', which is a specific verb+resource. It further details the analysis criteria (tag co-occurrence, connection patterns, structure note coverage), and the output path. This distinguishes it from sibling tools like get_cluster_report, which likely reads the existing report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: it analyzes all notes and saves a report, implying it is used to refresh cluster data. However, it does not explicitly mention when to use it instead of alternatives like get_cluster_report or after specific changes. The when-not guidance is implicit rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description must disclose behavioral details. It explains the 'bidirectional' parameter but does not mention side effects such as error behavior when the link does not exist, whether the operation is reversible, or permission requirements. This is a notable gap for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured with an Args block that lists each parameter. It avoids unnecessary verbosity and is appropriately sized for a simple tool with three parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple, and the description covers the basic functionality and the meaning of the bidirectional flag. However, it omits critical context such as how it differs from slipbox_delete_link, whether missing links cause errors, and any effects on the underlying notes. Given no output schema or annotations, the description is not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides brief explanations for each parameter ('ID of the source note', 'ID of the target note', 'If true, removes links in both directions'), which adds some meaning beyond the bare schema types and titles. However, the explanations are fairly obvious and do not deeply elaborate on formats or edge cases, so it does not fully compensate for the 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Remove a link between two notes' with a specific verb and resource, clearly indicating the action. However, it does not distinguish itself from sibling tool slipbox_delete_link, which likely performs a similar function, so it earns a 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 slipbox_delete_link or slipbox_create_link. The description lacks any context about prerequisites, alternatives, or conditions for appropriate use, so it provides minimal usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses search scope (titles and content), tag format (comma-separated), note_type allowed values, and limit default. However, it does not describe result ordering, case sensitivity, or return format, which is a notable gap for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an intro, behavior statement, bulleted examples, and a clean parameter list. Every sentence provides useful information with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

All parameters are documented with examples and defaults, which is sufficient for invocation. However, because there is no output schema, the description would be more complete if it briefly mentioned the return shape (e.g., list of matching notes). Overall it is solid but missing that piece.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The Args section fully explains all four parameters with clear descriptions, example values, and the allowed note_type list. Since schema coverage is 0%, this completely compensates and gives the agent everything needed to invoke the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the specific verb 'Search' and resource 'notes' with three filter dimensions (text, tags, type), and adds scope detail ('Searches across titles and content'). This clearly distinguishes it from sibling tools like find_similar_notes or list_notes_by_date.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides concrete usage examples and explicitly says parameters can be combined for precise filtering. However, it does not mention when to prefer this over alternatives or explicitly state when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It explicitly states partial updates (only provided fields change), how to clear fields via empty strings, and the literature promotion constraint. This goes well beyond a vague 'update' and covers key behavioral traits, though it doesn't mention error handling or return values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a short introductory paragraph and a clear Args list. It's slightly long due to necessary parameter explanations, but every sentence earns its place. The front-loaded update semantics and clearing behavior are immediately clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description covers the essential aspects: update semantics, field clearing, and the literature constraint. It lacks mention of errors or return values, but the provided information is sufficient for safe and correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero description coverage, but the description includes an Args section that explains each parameter, including formats (comma-separated tags, newline-separated references) and optionality. This adds substantial meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates an existing note, using the specific verb 'Update' and the resource 'an existing note'. It distinguishes itself from siblings like create or delete by focusing on modification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for modifying existing notes, and provides a specific constraint for literature notes (must have at least one reference). It doesn't explicitly contrast with create/delete, but the context is clear and the constraint gives actionable guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.