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 core filtering behavior (based on recent opening) but does not mention whether the operation is read-only, what output format to expect, or any limitations (e.g., based on last opened vs. last modified). This is adequate but leaves room for more 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 two sentences, front-loaded with the core function, and every word adds value. It is 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?

The tool has a single parameter, no output schema, and minimal annotations. The description covers the 'what' and 'why' but omits the return value and any edge cases. Given the tool's simplicity, it is sufficient but not complete—missing output expectations makes it a 3.

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 100%: the only parameter 'days' has a clear description with default value. The tool description adds no extra parameter semantics but aligns logically with the schema's meaning of 'recently'. Baseline of 3 is appropriate.

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: finding workspaces not opened recently. This specific verb+resource+condition distinguishes it from siblings like list_workspaces (lists all) or get_workspace (fetches a specific one), making its purpose unambiguous.

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

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

The phrase 'Useful for identifying abandoned or forgotten projects' provides clear context for when to use this tool. It does not explicitly name alternatives or exclusions, but the use case is well implied, earning a 4 rather than 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 exist, so the description carries behavior disclosure. It reveals that the tool returns aggregated counts, per-workspace breakdown, and totals, and that parent filtering scopes results. It does not specify output format, default status handling, or empty-workspace behavior.

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?

Two focused sentences: first states core function, second explains filtering. 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 two-parameter read-only aggregation with no output schema, the description covers purpose, scope filter, and return summary. It could mention output shape/edge cases, but it is adequate for selection and basic 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?

Input schema already describes both optional parameters (parent, status) with 100% coverage. The description adds only the same parent-prefix example already in the schema, so no significant semantic value beyond structured 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?

Clearly states it aggregates beads task counts across multiple workspaces and provides a per-workspace breakdown/totals, distinguishing it from sibling list_beads via the across-workspace aggregation scope.

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?

Gives clear usage context: use for aggregation across multiple workspaces and scope via parent prefix or omit for all. Does not explicitly contrast with sibling tools like list_beads or summarize_all, so not 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 clearly indicates a read-only operation ('Get') and discloses the return content by listing what status information is included. It does not cover error behavior or auth, but for a simple status tool this is reasonably complete.

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 a single sentence that front-loads the core purpose and immediately lists the relevant details. There is 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?

With only one parameter and no output schema, the description provides a useful summary of the return fields (git status, saved tabs, tab history, notes, staleness). It is sufficient for understanding what the tool will deliver, though it could have added a note about error cases or when not to use it.

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 input schema already documents the only parameter 'name' with description and examples, giving 100% schema coverage. The tool description does not add extra parameter meaning beyond referring to a 'specific workspace', so the baseline of 3 is appropriate.

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 uses a specific verb ('Get') and resource ('detailed status of a specific workspace') and lists the status categories (git status, saved tabs, tab history, notes, staleness). This clearly distinguishes it from siblings like list_workspaces or get_workspace_tree by emphasizing a single workspace.

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 phrase 'specific workspace' implies the tool is for retrieving details of one known workspace by name. However, it does not explicitly state when to use this tool versus alternatives like find_stale_workspaces or search_workspaces, nor does it mention any exclusions.

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 of behavioral disclosure. It only states the read action but does not mention whether it is read-only, performance implications, or what the tree structure includes (e.g., whether it includes all workspaces across all users/groups). There is no disclosure of side effects or limitations.

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?

Two sentences, action first, no filler. Every word earns its place, making it concise and easy to parse.

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 params, no output schema), the description provides a clear concept of what is returned (tree of workspaces) and implies it covers the full hierarchy. However, it could benefit from noting whether all workspaces are included regardless of user/group, but for a simple tool this is adequate.

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's coverage is trivially 100%. With no parameters, the description does not need to add parameter details. The baseline for zero parameters is 4.

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 identifies the action ('Get'), the resource ('full workspace hierarchy'), and the distinctive format ('tree structure... parent-child relationships'). This distinguishes it from sibling tools like list_workspaces (flat list) and get_workspace (single workspace).

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 the tool is for when you need hierarchical relationships, but it does not explicitly state when to prefer this over list_workspaces or search_workspaces, nor does it mention any alternatives or exclusions. Usage context is implied by the tree-structure wording.

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 for behavioral disclosure. It adds useful context about filtering (status, priority, type, label) and sorting (priority, then creation date), but does not explicitly state read-only behavior or mention pagination limits beyond schema defaults. This is acceptable for a list operation but not exhaustive.

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, front-loaded with the core action, and contains zero fluff. It efficiently communicates the tool's purpose and key behavior.

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 read-only list tool with fully described parameters and clear output sorting behavior, the description is adequate. It lacks explicit differentiation from sibling tools and does not mention any side effects, but given the simplicity and schema richness, it is nearly 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?

Schema description coverage is 100%, so the input schema already documents all parameters thoroughly. The description's mention of filtering by status, priority, type, and label merely restates what is in the schema, adding no new meaning. Baseline 3 is appropriate.

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 ('List'), the resource ('tasks from a workspace's beads issue tracker'), and the context. It distinguishes itself from sibling tools like list_workspaces and get_beads_across_workspaces by specifying it operates on a single workspace's issue tracker.

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 a single workspace's issue tracking, but does not explicitly contrast with alternatives like get_beads_across_workspaces. There is no 'when to use' or 'when not to use' guidance, leaving some ambiguity for an agent deciding between this and cross-workspace tools.

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 behavioral disclosure. It only states the listing behavior and optional filters but does not mention that it is read-only, any pagination or ordering behavior, or what 'metadata' includes. This is a significant gap for a tool with no annotation support.

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 a single, front-loaded sentence with no wasted words. It delivers the primary action and optional filters efficiently, earning a top score for conciseness.

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, but with no annotations or output schema, the description leaves significant gaps: it doesn't describe the return format (metadata fields), whether results are paginated, or how it relates to sibling tools like search_workspaces. A more complete description would add these details to be minimally viable.

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 input schema has 100% coverage with detailed descriptions for all three parameters (tags, status, stale_days). The description adds no additional meaning beyond the schema, simply restating that filtering is optional, which is already clear from the schema's optional 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 tool's purpose: 'List all workspaces with their metadata,' using a specific verb and resource. It implies a broad scope ('all') and optional filtering, which distinguishes it from the single-workspace get_workspace or tree-based get_workspace_tree, 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.

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

The description implies usage for general listing: 'List all workspaces' and mentions optional filters ('by status or staleness'). However, it provides no explicit guidance on when to choose this over siblings like search_workspaces or find_stale_workspaces, nor does it state any exclusions.

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 clearly states what data is searched and implies a read-only operation via 'search'. It does not disclose return format or side effects, but for a search tool the behavior is reasonably transparent.

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

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

The description is exactly two sentences, each earning its place. It is front-loaded with the action verb and provides detail without 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?

The description adequately covers the tool's purpose and search targets. However, with no output schema, it does not describe the return format or pagination behavior, leaving a gap in understanding what results to expect. Overall, it's good for a simple search tool but 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 schema already documents the only parameter with 100% coverage, including case-insensitive substring match. The description adds context about search targets but does not change parameter semantics, so the baseline of 3 is appropriate.

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 'Search across all workspace metadata, notes, and tab history', using a specific verb and resource. It enumerates exact search targets (workspace names, tags, workspace.md content, saved tab titles/URLs), clearly distinguishing it from sibling tools like list_workspaces or get_workspace.

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 finding content across all workspaces, but does not explicitly contrast with alternatives. However, the scope ('all workspace metadata') and search action make it clear when to use this tool versus listing or retrieving specific workspaces.

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 does disclose the nature of the tool (read-only summary) and the kind of data returned (counts, stale projects, recent activity), which is useful. But it doesn't elaborate on return format, potential performance implications of aggregating all workspaces, or whether any state changes are possible (though 'summary' implies non-destructive). It adds some value beyond the tool name but lacks rich behavioral context.

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

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

The description is concise: a single sentence stating the purpose and a short usage phrase. It is front-loaded with the core action and resource, avoids repetition of the tool name, and every clause adds value. No unnecessary 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 has no parameters, no output schema, and a simple aggregation purpose, the description sufficiently covers what an agent needs to know: when to use it and what it returns. It tells the agent the high-level nature and key output elements. This is 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?

The tool has zero parameters, and the baseline for 0-param tools is 4. The schema is empty and the description adds no parameter-specific details, which is appropriate since there are none to explain. The description compensates by clarifying the tool's output scope, so a 4 is warranted.

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 action ('Get a high-level summary') and resource ('all workspaces'), and further specifies the content ('counts by status, stale projects, recent activity'). This clearly distinguishes it from sibling tools like list_workspaces (which lists) and find_stale_workspaces (which specifically targets stale projects), as this tool provides an aggregated overview.

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 frames the intended use case: 'Designed for asking "where do things stand across all my projects?"' This tells an agent when to choose this tool over more specialized siblings. However, it doesn't explicitly state exclusions or alternatives, so it earns a 4 rather than a 5.

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