guide-registry

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description's 'Get' is consistent with that. The description adds only a small amount of context about the result contents, but no deeper behavioral details such as failure modes, permissions, or side effects. No contradiction with annotations.

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

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

One concise, front-loaded sentence that states the action, target, lookup key, and result scope. No redundant or filler 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?

For a simple single-parameter read-only tool with annotations covering the safety profile and an output schema covering the return shape, the description provides everything an agent needs 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?

Schema description coverage is 100% and the 'slug' parameter is already documented with an example. The description simply repeats that the lookup is by slug and does not add constraints, format rules, or additional meaning beyond 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 uses a specific verb ('Get') and a clear resource ('one guide's registry row'), identifies the lookup method ('by slug'), and states what the result includes ('artifact + routing-surface status'). This clearly distinguishes it from the list-oriented sibling tools like list_guides.

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 singular wording ('one guide') and 'by slug' make clear this is a targeted single-row lookup, not an enumeration like list_guides. However, it does not explicitly name alternatives or state when not to use it, so it stops just short of full guidance.

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?

Annotations already mark the tool as read-only and non-destructive, but the description adds important behavioral nuance beyond that: 'ksao_type/canon_component_id are null by design where unresolved — treat null as not yet joined, never as no link.' This prevents a common misreading and gives the agent essential interpretation guidance.

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 with no filler. Each sentence earns its place: the first defines the tool's scope, the second gives high-value parameter use cases, and the third explains the crucial null-handling convention. It is front-loaded and easily 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?

With 12 optional parameters, 100% schema coverage, an output schema, and read-only annotations, the description covers the remaining gaps well by highlighting key usage patterns and the null semantics that the schema alone would not convey. An agent has enough context to select and call this 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 input schema already documents all 12 parameters with high coverage, so the baseline is 3. The description adds extra semantic value by explaining what specific parameter combinations are for, such as min_guides=2 for cross-cutting capabilities and capability_detail for hydrated package output, going slightly beyond 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 a specific verb and resource: 'Traverse the capability spine joining books, guides, KSAO-grade elements and jobs.' This makes the tool's scope immediately clear and sets it apart from siblings like get_guide and list_guides, which focus on single guides or listing guides rather than cross-entity traversal.

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 concrete usage patterns: 'Use min_guides=2 for the cross-cutting capabilities', 'role=<role> for what a job requires', and 'capability_detail=<slug> for one package with its elements and books hydrated.' This is actionable guidance, though it does not explicitly state when not to use this tool versus the sibling 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?

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds useful output-scope context, especially the inclusion of guides homed to properties with no rendering surface, but it does not disclose behaviors like pagination, defaults, or response structure beyond what the schema already provides.

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 efficiently written sentence that front-loads the resource and scope, then adds a valuable edge-case detail about unrouted homes. There is no filler or repetition of schema 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?

Given the 13-parameter schema, full schema coverage, and an output schema, the description provides sufficient orientation: what resource is listed, what fields are included, and a notable inclusion edge case. It does not mention that get_guide exists for single-guide lookups, but that is a minor omission for a list tool whose siblings are inferable.

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 every one of the 13 parameters is already documented with meaningful descriptions and examples. The tool description adds no parameter-level detail, but it does not need to because the schema carries the full burden; 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 uses a specific verb ('List') with a specific resource ('bicycle.guide registry') and enumerates the exact content returned: every guide's home, status, access, standard, syndication, grounding, and the distribution roll-up. This makes it clearly distinct from siblings like get_guide (single guide) and list_capabilities/list_taxonomy (other registries), even without explicit sibling naming.

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 states what the tool lists but gives no explicit guidance on when to choose it over alternatives, nor any exclusions or prerequisites. The intended use is fairly obvious from the name and title, but the description itself does not provide routing guidance.

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?

Annotations already establish this as a safe read-only operation. The description adds value beyond those annotations by specifying what will be returned, including live guide counts and classification conventions, and by clarifying that the output is machine-readable data rather than prose.

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, information-dense sentence that front-loads the core purpose and then enumerates the included content. Every phrase adds value, with no filler or redundant restatement of the tool name.

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 zero parameters, strong read-only annotations, and an output schema present, the description needs only to communicate scope and format. It does so thoroughly by listing the taxonomy components and the machine-readable output expectation, making it complete for an agent to call 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 accepts zero parameters and the schema coverage is 100%, so there are no parameter semantics to explain. The description still adds meaningful information about what the returned taxonomy contains, satisfying the baseline for a no-parameter tool.

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 a clear resource, the bicycle.guide vocabulary, while enumerating the exact contents: domains, shelves, series, personas, guide_types, and classification conventions. This clearly distinguishes it from sibling tools like list_guides and get_guide, which concern guides rather than taxonomy.

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 when structured vocabulary or classification data is needed, especially with the phrase 'as machine-readable data rather than prose.' However, it does not explicitly state when to prefer this over list_guides or list_capabilities, 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.