guide-registry

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that the result includes artifact and routing-surface status, but it does not disclose behavior such as not-found handling or required permissions. This is adequate for a simple read operation.

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 entire description is one short sentence that front-loads the verb and resource, then appends the scope. No filler or redundancy exists.

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 one-parameter read-only tool with an output schema and clear sibling names, the description covers the essential invocation context. The output shape is already defined by the output schema, so nothing critical is missing.

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 100% parameter description coverage, including an example for 'slug'. The description mentions 'by slug' but adds no additional semantic detail beyond what the schema already provides, 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 states the verb 'Get', the resource 'one guide's registry row', and the identifier 'by slug', which precisely defines the operation. It also mentions what is included ('artifact + routing-surface status'), clearly distinguishing it from the sibling list_guides, which retrieves multiple 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 description provides clear context that this is for fetching a single guide when the slug is known, but it does not explicitly state when not to use it or name alternatives such as list_guides for bulk retrieval. The usage is implied by 'by slug' rather than directly contrasted with 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?

The description discloses an important behavioral nuance: 'ksao_type/canon_component_id are null by design where unresolved — treat null as not yet joined, never as no link.' This is a genuinely useful open-world interpretation of null values. However, it directly contradicts the openWorldHint=false annotation, which indicates a closed-world stance in which absence is meaningful. This is an Annotation Contradiction.

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?

Three sentences, each with a distinct job: core purpose, parameter recipes, and output semantics. The description is front-loaded with the main traversal purpose and wastes no words. It is appropriately sized for a 12-parameter tool.

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?

An output schema exists, so the description need not explain return values. It covers the key behavioral caveat around nulls and gives practical filter guidance. The missing piece is explicit guidance on when to use this tool versus sibling tools, but the schema and annotations carry much of the remaining burden.

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 all 12 parameters already have descriptions. The prose adds value with concrete recipe-like guidance for min_guides, role, and capability_detail, and the schema itself provides domain context like the 95.1% validation for ksao_type. This goes beyond the baseline of 3.

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 and resource: 'Traverse the capability spine joining books, guides (capability packages), KSAO-grade elements and jobs.' This clearly conveys a multi-entity traversal and distinguishes it from sibling tools like get_guide or list_guides, though it does not explicitly name those alternatives. No tautology is present.

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 conditional parameter usage recipes: 'min_guides=2 for the cross-cutting capabilities', 'role=<role> for what a job requires', and 'capability_detail=<slug> for one package'. However, it never states when to prefer this tool over its siblings or when not to use it. The guidance is about how to choose filters, not about tool 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?

Annotations already mark this as read-only and non-destructive. The description adds useful behavioral context by specifying that the listing is exhaustive ('every guide') and that the roll-up intentionally includes guides homed to properties with no rendering surface, which is a meaningful edge-case 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?

The description is a single dense sentence that front-loads the verb and resource, then packs the scope and roll-up detail without filler. Every phrase earns its place.

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 high parameter count, the 100% schema coverage, and the presence of an output schema, the description is adequate and complete for a listing tool. It captures the overall scope and the notable distribution edge case, though it could have briefly mentioned the available filters family.

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 baseline of 3 applies. The description does not add parameter-level semantics, but it does not need to because each of the 13 parameters is already well-documented in the schema with examples and filter meanings.

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: 'List the bicycle.guide registry.' It enumerates the fields returned (home, status, access, standard, syndication, grounding) and the distribution roll-up, clearly distinguishing this from single-guide retrieval (get_guide) and other registries (list_capabilities, list_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?

No explicit guidance is given on when to use this tool versus its siblings. There is no 'for a single guide use get_guide' or 'for capabilities use list_capabilities' style routing, leaving the agent to infer usage from the name alone.

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 provide readOnlyHint=true and destructiveHint=false, so the core safety profile is clear. The description adds meaningful behavioral context beyond annotations by noting that shelf guides counts are 'live' and that the output is structured 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 dense sentence that front-loads the resource name and then efficiently lists the exact contents. Every element earns its place; there is no filler or repetition.

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 parameterless read-only tool with an output schema and strong annotations, the description is complete: it names the domain, the categories included, the live nature of counts, and the machine-readable format. Nothing essential is missing for an agent to understand what it will receive.

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 parameter semantics are not a burden on the description. The description appropriately focuses on what the returned vocabulary contains rather than parameter details.

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 names a specific verb ('Get'), a clear resource (the bicycle.guide vocabulary), and enumerates exactly what is included: domains, shelves, series, personas, guide_types, and classification conventions. It clearly distinguishes the tool's machine-readable output from prose-based tools like get_guide.

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 'as machine-readable data rather than prose' implies a use case and hints at distinguishing this from a prose-oriented sibling, but it never explicitly names alternatives or states when to choose this tool over list_guides or list_capabilities. Usage context is present but only implicitly.

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