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 some behavioral context by mentioning that the returned row includes artifact and routing-surface status. It does not cover edge cases such as a missing slug or not-found behavior, but for a simple lookup tool the additional disclosure beyond annotations is reasonable.

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 concise sentence with no filler or repeated title content. The main action, resource, and qualifier are front-loaded, and the artifact/routing-surface status detail earns its place by rounding out the response scope without bloating the text.

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?

This is a low-complexity single-parameter lookup with a full output schema available, so the description does not need to enumerate return fields or error cases. It is adequate for an agent to understand what the tool returns and when to call it. A slightly more explicit pointer to sibling alternatives would make it fully complete, but 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?

Schema description coverage is 100%, and the single parameter slug is already documented with an example in the schema. The tool description adds no new parameter-level meaning beyond restating 'by slug', so the baseline 3 is appropriate because the schema carries the burden and the description does not conflict with it.

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'), names a precise resource ('one guide's registry row'), and adds the retrieval key ('by slug'), clearly distinguishing it from sibling list tools like list_guides. It also hints at return scope with 'artifact + routing-surface status', so there is no ambiguity about what this tool 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 clearly implies this tool is for fetching a single specific guide registry row when a slug is known, which gives an agent enough context to choose it over list_guides or list_taxonomy. It does not explicitly name alternatives or state when not to use it, but the singular-scope language provides clear operational context.

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 that the tool is read-only and non-destructive. The description adds meaningful behavioral context: ksao_type and canon_component_id are null by design, and null should be interpreted as 'not yet joined', not 'no link'. 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?

Three sentences with no filler: the first states the core purpose, the second gives actionable parameter patterns, and the third warns about null interpretation. It is appropriately compact for a tool with 12 parameters whose schema already carries the details.

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 tool with full schema coverage and an output schema, the description plus schema fully supports correct invocation. It covers selection, parameter intent, and the key data-interpretation caveat around null values. 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?

Schema description coverage is 100%, so the baseline is 3. The description goes beyond the schema by mapping min_guides, role, and capability_detail to specific use cases and by explaining the null semantics for ksao_type and canon_component_id.

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 ('traverse') and resource ('the capability spine'), and names the entities involved: books, guides, KSAO elements, and jobs. This clearly distinguishes it from siblings like list_guides, get_guide, and 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?

The description gives concrete usage patterns: min_guides=2 for cross-cutting capabilities, role=<role> for job requirements, and capability_detail for hydrated packages. It does not explicitly say when not to use this tool versus the siblings, but the context is strong enough for an agent to select it correctly.

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 signal a safe read-only operation, and the description adds meaningful behavior beyond that: it returns not just guide rows but also a distribution roll-up, and explicitly includes guides whose home has no rendering surface. This helps the agent expect comprehensive, gap-inclusive output rather than a simple filtered list.

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 one dense, front-loaded sentence with no filler. The em-dash clause adds compositional detail about what 'registry' means, and the parenthetical about rendering surfaces earns its place by flagging a notable inclusion.

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 13 parameters all documented in the schema and an output schema present, the description does not need to explain return shapes or filter semantics. It clearly sets expectations for scope and roll-up content, which is enough for a list-style read-only 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?

Schema description coverage is 100%, so the baseline is 3. The description repeats a few field names like home, status, access, and standard, but it does not add any meaning beyond what the per-parameter descriptions already provide.

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?

Description uses a specific verb and resource ('List the bicycle.guide registry') and clarifies scope as 'every guide' plus the distribution roll-up. This clearly distinguishes it from get_guide, which returns a single guide, and from capability/taxonomy listers by naming the guide registry explicitly.

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 given on when to use this tool versus siblings like get_guide, list_capabilities, or list_taxonomy. The description states what the tool does but not when it should be preferred or when another tool would be more appropriate.

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 indicate this is a safe read-only operation. The description adds useful behavioral context beyond annotations: it returns 'machine-readable data rather than prose' and notes that shelf counts are 'live', which suggests dynamic data rather than a static snapshot.

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 core purpose and then efficiently enumerates the taxonomy contents. Every clause adds information about what the caller can expect, with no 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 zero-parameter, read-only tool with an output schema, the description is fully adequate. It tells the agent what data categories are included, highlights live counts, and clarifies the machine-readable output format, leaving no critical gap for invocation.

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 documentation is not a burden on the description. With 100% schema coverage and an empty parameter list, the description appropriately focuses on what the response contains rather than input 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 precise verb and resource: 'Get the bicycle.guide vocabulary'. It enumerates the specific content areas returned (domains, shelves, series, personas, guide_types, classification conventions), making the tool's scope unmistakable and clearly distinct from siblings like get_guide and 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 description makes it clear that this tool is for retrieving vocabulary/taxonomy data rather than actual guides or capabilities, so the appropriate usage context is implied. However, it does not explicitly state when to choose this tool over list_guides or list_capabilities, nor does it name alternatives.

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