guide-registry

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile and lowering the burden. The description adds useful context that the row includes artifact and routing-surface status, but it does not disclose behavior for an unknown slug or clarify what 'registry row' means. Consistent with the calibrated 3 for read-only tools with annotation coverage.

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?

A single sentence delivers the verb, resource, lookup key, and response contents with zero filler. The title is equally tight. Every clause earns its place and the core action is front-loaded.

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 lookup with annotations covering safety and an output schema covering return shape, the description covers the essentials: what is fetched, how it is keyed, and what the row includes. Remaining gaps are minor—domain jargon like 'registry row', 'artifact', and 'routing-surface' is unexplained, and behavior on an unknown slug is unspecified.

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 property includes an illustrative example ('start-a-company'), so the schema carries the full parameter documentation. The description's 'by slug' merely reinforces the parameter's role without adding formats, constraints, or defaults, so the baseline 3 applies.

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?

Begins with a specific verb ('Get'), names the exact resource ('one guide's registry row'), and specifies the lookup key ('by slug'). The qualifier 'with its artifact + routing-surface status' scopes what the response includes, and the singular 'one' clearly distinguishes it from sibling 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 'by slug' qualifier and singular 'one guide' imply this is for fetching a single known guide, implicitly contrasting with list_guides, but the description never explicitly states when to use this tool versus an alternative or names the sibling for enumeration. Usage is left to inference rather than stated.

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 readOnly and non-destructive. The description adds a valuable behavioral caveat: '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 misinterpretation of null values beyond what the annotations convey.

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 carry the whole definition: the first states the traversal purpose, the second packs the high-value usage patterns and null semantics. No filler or repetition of schema 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 12-parameter read-only traversal tool with an output schema, the description covers the core use cases and the one subtle data-model trap (null semantics). The remaining parameters are fully documented in the input schema, and the output schema handles return-value expectations, 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?

Schema coverage is 100%, so the schema already documents all 12 parameters. The description adds semantic guidance for key parameters (min_guides=2, role, capability_detail) and explains the meaning of null in ksao_type/canon_component_id, going beyond the baseline schema-only documentation.

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 (capability packages), KSAO-grade elements and jobs.' This clearly differentiates list_capabilities from the sibling get_guide/list_guides/list_taxonomy tools by emphasizing the cross-entity join rather than a single entity retrieval.

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 gives explicit usage patterns for the main filters: 'Use min_guides=2 for the cross-cutting capabilities that span many guides, role=<role> for what a job requires, capability_detail=<slug> for one package...' This is clear contextual guidance, though it does not name alternatives or state when to prefer a sibling tool, so it misses the top score.

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 and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond those annotations: the response includes a distribution roll-up and explicitly includes guides homed to a property with no rendering surface. This is non-obvious and helps the agent understand the listing scope.

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 that opens with the core action and resource. The trailing enumeration and parenthetical are dense but meaningful, especially the note about guides with no rendering surface. It contains no filler, though the long list of fields makes it slightly heavy.

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 optional, fully documented parameters and an output schema present, the description does not need to explain return values or every filter. It provides the high-level purpose and highlights the non-obvious distribution roll-up behavior, which is enough for an agent to understand the tool's scope. It could add explicit sibling routing, but that gap is already scored under usage guidelines.

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 schema already documents all 13 parameters, including filters like home, access, status, domain, persona, and category. The description references some output fields that map loosely to filter parameters, but it does not add parameter-level meaning beyond what the schema provides. 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 names a specific verb and resource — 'List the bicycle.guide registry' — and enumerates what is included (home, status, access, standard, syndication, grounding, distribution roll-up). This clearly separates it from the sibling list_capabilities and list_taxonomy tools, which target different resources, and from get_guide, which is singular.

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 primary use case is implied by the verb and resource: call this to list the guide registry. However, it never explicitly says when to prefer this over get_guide, list_capabilities, or list_taxonomy, nor does it state any exclusions or alternative conditions.

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 and destructiveHint=false; the description adds that results are machine-readable rather than prose and include 'live guide counts', signaling dynamic data. This adds useful behavioral context without contradicting the 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?

A single, information-dense sentence with a front-loaded verb/resource, followed by an enumerated list of contents and a clarifying format statement. Every element earns its place; there is 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 read-only, zero-parameter tool with an output schema present, the description fully specifies the resource and the kinds of data returned. The output schema covers return values, so the description does not need to explain them. Nothing an agent needs to call it correctly 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 tool has zero parameters, so schema coverage is trivially 100%. No parameter-specific meaning is needed, and the baseline for zero-parameter tools 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?

States the specific verb 'Get' and resource 'bicycle.guide vocabulary', then enumerates exactly what is included: domains, shelves, series, personas, guide_types, and classification conventions. This clearly differentiates it from siblings like list_guides or get_guide, which concern guide content rather than the vocabulary itself.

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?

Provides clear context that this tool returns the taxonomy as machine-readable data rather than prose, implying it is the right choice when an agent needs vocabulary or classification conventions. It does not explicitly name alternatives or exclusion conditions, but the sibling list makes the intended use inferable.

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