guide-registry

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

The annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds context by specifying that the result includes artifact and routing-surface status. This clarifies what the returned registry row contains and reinforces that the operation is non-mutating.

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: core action and scope appear first, followed by the specific status fields returned. There is no filler, duplication of annotations, or unnecessary elaboration.

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, one-parameter, read-only lookup with a full output schema and safety annotations, the description is complete enough. It names what the result contains and identifies the lookup key, so an agent can select and invoke it without further clarification.

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 fully documents the only required parameter, 'slug', including an example. The description merely restates that lookup is by slug, adding no semantic detail beyond the schema, so the baseline 3 for 100% schema coverage 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 a specific verb ('Get') and a specific resource ('one guide's registry row'), scoped by slug, and names the status fields included ('artifact + routing-surface status'). This clearly distinguishes it from the sibling list_* tools, which operate over collections.

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 'one guide's registry row by slug' signals that this tool is for a single, slug-identified lookup rather than listing many guides. It does not explicitly name alternatives or exclusions, so it stops short of full 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?

The description discloses a critical interpretation rule — ksao_type/canon_component_id nulls are 'not yet joined', never 'no link' — which prevents a plausible misreading of results. Annotations already carry the safety profile (readOnlyHint=true, destructiveHint=false), and the description is fully consistent with them, adding interpretive context beyond what annotations provide.

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 dense sentences with the purpose front-loaded and no filler. The middle sentence packs three usage recipes compactly, which is readable despite its density; every sentence earns its place, including the null-semantics warning.

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, 0-required tool with an output schema and 100% schema coverage, the description supplies the unifying conceptual model — the spine join across books, guides, elements, and jobs — plus the critical null-handling rule. The only notable gap is the absence of explicit routing to sibling tools (get_guide, list_guides, list_taxonomy).

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% with rich per-parameter text (e.g., the 95.1% validation note on ksao_type and the ~30% person-attribute note on construct_class), so the baseline is 3. The description's references to min_guides, role, and capability_detail largely restate the schema rather than adding new meaning.

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 — 'Traverse the capability spine joining books, guides (capability packages), KSAO-grade elements and jobs' — with a clear resource and scope that distinguishes it from the simpler list/get siblings. It doesn't name a sibling explicitly, so differentiation from get_guide, list_guides, and list_taxonomy is implied rather than stated.

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?

Three concrete usage recipes are provided: min_guides=2 for cross-cutting capabilities, role= for what a job requires, and capability_detail= for a single hydrated package. This gives an agent clear entry points by scenario, though it never states when to prefer a sibling tool such as list_guides over this one.

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 cover read-only safety (readOnlyHint=true, destructiveHint=false), so the description adds value by disclosing the non-obvious inclusion of guides homed to properties with no rendering surface. It also enumerates the field categories returned. It does not contradict 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?

The description is a single efficient sentence that front-loads the verb and resource, then packs the scope and an important edge-case inclusion into a well-structured em-dash phrase. 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?

Given the output schema, full parameter documentation, and read-only annotations, the description is complete enough for correct selection and invocation. It adds the crucial scope note about the distribution roll-up and unrenderable homes, which is exactly the context an agent needs.

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 fully documents all 13 filter parameters. The description does not need to repeat parameter details, and it adds no extra parameter-level 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 and resource ('List the bicycle.guide registry') and enumerates the exact scope of what is returned: every guide's home, status, access, standard, syndication, grounding, and the distribution roll-up. This clearly separates it from sibling tools like get_guide (single guide), list_capabilities, 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 implies this is the tool to list the full guide registry, but it does not explicitly say when to prefer this over list_capabilities or list_taxonomy, nor does it mention get_guide for single-guide lookups. Usage context is clear only by inference from the resource name and scope.

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, destructiveHint=false, and openWorldHint=false. The description adds value by specifying the exact data categories returned and noting that shelf counts are 'live,' which indicates dynamic behavior. This exceeds what the annotations alone 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?

The description is a single, dense sentence with the main purpose front-loaded. Every element adds useful information: the resource, the specific vocabulary components, live counts, and the machine-readable output distinction. 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?

With no parameters, safety annotations, and an output schema present, the description covers what an agent needs: the tool's scope, contents, and output format. The enumerated categories make the expected result clear without needing to explain return values.

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 there is nothing for the description to document. Baseline for zero parameters is 4, and the description appropriately focuses on output 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 uses a specific verb ('Get') and resource ('bicycle.guide vocabulary') and enumerates exactly what is included: domains, shelves with live guide counts, series, personas, guide_types, and classification conventions. This clearly differentiates it from sibling tools like list_guides or 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 description implies when to use it—when structured vocabulary/taxonomy data is needed rather than prose—but it does not explicitly state when to avoid it or name alternative tools. The 'rather than prose' phrase gives some context, but the guidance is mostly implicit.

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