guide-registry

Traverse the capability spine (books · guides · KSAO elements · jobs)

list_capabilities

Read-only

Traverse the capability spine joining books, guides (capability packages), KSAO-grade elements and jobs. Use min_guides=2 for the cross-cutting capabilities that span many guides, role= for what a job requires, capability_detail= for one package with its elements and books hydrated. ksao_type/canon_component_id are null by design where unresolved — treat null as 'not yet joined', never as 'no link'.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Substring match on the element label.
`role`	No	Elements required by this job role, e.g. compensation-analyst.
`limit`	No	Cap the rows returned (default 200). `total` always reports the true count.
`has_job`	No	Only elements that some job requires (via a career guide).
`ksao_type`	No	knowledge \| skill \| ability \| other — from a panel validated at 95.1% on gold O*NET labels. 'other' is UNVALIDATED (no gold labels existed for it).
`capability`	No	Elements taught by this capability (guide slug).
`min_guides`	No	Only elements taught by >= N capabilities. 2 gives the cross-cutting spine.
`conflicting`	No	Only elements where 2+ non-career guides define the same label differently — these need a ruling.
`construct_class`	No	person-attribute (knowledge/skill/ability — what a JOB requires and a learner develops) \| condition-or-outcome (what a capability PRODUCES, e.g. 'Retention & Workforce Stability'). Only ~30% of elements are person attributes — filter to these for 'what does this role need'.
`capability_detail`	No	Return ONE capability with its elements and books hydrated, instead of querying elements.
`has_canon_identity`	No	true = only elements resolved to a JobFrame canon component (an IDENTITY, panel-adjudicated). false = only unresolved.
`canon_promotion_candidate`	No	true = only elements the JobFrame canon has NO component for. This is a real answer, not a failed lookup — these are the constructs to PROMOTE into the canon.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`total`	No
`elements`	No
`returned`	No
`capability`	No
`spine_meta`	Yes
`api_version`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 8, 2026

TDQS

A4.8/5.0

Behavior5/5

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 valuable behavior beyond that: nulls mean 'not yet joined' rather than 'no link', ksao_type 'other' is unvalidated, and construct_class filters to only ~30% person-attribute elements. These are exactly the kind of non-obvious behaviors an agent needs to know.

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

Conciseness5/5

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

Three sentences, each earning its place: purpose, parameter-to-use-case mapping, and the critical null-semantics caveat. The description is dense but not bloated, and the opening sentence immediately establishes what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 12-parameter read-only query tool with an output schema, the description covers the domain model, key usage modes, data-quality caveats, and null interpretation. The output schema handles return-value details, so nothing critical is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description enriches the parameters with domain meaning: min_guides=2 identifies the cross-cutting spine, capability_detail hydrates a package, canon_promotion_candidate represents real promotion candidates, and construct_class distinguishes 'what a job requires' from 'what a capability produces'. This goes well beyond the schema's basic field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete operation: traverse the capability spine to join books, guides, KSAO elements, and jobs. It is clearly differentiated from siblings like list_guides and get_guide by focusing on cross-entity traversal and element-level query modes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly maps parameters to use cases: min_guides=2 for cross-cutting capabilities, role=<role> for job requirements, and capability_detail=<slug> for a hydrated package. It does not explicitly contrast with sibling tools, but gives enough situational guidance for an agent to choose correctly.

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

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