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Search Workday documentation

search_workday_docs
Read-onlyIdempotent

Search Workday developer documentation by concept, widget, API, or task. Returns lightweight pointers (title, breadcrumb, doc_id, link) for targeted follow-up reading. Filter by section and limit results.

Instructions

Search the Workday developer documentation by concept, widget, API, or task.

Returns lightweight pointers (title, breadcrumb, doc_id, link) — NOT full page text. Call get_workday_doc with a returned doc_id to read a page.

When the full-text index is built (npm run build-index), this searches page BODIES (BM25), so intent/how-to phrasing works well — e.g. "sortable grid with pagination", "format a date in a PMD expression". Without the index it falls back to TITLE-only matching (engine="title"), where specific how-to phrasing may return weak hits — build the index for best results. The response 'engine' field tells you which mode ran.

Args:

  • query (string): concept/widget/API/task, e.g. "validate a field on submit"

  • section ('Extend Apps' | 'Integration Apps' | 'Workday APIs' | 'Workday Developer Copilot'): optional filter

  • limit (number): max results, 1-50 (default 10)

Returns: { query_echo, engine, count, results: [{ doc_id, title, breadcrumb, html_url, score }] } Higher score = stronger match. Empty results means no match — try broader terms or browse_workday_toc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesConcept/widget/API/task to find, e.g. 'validate a field on submit'
sectionNoRestrict to a top-level section
limitNoMax results (1-50)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_echoYes
engineYes
countYes
resultsYes
Behavior5/5

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

Annotations already indicate read-only, non-destructive, idempotent. The description adds context: returns lightweight pointers, fallback to title-only matching, engine field in response, and empty results behavior. No contradictions.

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

Conciseness4/5

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

The description is detailed and well-structured, but slightly verbose. It front-loads purpose and usage, but could be trimmed without losing value.

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?

Given the tool's complexity and available schema/output schema, the description covers all aspects: behavior, parameters, return format, and integration with sibling tools. No gaps.

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

Parameters4/5

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

Schema coverage is 100% with descriptions. The description adds examples for query and explains the effect of section and limit, but does not add new parameter info beyond the schema.

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 clearly states it searches Workday documentation by concept, widget, API, or task. It distinguishes from siblings by specifying it returns lightweight pointers and directs to get_workday_doc for full text. Sibling browse_workday_toc is also mentioned.

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

Usage Guidelines5/5

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

The description explains when to use this tool for searching, when to use get_workday_doc instead, and how to improve results (build index). It also describes fallback behavior and how to interpret the response.

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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