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search_context_docs

Read-onlyIdempotent

WHEN: the user asks about business/functional context that lives OUTSIDE the D365 code KB -- specs, functional design docs, mapping sheets, contracts, meeting notes, screenshots' captions -- anything an admin uploaded via the admin portal's 'Context Documents' library (PDF, Word .docx, Excel .xlsx/.xlsm, CSV, plain text/Markdown/JSON). Does NOT search X++ code or AOT objects -- use search_d365_code / get_object_details for that. Triggers: 'what does the spec say about...', 'check the mapping document for...', 'cherche dans les documents de contexte', 'according to the functional design'. An excerpt containing a 'Image N' marker has a picture the text cannot convey (a diagram, a screenshot): call again with includeImages=true to receive those pictures inline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language search query.
maxResultsNoMax distinct documents to return (1-20). Default 8.
includeImagesNoAttach the images embedded in the matched documents (Word only). Off by default because each picture is inlined as base64 and is far larger than the text around it.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent, and the description adds meaningful behavioral context: supported file formats, admin-uploaded library scope, and the 'Image N' marker behavior with instruction to re-call with includeImages=true. This goes well beyond the structured annotations.

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?

The description is dense but every sentence earns its place: scope, exclusions, alternatives, trigger phrases, and an image-handling instruction. It is front-loaded with the most important routing information and contains no filler.

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 read-only search tool with one required parameter and a simple schema, the description fully covers what the agent needs to select and call it correctly, including output behavior around excerpts and inline images. No output schema exists, but the description provides sufficient return-related guidance.

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?

The schema covers all three parameters with clear descriptions, so the baseline is 3. The tool description adds value by explaining when to set includeImages=true using the 'Image N' marker and why images are off by default, which helps the agent invoke the tool correctly beyond the schema text.

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 the tool searches business/functional context documents stored outside the D365 code KB, and explicitly distinguishes it from code search tools like search_d365_code and get_object_details. Specific document types and trigger phrases make the resource and scope unmistakable.

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 opens with 'WHEN', provides concrete trigger examples, explicitly states what it does NOT search, and names the sibling tools to use instead for X++ code/AOT objects. This gives an agent clear routing guidance with no inference required.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes and clear triggers, reducing ambiguity. For example, PR-related tools are separated into analysis, listing, commenting, and dependency mapping. However, some overlap exists between find_references, find_extensions, and find_callers, which could confuse an agent without careful descriptions.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with verb_noun structure within subgroups (e.g., ado_*, find_*, search_*, generate_*). There is no mixing of camelCase or other styles, though the variety of prefixes slightly reduces predictability.

Tool Count3/5

With 38 tools, the server feels slightly over-scoped for its domain. While each tool has a specific function, the number is high compared to typical well-scoped servers (10-15 tools). Some tools like find_references and find_callers could be consolidated.

Completeness4/5

The tool set covers a broad range of D365 F&O development and DevOps tasks, including code search, analysis, security, performance, upgrades, and work item management. Minor gaps exist, such as the absence of direct object modification or batch job management, but the core workflows are well covered.