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batch_search

Read-only

WHEN: you need context on multiple D365 objects or concepts simultaneously -- runs all queries in parallel. Use INSTEAD of multiple sequential search_d365_code calls -- each line becomes one parallel search. Maximum 6 queries per call. Results are equivalent to search_d365_code but returned together. When batch_search returns results, all matching objects are FULLY loaded (all chunks). Do NOT follow up with get_object_details on the same objects -- the complete source is already included.

Triggers: 'find all of these', 'look up multiple', 'cherche plusieurs', 'SalesTable AND VendTable', 'several objects at once', 'lookup X and Y and Z', 'plusieurs objets en même temps', 'context on all of these'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topKNoResults per query (default: 5, max: 15)
queriesYesNewline-separated search queries (max 6). Example: "SalesTable\nVendTable\nvendor invoice posting"
topObjectsNoFull-chunk objects per query (default: 3, max: 8)

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true, but the description adds important behavioral context: queries run in parallel, each line becomes one search, results are fully loaded with all chunks, and no follow-up detail fetch is needed. This goes well beyond the annotation and prevents redundant agent actions.

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 front-loaded with the key WHEN/INSTEAD message, followed by capacity limits, behavioral equivalence, and a clear anti-pattern. The trigger list is somewhat long but earns its place by helping the agent recognize when to choose this tool.

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 multi-query search tool with no output schema, the description sufficiently covers when to use it, how queries map to searches, limits, result equivalence, and post-call behavior. An agent has everything needed to invoke it correctly and avoid unnecessary follow-up calls.

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 already covers all parameters with descriptions, so the baseline is 3. The description adds meaning by clarifying that each newline-separated query becomes a parallel search, enforcing the max 6 behavior, and explaining that topObjects controls full-chunk loading per query.

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?

States a specific purpose: run multiple D365 object/concept searches in parallel. It explicitly says results are equivalent to search_d365_code but returned together, distinguishing it from the closest sibling without ambiguity.

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?

Provides explicit when-to-use guidance, tells the agent to use it INSTEAD of multiple sequential search_d365_code calls, sets a maximum of 6 queries per call, and even lists concrete trigger phrases. It also warns not to follow up with get_object_details because objects are fully loaded.

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.