Compare two D365 F&O objects side-by-side (fields, methods, signatures). Handy when investigating differences between standard and a customisation, or between two similar tables.
| Name | Required | Description | Default |
|---|---|---|---|
| objectNameA | Yes | First object name, e.g. 'SalesTable' | |
| objectNameB | Yes | Second object name, e.g. 'PurchTable' |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false; description adds the comparison scope but does not disclose return shape or failure behavior. With safety covered by annotations, this is acceptable.
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?
Two focused sentences that front-load the action and detail, with a usage cue in the second sentence; no wasted words.
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?
Enough for a simple read-only two-parameter tool: schema covers parameters and annotations cover safety. The only gap is no explicit statement of output/return value, since no output schema exists.
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 covers both parameters fully (100%) with examples; description reinforces comparison semantics but adds no syntax or additional parameter-specific guidance, so baseline 3 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?
Description names a specific verb ('Compare'), resource ('two D365 F&O objects'), and comparison dimensions ('fields, methods, signatures'), which clearly separates it from single-object lookup tools like get_object_details and version diff tools.
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?
States two concrete use cases ('standard vs customisation', 'two similar tables'), telling an agent when the tool is appropriate, though it does not explicitly name alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools overlap heavily: ado_analyze_pr_impact and ado_review_xpp_pr both review PR impact; get_object_details/get_object_context, find_related_objects/get_relation_graph, and find_callers/find_references/find_change_impact duplicate each other. The consolidated dmf tool plus five dedicated dmf_* tools also create ambiguous entry points, making misselection likely.
Most tools use readable snake_case verb_noun names, but conventions are mixed: domain prefixes (ado_, dmf_, odata_, appinsights_) coexist with generic verbs (find_, generate_, get_), and healthcheck breaks the pattern. Similar actions are also named inconsistently, such as find_callers vs find_change_impact and generate_data_entity vs find_entity_for_table.
At 90 tools this is far beyond a focused ALM server; the surface spans ADO, DMF, OData, App Insights, code search, security, release notes, wiki, and code generation. Even for a broad D365 F&O scope, 90 tools is an extreme count that makes discovery and selection difficult.
The breadth leaves few obvious dead ends: ADO work items/PRs/wikis, DMF/OData data movement, code analysis, security, and release-note generation all have lifecycle coverage. Minor gaps exist, such as no PR creation/update/abandon and no work-item deletion, but agents can complete core workflows without significant workarounds.