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DoiT MCP Server

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by doitintl

list_budget_suggestions

Read-only

Retrieve AI-generated budget suggestions for your account, then accept each by creating a matching budget or dismiss it. Review pending recommendations before deciding which to apply.

Instructions

AI-generated budget recommendations you can accept (link to a budget you created) or dismiss. Returns the pending AI-generated budget suggestions for your account. The set is small (a handful of pending suggestions) and is returned in full. Each suggestion can be accepted (after you create a matching budget via POST /analytics/v1/budgets) or dismissed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerContextNoScope the request to a specific customer by ID. Required for DoiT employees (whose token isn't tied to a single customer); omit for direct customer users.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral details: the set is small and returned in full, and each suggestion can be accepted or dismissed. It also explains the workflow (create budget via POST before accepting), which goes beyond annotations. 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.

Conciseness5/5

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

The description is concise, two sentences, and front-loaded with the core purpose. The first sentence explains the tool's function and follow-up actions, while the second provides scale and return behavior. Every sentence adds value without redundancy.

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 simplicity (one optional parameter, no output schema), the description covers the essential context: what it returns, the size of the result set, and the follow-up actions (accept/dismiss). It also links to the budget creation endpoint, enhancing completeness for a list tool in a workflow.

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

Parameters3/5

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

The sole parameter customerContext has a complete description in the schema (100% coverage), explaining when it is required and for whom. The tool description adds no additional parameter info, but since the schema covers it fully, a baseline score of 3 is appropriate.

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 lists AI-generated budget suggestions, uses the specific verb 'list' and resource 'budget suggestions', and distinguishes from siblings like accept_budget_suggestion and dismiss_budget_suggestion by focusing on the listing aspect. It also specifies 'pending' suggestions, narrowing the scope.

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 implies usage context: it returns suggestions that can be accepted or dismissed, and mentions the need to create a matching budget before accepting. This gives clear context but does not explicitly state when to use this tool versus alternatives like list_budgets or accept_budget_suggestion. The related siblings are evident, so guidance is adequate though not exhaustive.

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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