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lazymac2x

lazymac-mcp

ai_spend_tracker

Track AI service spending across OpenAI, Anthropic, and Google with budget monitoring and alert features.

Instructions

Track AI spending across OpenAI / Anthropic / Google with budgets and alerts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoFree-form params object — passed as query string for GET, JSON body for POST
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'budgets and alerts', hinting at monitoring and notification features, but doesn't specify how tracking works (e.g., real-time vs. batch, data sources), what permissions or authentication are needed, rate limits, or response formats. This leaves significant gaps for a tool that likely interacts with external APIs.

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 a single, efficient sentence that front-loads the core functionality: 'Track AI spending across OpenAI / Anthropic / Google with budgets and alerts'. It wastes no words and clearly communicates the tool's intent without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity implied by tracking spending across multiple providers with budgets and alerts, the description is incomplete. No annotations exist to clarify safety or behavior, and there's no output schema to explain return values. The description lacks details on how the tool operates, what data it returns, or error handling, making it inadequate for effective agent use.

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 input schema has 1 parameter with 100% description coverage, documenting it as a 'Free-form params object — passed as query string for GET, JSON body for POST'. The description adds no specific parameter details beyond the general purpose, so it doesn't compensate but doesn't need to given the schema coverage. Baseline 3 is appropriate as the schema handles the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Track AI spending across OpenAI / Anthropic / Google with budgets and alerts'. It specifies the verb ('Track'), resource ('AI spending'), and scope ('across OpenAI / Anthropic / Google'), though it doesn't explicitly differentiate from sibling tools like 'ai_budget_planner' or 'ai_cost_calculator', which may have overlapping functions.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'ai_budget_planner' and 'ai_cost_calculator', it's unclear if this tool is for monitoring, planning, or calculating costs, or how it relates to 'ai_rate_limit_tracker' or 'ai_token_counter'. No exclusions or specific contexts are mentioned.

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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