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alexpota

cloudscope-mcp

Cost Optimization Recommendations

list_recommendations
Read-onlyIdempotent

Fetch cost-saving recommendations for Azure or GCP by category. Each recommendation includes title, impact level, estimated annual savings, and suggested action to reduce waste.

Instructions

Fetches cost-saving recommendations filtered by category. Returns a list of recommendations each containing: title, category, impact level (high/medium/low), estimated annual savings in USD, affected resource ID, and a short description of the suggested action. Returns an empty list if no recommendations exist for the selected category. Use this when the user wants to reduce costs, find waste, or optimize resource usage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoCloud provider to query (azure or gcp)azure
categoryNoFilter by category: all, compute, storage, or networkingall
Behavior4/5

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

Annotations already indicate read-only, non-destructive, and idempotent behavior. The description adds meaningful detail: returns empty list if no recommendations, and lists return fields. No contradiction.

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, with two functional sentences and a usage guideline sentence. Front-loaded with the core purpose, no wasted words.

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?

The description is complete for this simple tool: explains return structure, empty list behavior, and usage context. Annotations cover safety. No output schema needed.

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?

Schema description coverage is 100% with both parameters having descriptions and enums. The description does not add additional meaning beyond the schema, so baseline score of 3 is appropriate.

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 it fetches cost-saving recommendations filtered by category, with a specific verb and resource. It provides a usage directive but does not explicitly distinguish from sibling tools like find_idle_resources or check_budgets.

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 explicitly says to use this when the user wants to reduce costs, find waste, or optimize resource usage. However, it does not specify when not to use it or mention alternatives.

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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