Cloud FinOps Skill & MCP

Browse the cloud waste runbooks

list_playbooks

Read-onlyIdempotent

See every ready-made runbook for finding and fixing cloud waste: idle, orphaned and overprovisioned resources, egress surprises, schedule blindness and AI/ML inefficiency across AWS, Azure and GCP.

Use this to discover which waste patterns have a runbook. When the
question already names a provider, waste category, or confidence tier,
call ``find_playbooks`` instead.

Each playbook is a small (~80-130 line) runbook scoped to one waste
pattern (e.g. ``aws-zombie-nat-gateway``, ``azure-orphan-disks``). Returns
``{"playbooks": [...], "total": N}`` where each entry includes ``name``,
``title``, ``scope`` (aws/azure/gcp/cross-cloud), ``service``,
``waste_category``, ``confidence`` (obvious/likely/possible), and
``approx_tokens`` - the same size hint the reference listing carries, so a
multi-playbook answer can be budgeted before fetching.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 19, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the agent knows this is a safe read. The description adds value by disclosing the return structure (playbooks array with total), the fields per entry, and the approx_tokens budget hint, which is useful for planning multi-playbook answers. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured, front-loading the core purpose before detailing the return format. It is longer than a single sentence but every part earns its place, explaining scope, alternatives, and output fields without fluff.

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 (no parameters), the presence of an output schema, and rich annotations, the description covers all necessary aspects: what it does, when to use it, what it returns, and how to budget for it. Nothing an agent needs to call it correctly is missing.

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 tool has zero parameters, so schema coverage is 100% and there is nothing to document. The description correctly omits parameter details, and the baseline for 0-parameter tools is 4, which is appropriate here.

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 the tool lists all ready-made runbooks for cloud waste across AWS, Azure, and GCP, covering specific waste patterns. It distinguishes itself from find_playbooks by naming the alternative and the condition that triggers it, making the purpose unambiguous.

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?

Explicitly states when to use this tool (to discover which waste patterns have a runbook) and when to use the sibling find_playbooks instead (when the question already names a provider, waste category, or confidence tier). This leaves no ambiguity about routing.

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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