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Costory: Your Finops MCP

list_teams

Read-only

List teams the current user belongs to, including each team's scopes. Each scope has an id (pass as scopeId to query or a report widget to apply the saved scope) and a pre-defined filterCel string (pass as filterCel for the same effect inline). Use when the user asks about a team's costs or wants to filter by team scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoOrganization slug. Omit to auto-detect from your account (fails if you belong to multiple orgs).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context by revealing the structure of the returned data (each scope has an id and filterCel) and how to use those values in other operations, exceeding the baseline expectations.

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?

Three sentences, each earning its place: the first defines the core action, the second explains the returned scope structure and its usage, and the third gives a clear usage trigger. No fluff or redundancy.

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

Completeness4/5

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

The tool is simple (one optional parameter, read-only, no output schema), and the description covers the output format and use cases well. It doesn't mention error conditions or empty results, but these are minor gaps for this type of tool.

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% for the single optional parameter 'slug', and the schema already explains auto-detection and multi-org failure. The description adds no additional parameter semantics, so the baseline of 3 applies.

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 uses a specific verb ('List') and resource ('teams the current user belongs to'), and clearly distinguishes itself from sibling list tools by focusing on teams and their scopes. It also explains the key output elements (scopes with id and filterCel), 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 Guidelines4/5

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

Explicitly states when to use the tool: 'Use when the user asks about a team's costs or wants to filter by team scope.' This provides clear context without explicitly listing alternatives or exclusions, but the guidance is direct and actionable.

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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TDQS

A4.1/5.0
Disambiguation4/5

Tools are organized by resource (alerts, dashboards, reports, events, virtual dimensions) with distinct actions, so most are clearly separable. The main confusion risks are the three report-delivery side-effect tools (run_report_now, retry_report_execution, transfer_report_execution) and the generic get that spans five resource types, though detailed descriptions mitigate these.

Naming Consistency4/5

The dominant verb_noun pattern (create_*, list_*, update_*, preview_*, get_*) is consistent and predictable across the set. Deviations like bare verbs query/search/get and the noun-only virtual_dimension_overlap_matrix are readable but break the otherwise uniform convention.

Tool Count3/5

44 tools is heavy and exceeds the comfortable range, but the server covers a genuinely broad FinOps platform spanning querying, dashboards, reports, alerts, events, virtual dimensions, docs, skills, and suggestions. Each tool has a distinct job, though the sheer count makes agent navigation harder.

Completeness3/5

Core workflows are well covered: query → dashboard/report/alert/event, plus a full virtual-dimension draft lifecycle. Notable gaps include alerts being create-only with no update/delete, no deletes for dashboards/events/published virtual dimensions, and budget management limited to query/get with no create/update.

Resources