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Costory: Your Finops MCP

by io.costory.app-api
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list_label_dimensions

Read-only

List all published engineered label dimensions (merge + value map). Use when the user asks which engineered label dimensions exist. Compact rows only: id, name, sourceKeys, maps. No pagination — orgs do not have enough labels to page. Edits go through publish_label_dimensions operations by id (merge; do not resend this array). Pass an operations array (add / update / delete by id). The server merges them onto all existing label dimensions — do not resend the full list. Publishing takes about 10 minutes to show up in Explorer. Preview with dryRun: true (default), then call once with dryRun: false and confirm: true. Before rename or delete, call list_label_dimension_usages. Not virtual dimensions — those use list_virtual_dimensions. EXAMPLE: "Show published label dimensions" → {}

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "context": "<context>"
    },
    "name": "list_label_dimensions"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugNoOrganization slug. Omit to auto-detect from your account (fails if you belong to multiple orgs).
contextYesA few words on why you are calling this tool, for the server developer's analytics. Describe people and things by role, such as "a customer". Do not quote the user or include names, emails, or other personal details.
llm_modelNoThe model identifier you are running as, for example "claude-opus-4-8" or "gpt-5.2". Pass "unknown" if you are not certain. Recorded for the server developer's analytics.
conversation_idNoThe conversation_id this server returned earlier in this conversation, unchanged, including after later user messages. Omit it if you have none. Recorded for the server developer's analytics.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""New value: +"A few words on why you are calling this tool, for the server developer's analytics. Describe people and things by role, such as \"a customer\". Do not quote the user or include names, emails, or other personal details."
    • changedInput schema / required
      Previous value: -[
-  "context",
-  "llm_model"
-]New value: +[
+  "context"
+]
  2. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "The conversation_id this server returned earlier in this conversation, unchanged, including after later user messages. Omit it if you have none. Recorded for the server developer's analytics.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The model identifier you are running as, for example \"claude-opus-4-8\" or \"gpt-5.2\". Pass \"unknown\" if you are not certain. Recorded for the server developer's analytics.",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "context",
+  "llm_model"
+]
  3. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description usefully adds row shape (id, name, sourceKeys, maps) and that there is no pagination because orgs have few labels. The rest of the text describes the publish workflow, operation arrays, dryRun, and a 10-minute propagation delay — behavior of a different tool that does not help an agent reason about this read call.

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

Conciseness3/5

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

Front-loaded and useful at the start, but nearly half the text is off-topic editing instructions repeated twice ('do not resend the full list' / 'do not resend this array'), and the imperative 'Pass an operations array' sits inside a listing tool's description. Trimming the publish-workflow material would make this much tighter.

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?

With no output schema, the description carries the return-value burden and does so by naming the four row fields and stating there is no pagination. The remaining gap is that the mixing of publish semantics could lead an agent to misread the tool's contract, but for a simple read-list tool the essentials are present.

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%, so slug, context, llm_model, and conversation_id are already documented in the schema; the description adds nothing about them. Baseline 3 applies, and the example invocation '{}' at least confirms no parameters are required beyond the auto-injected context.

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?

States a specific verb and resource ('List all published engineered label dimensions (merge + value map)') and immediately disambiguates from two siblings: virtual dimensions and publish_label_dimensions. An agent can tell exactly what this returns and what it does not.

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?

Gives an explicit trigger ('Use when the user asks which engineered label dimensions exist') and names alternatives: not virtual dimensions, and use list_label_dimension_usages before rename/delete. However, the guidance is diluted by several sentences about publishing/editing that belong to a different tool and make the when-to-use story noisier than it needs to be.

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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