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Delete Template

delete_template
DestructiveIdempotent

Delete a stored Carbone template. Takes effect immediately: the template is no longer listed, downloadable or renderable (404); the file itself is purged after the retention delay (Carbone Cloud: 24 hours). You can delete by Template ID (removes all versions) or by Version ID (removes only that specific version). To schedule a deletion instead, use update_template_metadata with expireAt set to a future Unix timestamp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
templateIdYesTemplate ID (64-bit) or Version ID (SHA-256) to delete. Template ID — deletes the template record and all its versions. Version ID — deletes only that specific version, leaving other versions intact. Both formats are returned by upload_template and list_templates.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, but the description goes well beyond them: immediate effect (404, no longer listed/downloadable/renderable) and the delayed physical purge after a 24-hour retention window on Carbone Cloud. That retention nuance is exactly the kind of behavioral context annotations cannot convey.

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, all load-bearing: effect, ID-format semantics, then the alternative tool. The most critical fact (immediate, irreversible effect) is front-loaded and nothing is padded.

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?

For a single-parameter destructive tool with no output schema, the description covers the destructive scope, the timing of the effect, the retention delay, and the escape hatch for deferring deletion. An agent has everything needed to call it safely.

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% and the single parameter's description already spells out the Template ID vs Version ID distinction and where the IDs originate. The description restates that same distinction, so it adds little beyond the structured field, which anchors this at the baseline 3.

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 ('Delete a stored Carbone template') and immediately differentiates itself from the sibling update_template_metadata by explaining the scheduled-deletion alternative. An agent can tell exactly what this tool does versus its neighbors.

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 the two valid invocation modes (Template ID = all versions, Version ID = one version) and names the alternative tool plus the condition that selects it (use update_template_metadata with expireAt for scheduling). No when-to-use inference is left to the agent.

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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