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update_prompt

Partially update a prompt's template, variables, labels, or description by providing only the fields to change. Use for label promotion and small edits.

Instructions

Partially update an existing prompt's template / variables / labels / description (Pro+ only, PATCH /v1/prompts/:id). name + version are immutable (change them via rename_prompt). promptId is required; only the fields you pass are updated. Used by AI agents for label moves (promoting 'staging' to 'production') and small patch edits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelsNoNew labels (full replacement, up to 8, each [A-Za-z0-9][A-Za-z0-9_-]{0,31}).
promptIdYesTarget prompt id (list_prompts.prompts[].id)
templateNoNew template body (non-empty, up to 50000 chars).
variablesNoNew variables (plain object; null clears them all).
descriptionNoNew description (1-500 chars). To explicitly clear the existing description, PATCH other fields without this one (an empty string '' is rejected by the schema — prevents an LLM hallucination from wiping the existing description).
Behavior5/5

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

Discloses partial update behavior (only passed fields updated), immutability constraints, and the nuance about description field (rejecting empty string to prevent accidental wipe). No annotations exist, so description fully addresses behavioral traits.

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?

Two well-structured sentences, front-loaded with key information, no wasted words. Every sentence adds value.

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 complexity (5 params, nested objects) and absence of output schema, the description covers operation, restrictions, usage scenarios, and important edge cases (description clearing). It is complete for an AI agent to use correctly.

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?

Schema coverage is 100% with good parameter descriptions. The tool description adds context like 'variables (null clears them all)' and 'promptId is required', which supplements the schema meaningfully.

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 it's for partially updating an existing prompt, lists the updatable fields (template, variables, labels, description), and distinguishes from rename_prompt. It specifies the HTTP method and Pro+ requirement.

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 warns that name and version are immutable and must be changed via rename_prompt. Provides usage examples like label moves and small patch edits, guiding when to use this tool.

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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