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Respan MCP Server

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by respanai

create_prompt_version

Create a new version of a prompt by providing its ID, messages, model, and sampling parameters; the version is saved as undeployed.

Instructions

Create a new version of a prompt. The version is always created as NOT deployed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stopNoArray of stop sequences
modelYesModel identifier to use for this version (e.g. gpt-4o) — required
top_pNoTop-p (nucleus) sampling parameter
messagesYesArray of message objects defining the prompt template
prompt_idYesUnique prompt identifier (from list_prompts)
max_tokensNoMaximum number of tokens for the completion
temperatureNoSampling temperature (0.0-2.0)
presence_penaltyNoPresence penalty (0.0-2.0)
frequency_penaltyNoFrequency penalty (0.0-2.0)
Behavior4/5

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

The description discloses an important behavioral trait: the version is always created as NOT deployed. This goes beyond the schema by telling the agent the resulting state, which is useful for understanding side effects and next steps. No annotations exist to contradict or supplement this.

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?

The description is concise, consisting of two clear sentences with no redundant information. It is well-structured and directly conveys the essential purpose and a key behavior.

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 description covers the main purpose and a critical behavioral detail (not deployed), which is sufficient for most usage scenarios. It does not mention output or return values, but given the tool's simplicity and lack of an output schema, this gap is acceptable.

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?

The input schema already provides comprehensive descriptions for all parameters (100% coverage), so the description adds little to parameter meaning. It does not clarify relationships or provide additional context beyond what the schema already offers.

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 action (create), the resource (a new version of a prompt), and includes a key qualifier (always created as NOT deployed). This is specific and distinguishes it from related tools like create_prompt or deploy_prompt_version.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description implies when to use this tool (when needing a new version) but does not explicitly mention alternatives or conditions for using it over other tools like update_prompt_version or deploy_prompt_version. It lacks explicit usage guidance.

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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