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Respan MCP Server

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by respanai

update_prompt_version

Update an existing prompt version with revised messages, model, or sampling parameters while keeping it undeployed. Use to refine prompt templates before deployment.

Instructions

Update an existing prompt version. Always keeps deploy: false.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stopNoUpdated array of stop sequences
modelNoUpdated model identifier (e.g. gpt-4o)
top_pNoUpdated top-p (nucleus) sampling parameter
versionYesVersion number to update (integer, from list_prompt_versions)
messagesNoUpdated array of message objects defining the prompt template
prompt_idYesUnique prompt identifier (from list_prompts)
max_tokensNoUpdated maximum number of tokens for the completion
temperatureNoUpdated sampling temperature (0.0-2.0)
presence_penaltyNoUpdated presence penalty (0.0-2.0)
frequency_penaltyNoUpdated frequency penalty (0.0-2.0)
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It discloses a key behavioral trait: always keeps deploy: false. However, it does not mention return value, potential side effects, or error conditions, leaving some behavioral aspects unclear.

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 a single sentence that is front-loaded with the purpose and includes a critical constraint. It contains no fluff and earns every word.

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

Completeness3/5

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

With 10 parameters, no output schema, and no annotations, the description is minimal. It captures the essential action and the deploy:false guarantee, but it does not explain what is returned or how this differs from closely related sibling tools beyond the deploy caveat. The schema covers parameter details, so the description is adequate but not thorough.

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 all 10 parameters, each with meaningful descriptions. The tool description adds no additional parameter semantics beyond the schema, 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 clearly states the tool's function with a specific verb and resource: 'Update an existing prompt version.' Additionally, the clause 'Always keeps deploy: false' distinguishes this tool from sibling deploy_prompt_version, making the purpose unmistakable.

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 use for modifying an existing version without deploying, but it does not explicitly mention alternatives like deploy_prompt_version or create_prompt_version. The 'Always keeps deploy: false' hints at a constraint but lacks explicit when-to-use vs. when-not-to-use 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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