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save_system_prompt_template

Save system prompt templates with a name for UI dropdown access. Use at session startup for .txt files and after optimization loops to preserve the best prompt.

Instructions

Save a named system prompt template so it appears in the UI "Load template…" dropdown.

Call at session startup for every .txt file in prompt-lab/system-prompts/: save_system_prompt_template(name=, content=)

Also call after a successful optimization loop to preserve the best prompt found.

Templates persist in Redis. Saving with the same name replaces the previous version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesTemplate name (shown in UI dropdown)
contentYesSystem prompt text
Behavior4/5

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

Despite no annotations, description discloses persistence in Redis and overwrite behavior on same name. This is sufficient for a simple write operation. Could mention error handling or idempotency implications, but overall transparent.

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?

Six sentences, each adding unique value: purpose, usage patterns, persistence, replace behavior. No fluff or repetition. Well-structured for quick comprehension.

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?

Tool has simple params, no output schema, but description covers purpose, usage, and persistence. Could mention return value or error scenarios, but missing info is minor given tool simplicity.

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 covers 100% of parameters with descriptions. Description adds moderate value by linking name to UI dropdown and providing example usage, but does not introduce new semantic details beyond schema.

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?

Description clearly states verb 'Save' and resource 'system prompt template' with specific UI effect ('appears in the UI Load template… dropdown'). Also gives concrete use cases (session startup, after optimization loop), leaving no ambiguity about what the tool does.

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?

Explicitly states when to call (session startup for .txt files, after optimization loop) and provides example call pattern. Lacks explicit 'when not to use' or alternatives, but usage context is clear and differentiated from siblings like save_template or set_system_prompt.

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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