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palinode_prompt

List, read, or activate versioned LLM prompts stored as memory files. Filter prompts by task type and set an active version.

Instructions

List, read, or activate versioned LLM prompts stored as memory files in the prompts/ directory. Use 'list' to browse available prompts, 'read' to view a specific prompt's content, or 'activate' to set a prompt version as active (deactivates others of the same task).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoPrompt name (required for 'read' and 'activate')
taskNoFor 'list': filter by task type
actionYesAction to perform: 'list', 'read', or 'activate'list
Behavior4/5

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

Annotations set readOnlyHint=false, destructiveHint=false, etc. The description adds behavioral context: 'activate' deactivates others of the same task, indicating side effects. This goes beyond annotations by disclosing the deactivation behavior.

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 two sentences, front-loading the main purpose and then detailing actions. Every sentence is essential, no redundancy.

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?

The tool has 3 parameters and no output schema. The description covers all actions, parameter dependencies, and side effects (deactivation). It is sufficient for an agent to correctly invoke the tool.

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 description coverage is 100%. The description adds value by explaining that 'name' is required for 'read' and 'activate', and 'task' is a filter for 'list'. It clarifies parameter usage beyond the schema's basic descriptions.

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 purpose: 'List, read, or activate versioned LLM prompts stored as memory files in the prompts/ directory.' It uses specific verbs (list, read, activate) and resource (prompts), distinguishing it from sibling tools that focus on other aspects like doctor, list, etc.

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?

The description provides clear context for each action: 'Use 'list' to browse available prompts, 'read' to view a specific prompt's content, or 'activate' to set a prompt version as active (deactivates others of the same task).' It does not explicitly mention when not to use or alternatives, but the action enum itself covers the main choices.

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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