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by kuklaph

Edit System Preference

cascade_edit_preference

Update a single Cascade system preference by name and value; changes apply server-wide immediately. Requires system-admin credentials.

Instructions

Update a single Cascade system preference.

Accepts a preference object with name and value. The name must exactly match an existing preference key (see cascade_read_preferences for the full list); value is always sent as a string, even for numeric or boolean preferences (Cascade parses it). Changes take effect server-wide immediately. Requires system-admin-level credentials.

Args:

  • preference (object, required, shape varies — see Cascade docs): The preference to update

    • name (string, required): Exact preference key

    • value (string, required): New value (serialized as string even for numbers/booleans)

Returns: Cascade OperationResult: { success: true } On failure: { success: false, message: "" }

Examples:

  • Use when: "Increase the server's API timeout" -> { preference: { name: "api.request.timeoutSeconds", value: "60" } }

  • Use when: "Toggle a feature flag" -> { preference: { name: "feature.somefeature.enabled", value: "true" } }

  • Don't use when: You want to read current values — use cascade_read_preferences first.

  • Don't use when: The target is user-scoped — system preferences are server-wide.

Error Handling:

  • "Preference not found" when name is not a recognized key

  • "Invalid value" when value can't be parsed for the preference's type

  • "Permission denied" when credentials lack system-admin rights. Responses are JSON text; structuredContent is authoritative when the response fits. Oversized responses return bounded _cache metadata for cascade_read_response. For cascade_read, read_mode controls preview versus raw Cascade payload shape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
preferenceNoREQUIRED: The preference to create or update. Shape: `{ name: string, value: string }`.
Behavior5/5

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

Annotations indicate readOnlyHint=false (mutation) and no destruction or idempotency. The description adds critical context: changes take effect server-wide immediately, requires system-admin credentials, and details error handling (preference not found, invalid value, permission denied). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main action and usage guidelines, but it includes a large boilerplate block after 'Error Handling' that discusses generic response handling and unrelated tools (e.g., cascade_read_response, cascade_read). This extraneous text reduces conciseness and relevance.

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 tool is simple with one parameter and no output schema. The description explains the return format (OperationResult), error cases, and essential behavior. However, the irrelevant boilerplate at the end slightly detracts from coherence, but the core information is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds substantial meaning beyond the schema: it explains the name must exactly match an existing key, value is always a string (even for numbers/booleans), and Cascade parses it. The Args section mirrors and elaborates on the schema, providing clear constraints.

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 'Update a single Cascade system preference,' specifying a precise verb and resource. It distinguishes from siblings by referencing cascade_read_preferences for reading and implying system-level scope, differentiating it from user-scoped tools.

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?

Explicit 'Use when' and 'Don't use when' examples guide the agent on appropriate usage, including alternatives like cascade_read_preferences and clarifying that it is not for user-scoped preferences. This provides clear context for when to invoke this tool versus others.

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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