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SavageCore

autobrr-mcp

by SavageCore

autobrr_system

Read-only

Perform autobrr system operations: check for updates, verify liveness and readiness, fetch latest update info, and list log files.

Instructions

autobrr system operations on autobrr. Pass operation and an arguments dict matching that operation's parameters.

  • autobrr_check_updates() — Trigger an update check against the GitHub releases API. WRITE: this modifies your autobrr instance.

  • autobrr_get_healthz_liveness() — Liveness probe - returns "OK".

  • autobrr_get_healthz_readiness() — Readiness probe - returns "OK" when the database is reachable, otherwise errors.

  • autobrr_get_latest_update() — Fetch the latest release info autobrr has seen.

  • autobrr_list_log_files() — List available log files (name, size, updated_at).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

The annotation declares readOnlyHint=true, but the description explicitly labels autobrr_check_updates as a WRITE operation that modifies the autobrr instance. This is a direct contradiction, triggering a score of 1 regardless of additional transparency.

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 well-structured bulleted list of operations, each with a concise, informative one-liner. It front-loads the general invocation pattern and avoids redundant or filler content.

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?

The description covers the purpose and basic behavior of each operation, including return values for health checks. However, it omits per-operation argument specifications and lacks explicit usage guidelines or exclusions, and the annotation contradiction undermines completeness. The presence of an output schema reduces the need to explain return formats, but the parameter gap remains.

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

Parameters2/5

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

The description gives generic guidance to pass an 'arguments' dict matching the operation's parameters but does not detail what arguments each operation accepts. With schema description coverage at 0%, the description fails to compensate and leaves the agent without necessary parameter details.

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 performs 'autobrr system operations' and enumerates five specific operations, each with a verb and resource. It differentiates from sibling resource-specific tools by focusing on system-level actions like health checks and update checks.

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 conveys the tool is for system operations, which implies a scope distinct from sibling tools that manage specific resources. However, it does not explicitly state when not to use this tool or mention alternatives, though the operation list provides clear context.

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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