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daemon_status_tool

Check if the Recall memory storage daemon is running and monitor its health, queue statistics, and cache performance for persistent AI assistant data.

Instructions

Check if the recall daemon is running and healthy.

The daemon provides fast (<10ms) memory storage by queueing operations and processing embeddings asynchronously.

Returns: Dictionary with: - running: Boolean indicating if daemon is running - status: Detailed status if running (uptime, queue stats, cache stats) - error: Error message if not running

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by disclosing behavioral traits: it describes the daemon's function (fast memory storage, queuing, async embeddings), and specifies the return structure with details like uptime and queue stats. It lacks explicit rate limits or auth needs, but covers core behavior adequately.

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 front-loaded with the core purpose in the first sentence, followed by relevant context and a clear return format. Every sentence adds value without redundancy, making it efficient and well-structured.

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?

Given the tool's low complexity (0 parameters), no annotations, but an output schema exists, the description is complete. It explains what the tool does, why it matters (daemon role), and details the return values, compensating for the lack of annotations and leveraging the output schema.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's function and output, which aligns with the baseline for zero parameters.

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 with a specific verb ('Check') and resource ('recall daemon'), including its health aspect. It distinguishes from siblings by focusing on daemon status rather than memory operations, file activities, or validations.

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 implies usage context by explaining the daemon's role in memory storage and asynchronous processing, suggesting this tool should be used to monitor its operational state. However, it does not explicitly state when to use it versus alternatives or provide exclusions.

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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