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k9fr4n

thruk-mcp

by k9fr4n

thruk_worker_health

Detect mod-gearman worker blind spots by scanning hosts and services for worker artefacts, distinguishing real outages from supervision gaps.

Instructions

Distinguish a real outage from a mod-gearman supervision blind spot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows scanned per object type (max 5000, default 500).
backendsNoComma-separated backend names (sites). Omit for all backends.
sample_limitNoMaximum example rows returned in 'samples' (default 20).
include_hostsNoAlso scan /hosts host checks for worker artefacts (default true).
include_servicesNoScan /services for worker artefacts (default true).
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only states 'distinguish,' giving no indication of side effects, permissions, rate limits, or whether the tool is read-only. Key behaviors such as data scanning limits (inferred from parameters) are not mentioned in the description.

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

Conciseness4/5

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

The description is extremely concise (one sentence, no filler). It lacks structured formatting (e.g., bullet points), but for such brevity, the lack of structure is acceptable. Every word serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and moderate complexity (5 parameters), the description is insufficient. It fails to explain what the output contains, how to interpret results, or how the tool differentiates real outages from blind spots. Users are left without enough context to use it effectively.

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 coverage is 100%, so the schema already documents all five parameters. The description adds no extra meaning beyond the schema, meeting the baseline of 3. However, it does not synthesize parameter behavior (e.g., that limit and sample_limit control scanning and output).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: distinguishing a real outage from a mod-gearman supervision blind spot. This provides a specific verb ('distinguish') and resource ('mod-gearman supervision blind spot'), setting it apart from general health checks like thruk_backend_health. However, it lacks explicit mention of 'worker health' or 'Thruk workers', which could be more precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like thruk_backend_health, thruk_concurrent_failures, or thruk_problems. The description implies a diagnostic scenario but does not specify context, prerequisites, or 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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