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myers-gh1328

tiny-loki-mcp

by myers-gh1328

loki_query

Execute bounded LogQL range queries to retrieve compact log records with known selectors and text filters.

Instructions

Run a bounded LogQL range query and return compact log records. Use this when you already know the LogQL selector or need text filters. Do not use this for unbounded or long-history searches; since and limit are capped by server configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesBounded LogQL query, for example {host="example"} |= "error".
sinceNoLookback duration such as 30m, 2h, or 1d.30m
limitNoMaximum log entries to return.
Behavior4/5

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

No annotations provided, so description must carry the burden. It mentions that the query is bounded and that since and limit are capped, implying read-only behavior. However, it does not detail error handling, authentication requirements, or the exact response format beyond 'compact log records'.

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 extremely concise (two sentences) with no unnecessary words. The first sentence captures purpose and output, the second provides usage guidance. Every sentence earns its place.

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?

Given no output schema, the description explains the return value ('compact log records') but not its structure. The three parameters are all documented in the schema, and the description adds context about server caps. This is generally sufficient for a simple query tool, though more detail on the response format would improve completeness.

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 coverage is 100%, but the description adds value by clarifying that since and limit are subject to server configuration caps, which is not in the schema. It also describes the output as 'compact log records', though the schema does not define output.

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 verb 'Run', the resource 'bounded LogQL range query', and the output 'compact log records'. It effectively distinguishes from sibling tools like loki_labels and loki_recent by specifying that this tool is for LogQL queries with text filters.

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?

The description explicitly states when to use ('when you already know the LogQL selector or need text filters') and when not to use ('Do not use for unbounded or long-history searches'), and mentions server-side caps on since and limit. This provides clear decision support.

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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