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snickery

loki-tail-mcp

by snickery

loki_query_instant

Execute LogQL metric queries at a single point in time to get instant results for aggregations like count_over_time, ideal for monitoring snapshots.

Instructions

Run a LogQL instant query at a single point in time.

Best for metric queries like count_over_time({container="crowdsec"}[5m]). For raw log search, prefer loki_query_range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeNonow
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the instant, single-point-in-time behavior but does not mention return format, side effects, or permissions. The read-only nature is implied by 'query' but not explicitly stated, and the existing output schema mitigates missing return value details.

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 three sentences, each adding value: the first defines the core action, the second gives a metric-query use case, and the third points to an alternative tool. No fluff or repetition, and the most important information is front-loaded.

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 purpose, an example, and alternative guidance, but with only 3 parameters and zero schema descriptions, it leaves the agent without enough detail on parameter semantics. The output schema covers return values, so that is not a gap, but parameter documentation remains thin.

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 input schema has zero description coverage for parameters. The description provides an example query for the `query` parameter but does not explain the `time` (e.g., format, default 'now') or `limit` (e.g., max results) parameters. Given the low schema coverage, the description should have compensated more thoroughly.

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 uses a specific verb ('Run') and resource ('LogQL instant query') with a clear temporal scope ('at a single point in time'). It also distinguishes from the sibling tool `loki_query_range` by explicitly recommending the latter for raw log search.

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 provides explicit guidance on when to use this tool: 'Best for metric queries' with a concrete LogQL example. It also names the alternative for raw logs ('prefer `loki_query_range`'), covering both use and non-use cases.

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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