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crunchtools

mcp-syslog

by crunchtools

syslog_context_tool

Retrieve log entries around a given timestamp to correlate failures with surrounding events, filtering by source or severity as needed.

Instructions

Return log entries surrounding a specific moment.

Use this after an alert names a time. Omitting source spans the whole fleet, which is how a failure gets correlated with whatever else was happening.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum entries to return.
sourceNoRestrict to one source. Omit to span all sources.
severityNoOptional minimum severity.
timestampYesThe moment of interest — ISO-8601, or relative like '30m' ago.
after_secondsNoHow far forward from the timestamp to include.
before_secondsNoHow far back from the timestamp to include.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It reveals that omitting source spans all sources, a useful trait, but does not state read-only-ness, response format, ordering, or potential limits. The presence of an output schema mitigates the missing return details, but the description alone leaves several behavioral aspects unaddressed.

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?

Two sentences with zero waste. The primary purpose is front-loaded, and the usage hint follows naturally. Every word earns its place; no redundancy.

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?

For a tool with a fully documented schema and an output schema, the description provides sufficient context to call it correctly. It covers the primary use case and a helpful tip about fleet correlation. Minor gaps like time-range boundaries or default behavior are not critical given the complete schema.

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 description coverage is 100%, so all parameters are already documented. The description repeats the source-omission point already in the schema and adds usage context, but no new parameter-level meaning. The description contributes minimal value beyond the schema, so the baseline 3 applies.

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 it returns log entries around a specific moment, which is a distinct action from grep, search, or tail. However, it does not explicitly differentiate itself from sibling tools, so the purpose is clear but not maximally disjoint.

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 gives an explicit trigger: 'Use this after an alert names a time.' It also explains a key usage pattern (omitting source for fleet-wide correlation) but does not mention which sibling to use instead in other scenarios, so it provides context without alternatives.

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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