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kernl

kernl

by fastslack
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kernel_facts_query

Retrieve temporal facts: what is true now or at a specified time, what was believed then, and optional full history of values and corrections.

Instructions

Facts that are true now — or were true at as_of, or as Kernl believed them at known_at. history lists every value ever recorded with when it held and whether it was corrected.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "kernel_facts_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoMatch in the subject name, predicate or value.
as_ofNoWhat was true at this moment (ISO). Default now.
limitNo
historyNoEvery value ever recorded, including ended and corrected ones.
subjectNo
known_atNoAs Kernl believed it at this moment (ISO). Default now.
predicateNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the disclosure burden and does add real behavioral context: it explains that history returns every recorded value with when it held and whether it was corrected, which is more than the schema states. It leaves implicit that this is a pure read with no side effects and says nothing about permissions or result limits.

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?

Two dense sentences with no filler, and the three temporal modes are front-loaded ahead of the history detail. The telegraphic 'Facts that are true now' opening requires the agent to infer the retrieval verb, which costs a little clarity.

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?

For a 7-parameter query tool with an output schema covering return values, the description's job is the temporal semantics, and it covers all three modes precisely. The undocumented subject/predicate/limit parameters are the schema's gap rather than something return-value or behavior prose must restate.

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 57%, so the schema already documents as_of, known_at, history and text. The description clarifies the temporal distinction between as_of (was true) and known_at (believed by Kernl), which is genuinely useful, but subject, predicate and limit have no documentation in either place, and the description does not compensate.

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 identifies the resource (facts) and the three temporal modes it can return, so an agent knows what it is querying. It never uses an explicit retrieval verb and does not distinguish itself from siblings such as kernel_facts_as_of, so the purpose is clear but the boundary is not.

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

Usage Guidelines3/5

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

Usage guidance is only implied through the explanation of as_of, known_at and history — the agent can infer when to set each mode, but there is no explicit statement of when to call this tool versus kernel_facts_as_of or kernel_facts_explain, and no 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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