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yokozuna-mcp

by mbe24
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TypeScript
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Learn a scope's log schema in depth (propose-only)

sumo_describe_schema
Read-only

Discovers the schema of log data by stratified sampling: enumerates nested JSON keys, characterizes string payloads, and provides ranked severity fragments. Use when digest shows no-signal or for first contact with a new system.

Instructions

Thorough schema learner — the deep counterpart to the lite auto-detection inside sumo_error_digest/sumo_trend: STRATIFIED-samples the scope (per category × type/stream stratum, spread across message shapes — never first-N rows), enumerates top-level AND nested JSON keys (fill %, inferred types incl. float-strings, top values; arrays marked []), characterizes string payloads (format + severity-ish token hits) instead of returning an empty schema, breaks fields out per stratum, and closes with RANKED paste-ready severity fragments for the filter= param — each with honest caveats. It PROPOSES, never decides: it applies no filters and persists nothing; record what you confirm in your own memory. Use when a digest disclosed no-signal/zero-match or on first contact with a new system. Job budget: 2-4 aggregate jobs + 1-6 bounded page jobs, all auto-deleted. Time range: exactly ONE of last (relative, e.g. "15m", "2h"; units s/m/h/d) OR both from and to (ISO-8601 like 2026-07-02T18:28:00, or epoch milliseconds).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd time: ISO-8601 or epoch ms. Requires `from`.
fromNoStart time: ISO-8601 or epoch ms. Requires `to`.
lastNoRelative window ending now, e.g. "15m", "2h", "1d". Mutually exclusive with from/to.
queryYesScope query (keywords + metadata filters; no | operators).
maxDepthNoNested-key flattening depth (default 4); arrays marked [].
timeZoneNoIANA timezone for query-time parsing (default UTC).
sampleSizeNoMessages sampled for key enumeration (default 200, cap 1000).
stratifyByNoExplicit stratification field: an absolute JSON path from the _raw root (e.g. log.type, stream). Default: auto-detected (log.type, then stream, then category-only).
byReceiptTimeNoSearch by receipt time; recommended true for very recent windows (ingestion lag).

Tool Definition Quality

A4.8/5.0
Behavior5/5

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

Adds extensive behavioral context beyond annotations: 'PROPOSES, never decides', auto-deletion of jobs, stratified sampling strategy (not first-N), and honest caveats on output. Annotations only indicate readOnlyHint=true, which is consistent.

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 relatively long but well-structured with clear sections. Every sentence provides value, though it could be slightly more compact. The use of colons and lists aids readability.

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?

Given the tool's complexity (9 parameters, no output schema), the description is thorough: covers sampling, output format hints (ranked severity fragments), budget, and parameter relationships. No missing critical context.

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% with descriptions for all 9 parameters. The description adds extra usage context like mutual exclusivity of time parameters and default auto-detection for stratifyBy, enhancing understanding beyond the schema.

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 tool is a 'thorough schema learner' and 'deep counterpart' to lite detection in siblings. It details stratified sampling and key enumeration, and distinguishes itself by being 'propose-only' and never deciding.

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?

Explicit usage guidance: 'Use when a digest disclosed no-signal/zero-match or on first contact with a new system.' Also specifies budget and time range constraints, implying when not to use (when a quick schema suffices).

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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