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samvallad33

Vestige

by samvallad33

system_status

Retrieve combined system health and statistics, including status, cognitive module health, warnings, and recommendations, to diagnose issues in one call.

Instructions

Combined system health and statistics. Returns status (healthy/degraded/critical/empty), full stats, FSRS preview, cognitive module health, state distribution, warnings, and recommendations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schema_introspectionNoWhen true, extends the response with a 'schema' block carrying the SQLite schema version, per-table row counts + column lists, and embedding-coverage convenience fields. Default: false (response shape unchanged). Use this for audit / migration-guard / downstream-upgrade scripts that otherwise have to read SQLite directly.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.6.0
  2. Removedv2.3.0
  3. First observedv2.1.27

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden of behavioral disclosure. It compensates well by stating the return value semantics, possible status values (healthy/degraded/critical/empty), and the main output sections. It does not explicitly confirm the tool is read-only, but 'Returns' plus the diagnostic nature of the output strongly imply a non-mutating operation.

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 compact, front-loaded with the core purpose, and uses a single follow-up sentence to list the return contents. Every phrase earns its place, and the response is no longer than needed to convey the tool's scope.

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?

There is no output schema, so the description does the work of explaining return values; it lists the major response components in enough detail for an agent to know what to expect. Some terms like 'full stats' and 'recommendations' remain general, but the optional parameter is well-covered by the schema and no required parameters or complex inputs are missing.

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%, and the single optional schema_introspection parameter is thoroughly documented in the input schema, including its effect on the response and when to use it. The tool description itself adds no parameter-specific meaning, but per the baseline for high schema coverage, no compensation is required.

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 the tool is a combined health and statistics reporter, enumerating the returned categories (status, stats, FSRS preview, cognitive module health, state distribution, warnings, recommendations). The verb 'Returns' and resource 'system health and statistics' make the operation clear, though it does not explicitly contrast itself with the sibling memory_health tool.

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?

The usage context is implied by 'Combined system health and statistics' and the listed output categories, suggesting a high-level diagnostic overview. However, there is no explicit when-to-use guidance or mention of alternatives such as memory_health or memory_timeline, leaving the agent to infer selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.