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vora_list_observations

Read-onlyIdempotent

List the signed-in user's recorded observations (biomarker values) with their ids, filterable by biomarker name, date range or source.

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": "vora_list_observations"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLatest observation date, YYYY-MM-DD
fromNoEarliest observation date, YYYY-MM-DD
limitNoMax rows, default 50
sourceNoOnly this source, e.g. 'mcp', 'manual', 'MyMojoHealth'
biomarkerNoCase-insensitive substring of the biomarker name, e.g. 'glucose'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered. The description usefully adds per-user scoping, but says nothing about result ordering, total counts, or pagination beyond what the annotations and schema imply.

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?

A single front-loaded sentence covering purpose, scope and filters with no filler. The trailing filter clause is slightly listy but each element earns its place.

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 an optional-parameter, read-only list tool with full schema coverage and complete annotations, this is largely sufficient; the mention of returned ids helps. Without an output schema, a line on what else each row contains (value, unit, date) would have closed the last gap.

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 100%, so every parameter including date formats, the 'mcp'/'manual' source examples, the case-insensitive substring rule and the default limit of 50 is already documented in the schema. The description only echoes the filter categories, adding no syntax or edge-case meaning beyond that.

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 names a specific verb (List) and resource (recorded observations / biomarker values) and clarifies the result includes ids plus the filterable dimensions. It does not, however, distinguish itself from near-siblings like vora_get_latest_biomarkers or vora_list_biomarkers, leaving the agent to infer the split.

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?

'signed-in user's' scopes the data implicitly, and the filter list implies when the tool is useful (browsing historical observations by biomarker/date/source). There is no explicit when-not guidance and no alternative tool is named, so an agent comparing against vora_get_latest_biomarkers gets no routing help.

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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