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Glama

check_data_quality

Read-onlyIdempotent

Audit an asset's price history for missing closes, zero-volume bars, gaps, stale data, and suspicious moves before trusting or analyzing long-term figures. Returns an overall verdict.

Instructions

Audit an asset's price history before trusting figures built on it: missing closes, zero-volume placeholder bars, gaps, suspicious one-session moves (unadjusted splits, redenominations, provider errors) and a stale latest bar, with an overall verdict. Use it when a result looks surprising or before a long-period analysis.

Input Schema

NameRequiredDescriptionDefault
endNoOptional ISO end date; defaults to today.
startNoOptional ISO start date, e.g. '2023-01-01'.
periodNoLookback ending at `end`. Ignored when `start` is given.5y
symbolYesA symbol returned by search_assets.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.1.9
    • addedInput schema / properties / period / anyOf
      Added value: +[
      +  {
      +    "enum": [
      +      "1m",
      +      "3m",
      +      "6m",
      +      "ytd",
      +      "1y",
      +      "3y",
      +      "5y",
      +      "10y",
      +      "max"
      +    ],
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedInput schema / properties / period / enum
      Removed value: -[
      -  "1m",
      -  "3m",
      -  "6m",
      -  "ytd",
      -  "1y",
      -  "3y",
      -  "5y",
      -  "10y",
      -  "max"
      -]
    • removedInput schema / properties / period / type
      Removed value: -"string"
  2. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld, so the safety profile is covered structurally. The description goes beyond that by disclosing the specific anomaly classes it inspects and that it returns an overall verdict, which tells the agent what the operation actually examines. It does not mention latency, provider coverage, or failure modes, keeping it at a 4.

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 diagnostic payload is front-loaded in the first clause, the enumerated checks follow, and the single usage sentence is last. Every clause carries information and nothing is redundant.

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 must convey what comes back, and it does — the listed anomaly checks plus an overall verdict. For a read-only, idempotent tool with fully documented parameters, that is nearly complete; only the precise response shape (per-check detail vs summary) remains unspecified.

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 symbol, start, end, and period are all documented in the schema itself. The description adds no additional parameter meaning beyond a passing reference to 'long-period analysis', so the baseline 3 applies.

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?

States a specific verb (audit) and resource (an asset's price history) and enumerates exactly what the audit detects: missing closes, zero-volume bars, gaps, suspicious one-session moves, and stale latest bars, plus an overall verdict. This is far more specific than a tautology and clearly positions it as a diagnostic tool rather than a summary or comparison tool.

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?

Explicitly says when to use it: when a result looks surprising or before a long-period analysis. That is a concrete trigger condition. However, it names no alternatives or exclusions (e.g., when get_price_summary or explain_price_move would be the better first stop), so it stops short of 5.

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