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get_stock_prices

Read-onlyIdempotent

Get daily stock price history (OHLCV) for an NZX company. Use for price trends, returns, and technical context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date (YYYY-MM-DD)
daysNoNumber of recent trading days (default 30)
fromNoStart date (YYYY-MM-DD)
tickerYesNZX ticker symbol

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool payload. Null when the call did not produce one — read meta.availability_status to find out why, and do not treat null as zero, empty or "none found".
metaYes
toolYesTool that produced this result.
schema_versionYesEnvelope contract version. Bumps only on a breaking shape change.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / days / minimum
      Added value: +1
    • changedInput schema / properties / days / type
      Previous value: -"number"New value: +"integer"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "data": {
      +      "description": "The tool payload. Null when the call did not produce one — read meta.availability_status to find out why, and do not treat null as zero, empty or \"none found\"."
      +    },
      +    "meta": {
      +      "additionalProperties": true,
      +      "properties": {
      +        "availability_status": {
      +          "description": "ok: complete payload. truncated: payload exceeded the transport cap and was cut. parse_failed: payload is text this server could not parse as JSON. error: the tool raised.",
      +          "enum": [
      +            "ok",
      +            "truncated",
      +            "parse_failed",
      +            "error"
      +          ],
      +          "type": "string"
      +        },
      +        "encoding": {
      +          "description": "toon = pipe-delimited tabular encoding; header row names the columns.",
      +          "enum": [
      +            "json",
      +            "toon"
      +          ],
      +          "type": "string"
      +        },
      +        "provenance": {
      +          "description": "Whether the figures can cite a source document. \"undeclared\" means no claim has been made for this endpoint yet — it is not a claim that the data is unsourced.",
      +          "enum": [
      +            "direct",
      +            "label",
      +            "reachable",
      +            "none",
      +            "undeclared"
      +          ],
      +          "type": "string"
      +        },
      +        "retrieved_at": {
      +          "description": "When this platform produced the answer — NOT the as-at date of the data.",
      +          "format": "date-time",
      +          "type": "string"
      +        },
      +        "warnings": {
      +          "items": {
      +            "type": "string"
      +          },
      +          "type": "array"
      +        }
      +      },
      +      "required": [
      +        "retrieved_at",
      +        "availability_status",
      +        "provenance"
      +      ],
      +      "type": "object"
      +    },
      +    "schema_version": {
      +      "description": "Envelope contract version. Bumps only on a breaking shape change.",
      +      "type": "string"
      +    },
      +    "tool": {
      +      "description": "Tool that produced this result.",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "schema_version",
      +    "tool",
      +    "data",
      +    "meta"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds that the data is daily history with OHLCV fields, giving useful behavioral context beyond the annotations. It does not discuss adjustment policy or missing-ticker behavior, but those are minor given the annotations and output schema.

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 two short sentences with the core operation front-loadedley and no filler or repetition of schema fields. Every sentence contributes to selection or invocation.

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?

With a full output schema, 100% parameter coverage, and clear annotations, the description is complete for a low-complexity read-only tool. Nothing that an agent needs to call it correctly is 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%, so ticker, from, to, and days are already documented in the input schema. The description adds no parameter-level detail beyond the schema, so the baseline score of 3 is appropriate.

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 uses a specific verb and resource: 'Get daily stock price history (OHLCV) for an NZX company.' It names the data format and explicit use cases, which distinguishes it from sibling tools like get_daily_market_wrap and get_technical_signals.

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?

It explicitly says 'Use for price trends, returns, and technical context,' which gives clear routing guidance. It does not name alternatives or state when not to use it, but the use-case list is sufficient for most selection decisions.

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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