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JerBouma

Finance Toolkit

search_metrics

Read-onlyIdempotent

Search financial metrics by keyword with typo tolerance. Handles common abbreviations and minor typos to return relevant matches.

Instructions

Search across all metrics by keyword with typo tolerance.

    Supports minor typos and common financial abbreviations. Tokens
    shorter than four characters bypass fuzzy matching and require an
    exact substring hit.

    Args:
        query: Free-text search string, e.g. ``'debt'``,
            ``'moving average'``, ``'sharpe'``, or ``'retun on equty'``.

    Returns:
        str: Markdown table of matching tools sorted by relevance score,
            or a guidance message when no strong matches are found.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFree-text keyword to search across all metric names and descriptions, e.g. 'sharpe', 'debt', or 'moving average'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Beyond annotations (read-only, idempotent, non-destructive), the description adds key behaviors: typo tolerance, fuzzy matching conditions for short tokens, return format (Markdown table sorted by relevance), and a fallback guidance message. This significantly aids agent expectations.

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 concise with no wasted words. It front-loads the main purpose, then provides structured Args/Returns sections. The docstring format is clear and scannable.

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?

For a simple search tool with one parameter, the description is complete: it covers purpose, matching behavior, query examples, return format, and edge cases (short tokens, no matches). The output schema exists (not shown here) but the description explains the return well.

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% and the schema defines 'query' as free-text. The description enhances this with concrete examples ('debt', 'moving average', 'sharpe', 'retun on equty') and explains fuzzy matching behavior relative to token length, adding value beyond raw 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 verb 'Search', the resource 'all metrics', and the method 'by keyword with typo tolerance'. It distinguishes from sibling tools like search_by_category by specifying the scope as metrics. Examples and return format further clarify purpose.

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?

The description provides clear context: it searches metrics by keyword with typo tolerance. It specifies that short tokens (<4 chars) require exact matches. While it doesn't explicitly state when not to use, the sibling list implies this is the go-to for metric search, and the examples guide usage effectively.

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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