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Gale Finance

Compare two assets' performance and risk

compare_assets
Read-onlyIdempotent

Compare two assets using Gale Finance's published pair pages: the rolling 1Y compare (default), a calendar-year compare (horizon "2024"), or the long-term scorecard with year-by-year returns (horizon "long_term"). Pairs resolve in either order and keep the cited page's A/B labels. When Gale has no pair page, returns each asset's own metrics side by side and says pair figures are not published. Example: "How has gold performed vs bitcoin historically?".

Input Schema

NameRequiredDescriptionDefault
asset_aYesFirst asset: ticker, name, or alias
asset_bYesSecond asset: ticker, name, or alias
horizonNo"1y" (default), a calendar year such as "2024", or "long_term"

Output Schema

NameRequiredDescriptionDefault
notesNo
periodNo
statusYes
asset_aNo
asset_bNo
metricsNo
drawdownsNo
win_tallyNo
candidatesNo
source_urlYesCanonical Gale page holding these figures
correlationNo
source_kindNo
source_urlsNo
data_throughYesData-through date (YYYY-MM-DD) of the cited figures
horizon_noteNo
method_notesNo
source_labelNoWhich published Gale source the figures come from
year_by_yearNo
ambiguous_sideNo
best_worst_dayNo
overall_winnerNo
best_worst_yearNo
methodology_urlYes
rolling_returnsNo
orientation_noteNo
per_asset_windowsNo
requested_horizonYes
available_horizonsNoHorizons Gale publishes for this pair: 1y, calendar years, long_term
correlation_yearlyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, closed-world and non-destructive behavior, so the description's added value is the fallback semantics: when no pair page exists it returns each asset's own metrics side by side and explicitly flags that pair figures are unpublished. It also discloses that pairs resolve in either order and that the cited page's A/B labels are preserved, which prevents label confusion. No rate limits or latency notes, but that is minor here.

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?

Front-loaded with the core action and the mode options, then the fallback, then an example. Dense but every sentence carries information; the embedded quoting of horizon values is slightly awkward but not wasteful.

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 an output schema present, the description need not explain return shapes, and it covers the remaining ambiguity an agent would face: mode selection, argument order, and the degraded no-pair-page path. Nothing needed to invoke this correctly is missing.

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%, so the baseline is 3, but the description adds genuine meaning: it enumerates the accepted horizon values with their default and explains that asset_a/asset_b order is irrelevant and label order follows the source page. That goes beyond the schema's terse "First asset / Second asset" wording.

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 and resource ("Compare two assets") plus the data source (Gale Finance's published pair pages) and the three comparison modes. It is clearly distinguishable from siblings like get_risk_return_metrics (single asset) or rank_assets_by_metric (ranking) without opening any schema.

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?

Gives clear context for each mode (rolling 1Y default, calendar year via horizon "2024", long-term scorecard via "long_term") and a concrete example query that shows the intended use. It does not explicitly name sibling alternatives or say when to prefer them, which keeps it below a 5.

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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