Get USD-denominated performance metrics for a GIFT City IFSC fund. Returns trailing returns (1W/1M/3M/6M/1Y/3Y/5Y/10Y/YTD), Sharpe, Sortino, and max drawdown.
| Name | Required | Description | Default |
|---|---|---|---|
| scheme_code | Yes | GIFT City fund code (e.g. GIFT-PP-NASDAQ, GIFT-PP-SP500, GIFT-EDEL-CHINA, GIFT-DSP-GLOBAL) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It transparently states this is a read operation returning performance metrics and lists them (trailing returns, Sharpe, Sortino, max drawdown). It does not mention error behavior or data freshness, but for a read-only metrics tool this is a reasonable disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the purpose and scope, the second enumerates the output metrics. Every word contributes value, and it is front-loaded with the tool's core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read-only metrics tool with no output schema, the description is sufficiently complete: it specifies the input type and the full expected output metric set. It could mention data as-of date or response format, but the listed metrics set clear expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for the sole parameter is 100%, with the scheme_code description and examples already documenting valid GIFT City fund codes. The tool description adds the USD-denominated/GIFT City framing, which reinforces the schema but does not materially add new parameter-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and identifies the exact resource: USD-denominated performance metrics for a GIFT City IFSC fund. It enumerates the returned metrics, clearly distinguishing it from sibling tools like get_metrics or get_sif_metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly scopes the tool to GIFT City IFSC funds with USD-denominated metrics, giving the agent context on when to use it. It does not explicitly name alternatives or state when-not-to-use, but the GIFT City/USD framing is directional enough against siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are mostly distinct, with clear prefixes (gift, nps, sif) separating fund types. Some overlap exists among metrics/returns tools, but descriptions clarify their specific scope. Overall, an agent can differentiate tools without much ambiguity.
All tools follow a consistent snake_case verb_noun pattern (e.g., get_fund, list_categories, screen_funds). Verbs are standardized (get, list, search, compare, find, screen), making the API predictable and easy to navigate.
At 28 tools, the set exceeds the 'too many' threshold. While the domain covers multiple fund types, the count is excessive; several tools (e.g., get_metrics, get_gift_metrics, get_nps_metrics) could be consolidated with parameters. This may overwhelm agents.
The tool surface is comprehensive for a read-only mutual fund data server. It covers search, comparison, screening, NAV history, holdings, quantitative metrics, benchmarks, and specialized segments (GIFT, NPS, SIF). No critical gaps were identified.
