Get USD NAV history for a GIFT City IFSC fund. Supports optional date range filtering.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | End date in YYYY-MM-DD format (optional) | |
| from | No | Start date in YYYY-MM-DD format (optional) | |
| scheme_code | Yes | GIFT City fund code (e.g. GIFT-PP-NASDAQ) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the core function and optional date filtering but omits details such as response format, pagination, error behavior, or any limits, which is a significant gap for a data-retrieval tool.
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 short sentences that immediately state the tool's purpose and optional filtering. There is no redundant information, making it highly efficient and well-structured.
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?
The tool is low-complexity (simple read operation, 3 params, no nested objects) and the schema covers parameters. However, with no output schema and no annotations, the description does not mention the return structure or any behavioral caveats, leaving some incompleteness for a historical data tool.
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 description coverage is 100%, so all three parameters (scheme_code, from, to) are documented in the schema. The description does not add meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 clearly specifies the verb 'Get' and resource 'USD NAV history' scoped to 'GIFT City IFSC fund'. This distinguishes it from sibling tools like get_nav_history, which likely covers non-GIFT funds, and get_latest_nav, which focuses on the most recent value.
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 implies usage for GIFT City IFSC fund NAV history but does not explicitly state when to prefer this over alternatives like get_nav_history. No exclusions or when-not-to-use guidance is provided, leaving the context implicit.
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.
