Get TRI (Total Return Index) series for a benchmark index. Available: NIFTY 50, NIFTY 100, NIFTY 500, NIFTY MIDCAP 150, NIFTY SMALLCAP 250, and others.
| Name | Required | Description | Default |
|---|---|---|---|
| to_date | No | End date in YYYY-MM-DD format (optional) | |
| from_date | No | Start date in YYYY-MM-DD format (optional) | |
| index_name | Yes | Benchmark index name (e.g. "NIFTY 50", "NIFTY MIDCAP 150") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It explains that the tool returns TRI series and lists available indices, which adds context beyond the schema. However, it does not describe expected behaviors such as default date ranges, data frequency, or output format, which could be relevant 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 a single, focused sentence followed by a useful list of supported indices. It is front-loaded with the core function ('Get TRI series') and contains no wasted words. Every element contributes to understanding the tool's purpose.
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 relatively simple with 3 parameters, all documented in the schema, and no output schema, so the description does not need to explain return values. However, it lacks information about default behavior for optional date parameters and the structure or scope of the returned series. Given the absence of annotations, a bit more behavioral context would improve completeness.
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 the baseline is 3. The description adds value by providing examples of index_name values in the list of available benchmarks, but it does not elaborate on from_date/to_date beyond what the schema already states. Overall, the description complements the schema but does not significantly enhance parameter understanding.
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 states the tool's function: 'Get TRI (Total Return Index) series for a benchmark index.' It specifies the resource (benchmark index) and the type of data (TRI series), and lists available indices. This distinguishes it from sibling tools that focus on funds, NPS, or categories.
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 retrieving benchmark index TRI series but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or alternate tools. The context is clear enough for an agent to infer, but it lacks explicit decision-making guidance.
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.
