Get parsed full monthly NPS portfolio holdings for a scheme where available. Current full-parser coverage is SBI Pension Funds.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max holdings (default: 100, max: 500) | |
| asset_class | No | Optional asset class filter | |
| scheme_code | Yes | NPS scheme code, e.g. SM001003 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses coverage limitations and monthly/full data scope, which is useful. However, it does not describe behavior when coverage is unavailable, the return format, or potential errors, leaving gaps in transparency.
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, front-loads the core purpose, and includes only essential context about coverage. There is no filler or redundancy.
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 description explains the tool's purpose and key coverage limitation, which is helpful. However, with no output schema and no annotations, it omits details about return format and failure behavior for non-covered schemes, leaving some contextual gaps.
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?
All three parameters have descriptions in the input schema (100% coverage), so the schema does the heavy lifting. The description adds no additional parameter-level detail beyond what is already in the schema, keeping the score at the baseline.
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') with a specific resource ('parsed full monthly NPS portfolio holdings') and adds scope via 'where available' and 'Current full-parser coverage is SBI Pension Funds.' This clearly distinguishes it from sibling tools like 'get_nps_holdings' by emphasizing 'parsed full monthly' and coverage.
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 coverage note ('where available' and 'SBI Pension Funds') implies when the tool is applicable, but it does not explicitly state when to use it versus alternatives or mention what to use for unsupported schemes. Guidance is implied rather than explicit.
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.
