latest_navFast single-value lookup of a mutual-fund scheme's latest NAV (net asset value) from MFAPI. Returns the most recent NAV, its date, and basic scheme metadata. Use search_schemes to find a scheme_code first (e.g. 118550). Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| scheme_code | Yes | AMFI scheme code, e.g. 118550. Get one from search_schemes. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. Description adds detail about returning the most recent NAV, date, and basic metadata, and mentions it's keyless. Does not contradict annotations, but adds only moderate extra context beyond them.
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?
Two sentences, concise and front-loaded with the purpose. Every sentence adds value: purpose, return info, usage guidance, and keyless mention. No wasted words.
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 simple one-parameter tool with no output schema but rich annotations, the description explains return values (NAV, date, metadata) and mentions keyless key property. Adequately complete for its complexity.
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 is 100%, with parameter description already including an example and reference to search_schemes. Description repeats this guidance, adding minimal new value. Baseline 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?
Description clearly states it performs a fast single-value lookup of the latest NAV for a mutual-fund scheme. It specifies the verb (lookup), resource (latest NAV), and distinguishes from siblings by referencing search_schemes for obtaining the scheme_code.
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?
Explicitly instructs to use search_schemes first to find the scheme_code, providing clear context for when to use this tool. Does not specify when not to use or name alternatives explicitly, but the single-value nature implies it's not for history.
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.
Each tool has a clear, distinct purpose. The various `ask_pipeworx*` variants are differentiated by mode (single vs grounded vs research). `get_nav_history` vs `latest_nav` serve different query granularities. Administrative tools like `remember`/`recall`/`forget` are clearly separate. No two tools overlap in functionality.
Tool names follow a consistent snake_case convention and generally use `verb_noun` order (e.g., `ask_pipeworx`, `search_schemes`, `validate_claim`). A few exceptions like `entity_profile` (noun_verb) exist, but the pattern is mostly predictable.
At 34 tools, the server is quite large, including many specialized tools (e.g., multiple Polymarket tools, administrative memory/subscription tools) that could arguably be split into separate servers. The number feels slightly excessive for a coherent, focused server.
The tool set covers an extraordinarily wide range of domains: company financials, SEC filings, FDA drugs, economic data, mutual funds, real estate, prediction markets, npm dependencies, AI visibility, and more. It also includes memory, subscription, and feedback mechanisms. There are no obvious gaps for the domains addressed.