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HSH Data-on-Demand

by io.github.hshintelligence

hsh-india-fundamentals

Indian listed-company fundamentals from NSE official XBRL filings — primary regulatory disclosures, no third-party data. Quarterly P&L (revenue, net profit, EPS, net margin) with YoY and QoQ growth, PLUS the annual balance sheet (assets, equity, debt, current assets/liabilities, cash) and self-computed institutional ratios: ROE, ROCE, debt/equity, current ratio, interest coverage, asset turnover. PLUS shareholding pattern (promoter %, public %, promoter-pledge governance flag). Institutional-method (ratios derived from primary filings). Values in INR crore. Pass an NSE symbol. Pay per call via x402 (USDC on Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoQuarterly or Annual.
symbolYesNSE symbol, e.g. RELIANCE, TCS, INFY, HDFCBANK.

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses data source, frequency (quarterly/annual), units (INR crore), and cost mechanism. However, it does not mention rate limits, idempotency, or response size limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is a single dense block but front-loads the main purpose and uses clear listing. Every sentence adds value, though could be structured with bullet points for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description must explain return values. It does so in detail covering P&L, balance sheet, ratios, shareholding, and units. Missing error handling or symbol validation, but overall comprehensive for a fundamentals tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but description adds value by explaining 'Pass an NSE symbol' and giving examples (RELIANCE, INFY), and clarifies period values 'Quarterly or Annual.' This exceeds the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly specifies the tool provides Indian listed-company fundamentals from NSE XBRL filings, listing exact data categories (P&L, balance sheet, ratios, shareholding). Distinguishes from siblings by its focus on fundamentals and regulatory source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States to pass an NSE symbol and notes pay-per-call, but does not explicitly guide when to use this vs. alternative tools like hsh-india-announcements. Usage context is implied but lacks explicit when/not recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation4/5

Most tools have distinct purposes, but some closely related tools (e.g., hsh-b2b-*, hsh-esg-* variants) could cause confusion. Descriptions help differentiate, but an agent might still misselect similar products.

Naming Consistency3/5

Naming convention is mixed: some tools use hyphens (hsh-b2b-contact), others use underscores (hsh_broker_data_request). While mostly readable, the inconsistency could be confusing for agents expecting a uniform pattern.

Tool Count3/5

32 tools is on the high side for a single server, but given its purpose as a data marketplace, the large number reflects a wide catalog. However, it may be overwhelming for agents to navigate.

Completeness3/5

Covers many data domains but has obvious gaps (e.g., weather, social media). The inclusion of custom data request tools (hsh_describe_data_need, hsh_broker_data_request) mitigates these gaps, allowing agents to request missing data.

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