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rj250792

Tijori Finance MCP

by rj250792

screen_companies

Identify Indian companies by financial metrics such as ROE or debt ratios, or by business relationships like revenue from a region. Supports presets, field comparisons, and SME screening.

Instructions

Screen companies by financial metrics and/or business data. Pass 'preset' (a popular screen name from list_popular_screens, e.g. 'Cash Flow Machines'), OR 'filters' and/or 'alternate'. 'filters' accepts a query string like '( ROE > 15 ) and ( Market Capitalization > 500 )' or a shorthand object like {roe:{min:15}, debt_to_equity:{max:0.5}}. Query strings support any field name from search_screener_fields, % values ('ROCE > 20%'), field-vs-field comparisons ('Net Sales > 3Yrs ago Net Sales'), and arithmetic ('capex/Net Block > 0.5'). 'alternate' is a business-data query using relationships: 'makes ', 'revenue from <product/region> > N', 'market share > N', 'uses ', 'caters to ', 'has plant in ' — combinable with AND/OR/NOT, e.g. 'market share > 50' or 'revenue from Defence > 50'. Product/region names come from search_screener_fields with type Products/Regions. Optional flags: latest_results_only (only companies that reported the latest quarter), superstar_investors (only companies a superstar/whale investor holds — adds a 'whales' column), sme (search the SME-listed universe instead of mainboard). 'limit' caps returned rows (default 50) and 'offset' pages through the rest (e.g. offset: 50 for rows 51-100 — served from cache, no refetch); total_results always reports the full match count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
smeNo
limitNo
offsetNo
presetNo
filtersNo
alternateNo
latest_results_onlyNo
superstar_investorsNo
Behavior4/5

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

With no annotations, the description fully discloses behavior: it's a read-only screening operation. It details pagination with limit/offset, caching for offset >0, reporting of total_results, and flags that modify results (latest_results_only, superstar_investors, sme). No contradictions noted.

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?

The description is long but well-organized, starting with the core purpose and then detailing each parameter. Every sentence adds value. It could be slightly more structured (e.g., bullet points), but for a complex tool it is clear and efficient.

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?

Given the complexity (8 params, no output schema, no annotations), the description covers all necessary aspects: usage modes, syntax, flags, pagination, caching. It does not describe the output format explicitly, but the tool's purpose implies a list of companies with columns. Overall, it provides sufficient context for an AI agent to use the tool correctly.

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

Parameters5/5

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

Schema coverage is 0%, so the description carries the full burden. It explains each of the 8 parameters: preset, filters (with two formats and examples), alternate (with relationship grammar), latest_results_only, superstar_investors, sme, limit, and offset (including caching behavior). This is comprehensive and highly useful.

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?

The description clearly states it screens companies by financial metrics and/or business data, with two distinct modes (preset or filters/alternate). It distinguishes itself from sibling tools like list_popular_screens (which lists preset names) and search_screener_fields (which lists available fields) by being the actual screening execution tool.

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

Usage Guidelines4/5

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

The description explicitly tells when to use each mode: 'Pass preset... OR filters and/or alternate.' It provides detailed syntax for filters (query string or object) and alternate (relationship-based queries). It lacks explicit guidance on when NOT to use this tool (e.g., for simple company lookup), but the context is clear enough.

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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