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Glama

Indian NSE Stock Insights

screen_stocks

Filter the active universe. Keys: rsi_min, rsi_max, adx_min, trend, near_demand_zone, pattern, min_volume_ratio, sector. At least one required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It only lists filter keys and a requirement. It does not explain how filters are combined (AND/OR), whether results are returned as a list, or any side effects. This leaves significant behavioral ambiguity.

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

Conciseness5/5

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

The description is a single sentence that front-loads the action. It lists the keys efficiently and has no fluff. Every word earns its place, making it highly concise and well-structured.

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

Completeness2/5

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

Despite having an output schema (not visible), the description lacks critical context about the tool's behavior and filter semantics. It does not explain how multiple filters interact or what the output represents. For a tool with a complex filter object and no schema descriptions, this is incomplete.

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

Parameters2/5

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

The schema is generic (an object with additionalProperties), so the description is the only source of parameter meaning. It lists key names but lacks types, formats, or examples. With 0% schema coverage, the description only partially compensates; users would not know if rsi_min is a number or trend is a string.

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 'Filter the active universe' clearly states the tool's purpose with a specific verb and resource. It distinguishes from sibling tools that focus on individual stock analysis or specific data retrieval, as this is a screening tool for the entire universe.

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?

The description implies usage for filtering stocks based on criteria but does not explicitly state when to use this tool versus alternatives like get_technical_indicators. The 'At least one required' note gives minimal usage guidance but lacks exclusions or alternative references.

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

A3.5/5.0
Disambiguation5/5

Each tool targets a distinct aspect of stock analysis: quotes, OHLC data, technical indicators, patterns (single vs multi-bar), levels (support/resistance, Fibonacci, demand/supply), volume, market overview, comparison, and screening. Overlapping concepts are clearly differentiated by granularity and methodology.

Naming Consistency4/5

Most tools follow the 'get_' prefix with snake_case nouns, but 'compare_stocks' and 'screen_stocks' omit the prefix. Despite this minor deviation, the overall verb_noun convention is consistent and readable.

Tool Count5/5

With 12 tools, the server is well-scoped for an NSE stock insights platform. Each tool earns its place by covering a distinct analytical need, ranging from raw data retrieval to advanced pattern detection and screening.

Completeness5/5

The tool surface comprehensively covers the technical analysis domain: market-wide context, quotes, historical candles, indicators, pattern recognition, price levels, volume analysis, comparative analysis, and stock screening. No obvious gaps for the stated purpose.