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

With no annotations, the description must carry the behavioral disclosure burden. It names the output content (OHLCV bars) and the supported asset classes, but it does not mention bar ordering, exchange-selection caveats for non-EURONEXT symbols, adjustment behavior, or error handling. Some useful transparency exists, but important nuances are omitted.

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 with no filler. The primary action is front-loaded, and the second sentence adds useful asset-class scope without bloating the definition.

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 tool is simple and the schema documents all parameters, so an agent can invoke it. However, with no output schema and no annotations, the description leaves out useful invocation-relevant details such as whether exchange must match the symbol (the default is EURONEXT, which may not work for all symbols) and the ordering/shape of returned bars.

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 description coverage is 100%, so each parameter is already documented. The description adds broad domain context ('Supports stocks, crypto, forex, futures'), but it does not add parameter-specific meaning beyond what the schema provides. The baseline 3 applies.

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 and resource: 'Fetch historical OHLCV bars for any symbol from TradingView.' This clearly distinguishes it from sibling tools like tv_get_quote, tv_get_indicators, and tv_screener, which serve different purposes (current quote, derived indicators, screening).

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 description provides clear context: use this tool when historical OHLCV candle data is needed. It does not explicitly say 'use tv_get_quote for current prices' or 'use tv_get_indicators for computed values,' but the historical bar framing makes the intended use apparent.

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

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

With no annotations, the description carries the full disclosure burden and does add useful behavioral context: RSI divergence flags, Bollinger squeeze detection, ATR stop_long/stop_short levels, the [-1,+1] composite score range, and what each optional flag produces. However, it does not reveal the return shape, that the indicators parameter defaults to ['all'] so every call computes the entire indicator set, or any data-source/error behavior.

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 dense sentences of roughly 60 words with the core purpose front-loaded and no filler. Parameter names are embedded inline (include_weekly=true, benchmark_symbol, include_score=true), making the text directly actionable for an agent without cross-referencing the schema.

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 20-parameter tool with no output schema and no annotations, the description thoroughly covers the feature and option matrix but omits the output contract: what the response contains, how weekly/benchmark/score fields appear in results, and that the default is to compute all indicators. An agent can select the tool confidently but would invoke it without knowing what it returns.

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 description coverage is only 25%, so the description must compensate. It maps the three optional features to their parameter names inline (include_weekly=true, benchmark_symbol, include_score=true) and its indicator inventory aligns with the indicators enum values. The many numeric tuning parameters (macd_fast, atr_length, sma_periods, etc.) are left to their self-explanatory names, which is passable but adds no real semantic depth.

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 opens with a specific verb and resource ('Compute technical indicators for any symbol') and enumerates the full indicator surface: RSI, MACD, Bollinger Bands with squeeze detection, EMA, SMA, ATR with stop levels, Stochastic, ADX, OBV, volume MA20/ratio, and RSI divergence flags. The sibling names (tv_get_historical_data, tv_get_quote, tv_screener) make this tool's distinct role unambiguous even without explicit comparison.

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 opening sentence establishes a clear selection context: use this tool when computed indicators are needed, as opposed to raw bars (tv_get_historical_data), a snapshot quote (tv_get_quote), or universe filtering (tv_screener). It stops short of naming those alternatives explicitly or stating when not to use this tool, but the purpose is specific enough that an agent can route correctly.

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

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

No annotations are present, so the description carries the full burden. It usefully discloses the output shape (last OHLCV bar plus percentage change), but it does not mention data delay, exchange handling, or how the interval parameter affects the returned bar. Acceptable but not rich.

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?

Single sentence, front-loaded, and free of filler. Every phrase earns its place by specifying the object, the timeframe, and the included data.

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 3-parameter read tool, the description gives the core return fields, but with no output schema and no annotations it should also clarify interval/exchange behavior and the reference period for the percentage change. Adequate with clear 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?

Schema coverage is only 33%: only 'symbol' has a description, while 'exchange' and 'interval' are undocumented. The description adds no meaning for exchange or interval and does not compensate for the low coverage.

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'), names the resource ('latest price quote for a symbol'), and states the exact payload ('last OHLCV bar plus percentage change from the previous bar'). The words 'latest' and 'last bar' clearly distinguish it from tv_get_historical_data and the other siblings.

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 description implies usage for obtaining a current snapshot rather than historical data or indicators, but it never explicitly states when to choose this tool over its siblings. There are no exclusions or alternative routing hints.

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

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

With no annotations, the description carries the burden of explaining behavior. It does disclose output fields ('price, volume and RSI data') and the market coverage for France and America. It does not explain how 'top matches' are ordered, how limit interacts with results, or whether RSI bounds are inclusive.

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?

Three concise sentences that front-load the core purpose, then the key market values, then the return data. There is no filler or repetition of schema defaults.

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 an optional-parameter screener with no output schema, the description provides enough to invoke it sensibly: what it screens, key market options, and what data is returned. The missing ordering/ranking criteria and the unexplained min_market_cap parameter are gaps, but the tool remains usable with defaults.

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 description coverage is only 33%, so the description must compensate. It adds the 'RSI range' concept and market context, but min_market_cap is completely unexplained and limit is only inferable. The description partially fills the gap but does not fully cover all six parameters.

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 ('Screen') with a clear resource ('stocks, crypto or forex symbols') and names the key filtering dimensions. It also distinguishes itself from the sibling tools by focusing on screening/discovery rather than historical data, quotes, or indicators.

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?

Usage context is implied: use this tool to find symbols matching market, volume, and RSI criteria. However, it never explicitly says when NOT to use it or directs the agent to alternatives like tv_get_quote or tv_get_indicators, so routing is left to inference.

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