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

There are no annotations, so the description carries the burden. It usefully discloses the exact set of valid periods and the symbol-count bound, which are behavioral constraints, but it says nothing about auth, rate limits, or handling of invalid periods. The presence of an output schema lowers the need to explain return values.

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?

A single sentence with no filler, and the scope constraint and metrics are front-loaded rather than buried.

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?

An output schema exists, so return values need no explanation, and both input parameters are covered with meaningful constraints. What remains unstated is error behavior for out-of-range periods or symbol counts, a minor gap for a read-only comparison tool.

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 0%, so the description has to compensate, and it does: it enumerates the accepted period values (1mo through 5y) that the schema leaves as a free string, and it states the 2-10 cardinality constraint on the symbols array. It does not clarify the default of 1y or symbol format (ticker casing/styles).

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?

Specific verb (rank) plus resource (2-10 symbols) plus the metrics returned (return, volatility, drawdown), so the agent knows exactly what the tool produces. It doesn't name the siblings get_quote or get_signals, so the differentiation from those is only implicit, which keeps it below a 5.

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 '2-10 symbols' bound and the period framing imply the multi-symbol comparison use case, which distinguishes it from a single-quote tool. However, there is no explicit when-to-use/when-not-to-use guidance and no mention of alternatives.

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 exist, so the description carries the full burden, yet it says nothing about whether prices are delayed or real-time, auth requirements, rate limits, or what happens for an invalid/unknown symbol. Only the returned field names are disclosed, which is the bare minimum for a market-data read.

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?

One sentence that front-loads the payload contents and ends with the scoping constraint and examples. Nothing is wasted, though leading with the verb would make the action even more immediate.

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?

An output schema exists, so return structure needn't be explained, and the single parameter is illustrated. However, for a zero-annotation tool the description leaves out data freshness and failure behavior, which materially affect how an agent should present and retry the result.

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?

The schema coverage is 0%, but the description compensates partially with concrete examples (RELIANCE, TCS, NIFTY), showing that index names are valid and implying NSE ticker format. It still omits casing rules, exchange prefixes, or series suffixes, so an agent could still pass malformed symbols.

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?

States the exact fields returned (latest close, daily change, 52-week range) scoped to one NSE symbol, which is far more specific than a restatement of the name. It implies single-symbol scope, distinguishing it from compare_symbols, but never names the siblings explicitly.

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 is only implied: 'symbol' plus the field list tells an agent this is a single-symbol snapshot tool. There is no explicit when-to-use, when-not-to-use, or alternative such as compare_symbols for multi-symbol work or get_signals for other data.

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 behavioral burden, and it discloses almost nothing: no statement that it is a read-only computation, no data-window or history requirement (relevant for 12-1 momentum), no freshness/latency notes, and no hint about what happens for an invalid or untradeable symbol. Naming the metrics and calling the regime 'rule-based' is the only behavioral signal.

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?

One tight sentence with no filler, and the metric inventory is front-loaded so an agent can judge relevance immediately. Nothing to trim.

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?

An output schema exists, so return values need not be explained. However, for a computation with a historical window (12-1 momentum) and an untyped symbol identifier, the description should at least cover symbol format and any lookback/data assumptions; those gaps keep it merely adequate.

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 0% for the single required 'symbol' parameter, and the description only echoes it as 'for a symbol'. It adds no format guidance (ticker vs. exchange-suffixed, case sensitivity, supported universes), so the one input the agent must supply remains underspecified.

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 enumerates exactly what is computed for a symbol (RSI, volatility, drawdown, 12-1 momentum, rule-based trend regime), which is far more concrete than 'Get Signals'. It never names the siblings get_quote or compare_symbols, so the boundary between a single-symbol signal panel and a price quote or multi-symbol comparison is left to inference.

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?

There is no when-to-use guidance at all: nothing says to call this instead of get_quote for a raw price, or instead of compare_symbols when evaluating multiple names. The agent must infer the selection rule from the metric list alone.

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