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

No annotations are provided, so the description carries the full disclosure burden. It discloses key execution assumptions: fills at next bar's open, costs charged both sides, a bar touching both stop and target counts as a stop, and assumptions returned with results. This goes beyond a generic 'runs a backtest.' It does not mention potential rate limits or data source details, but the essential behavioral traits are covered.

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 sentences, each carrying distinct value: purpose/outputs, execution assumptions, and result contents. The most important information is front-loaded and there is no filler. This is an appropriate size for the tool's complexity.

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 tool with 9 parameters and a nested strategy object, the description plus schema cover the essentials: inputs are defined by the schema, and behavioral assumptions are clearly stated. Since there is no output schema, the mention of metrics, trade list, equity curve, and assumptions is valuable. Minor gaps remain around strategy variants, default values, and error behavior, but these are either in the schema or not critical for invocation.

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 56%, leaving slippageBps, commissionBps, stopAtrMultiple, and targetRMultiple undocumented. The description partially compensates by explaining cost behavior ('costs are charged both sides') and stop/target ambiguity, which gives those parameters context. However, it does not map each parameter to its effect or indicate which are optional, so the gap is not fully closed.

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: 'Runs a strategy over the history' and enumerates concrete outputs (metrics, trade list, equity curve). This clearly distinguishes it from siblings like list_symbols or get_ohlc, though it does not explicitly name an alternative. The purpose is unambiguous.

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 backtesting a strategy but provides no explicit when-to-use guidance or exclusions. It does not mention alternative tools or conditions where backtest would be inappropriate. With sibling tools serving clearly different purposes, the omission is minor but still leaves selection to inference.

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 transparency burden. It discloses a non-obvious behavioral trait: long ranges are truncated to the most recent rows, and the response states total available. It does not cover error cases or row ordering, but the key edge-case behavior is surfaced.

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 sentences with no filler. The core purpose is front-loaded, followed by a concise behavioral caveat. Every word earns its place.

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 retrieval tool with no annotations or output schema, the description covers the main purpose, truncation behavior, and response-related note. It omits minor details like ordering and timestamp format, but standard OHLC data and the schema's parameter descriptions make this sufficient.

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 the baseline is 3. The description adds contextual behavior about truncation that relates to the bars parameter but does not detail each parameter beyond the schema. The schema already documents symbol, bars, and timeframe adequately.

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 ('Returns recent candles for a symbol') and is clearly distinguished from siblings like list_symbols, backtest, indicator, and position_size by its unique data-retrieval role. An agent can determine what this tool does without needing to open the schema.

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 purpose statement implies when to use the tool (whenever recent OHLC candles are needed), but it provides no explicit exclusions or recommendations among alternatives. There is no mention of when not to use this tool or which sibling might be more appropriate.

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 burden of behavioral disclosure. It reveals a non-obvious behavioral trait: values are aligned with candles and null before enough history, preventing silent series shifts. However, it does not mention other behaviors like read-only nature, output structure, or error handling, so it is not fully comprehensive.

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 entire description is a single sentence that front-loads the primary action and then adds a critical behavioral detail. There is no filler, repetition of schema information, or unnecessary context.

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 moderately complex with six parameters and no output schema, yet the description does not specify the return shape (e.g., one array per series for Bollinger) or default periods. While the alignment/null behavior adds useful return context, the lack of explicit output structure and usage guidance leaves noteworthy 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 description coverage is 83%, so the schema documents most parameter semantics (e.g., range for bars, period, enum for timeframe). The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate.

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 names a specific verb ('Computes') and a resource ('technical indicator') while explicitly enumerating the exact indicators supported: SMA, EMA, RSI, ATR, and Bollinger bands. This clearly distinguishes the tool from siblings like list_symbols or backtest, which perform unrelated operations.

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 states what the tool computes but provides no guidance on when to use it versus alternatives such as get_ohlc or backtest. There are no explicit conditions, exclusions, or references to sibling tools, so the agent must infer usage context entirely.

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 provided, the description carries the behavioral burden. 'Lists the instruments' clearly indicates a read-only operation with no side effects, and adding the data-provenance context is useful. It does not disclose output format or potential limitations, but these are less critical for a simple listing tool.

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 one short sentence that immediately states the core function and then adds one useful contextual detail. Every word earns its place; there is no filler.

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 parameterless listing tool with no output schema, the description is reasonably complete: it tells the agent what will be listed and mentions the provenance. It could mention the exact shape of the returned data, but this is a minor gap for such a simple 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?

The tool has zero parameters awaited with 100% schema coverage, so there is nothing for the description to add. Baseline 4 is appropriate given no parameter semantics are needed.

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 states a specific verb ('Lists'), a resource ('instruments this server can analyse'), and an additional scope ('where their data comes from'). This clearly distinguishes list_symbols from its siblings, which perform analysis, price retrieval, indicators, and position sizing.

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 that this tool is used to discover available symbols before calling analysis tools, but it does not explicitly state when to use this tool versus alternatives. It provides no exclusions or conditions, though the listing purpose is inherently distinct from the sibling tools.

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 provided, so the description carries the full burden. It discloses that the tool refuses inputs that risk more than the account or imply a zero stop, which is useful behavioral context. However, it does not mention whether the tool is read-only, what the output format is, or how it handles errors beyond refusal. For a calculation tool with no annotations, this is a moderate gap.

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 sentences with no fluff. The primary purpose is stated first, followed by a key behavioral constraint. Every word earns its place, and the structure is optimal for quick comprehension.

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 tool with 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain what the tool returns (e.g., position size in shares or lots), nor does it mention contractSize or the role of entry price. The refusal behavior is disclosed, but other essential usage details are missing. The description is not sufficient for an agent to fully understand the tool's behavior and output.

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 20% (only contractSize has a description). The tool description maps the main inputs (equity, risk tolerance, stop distance) to the calculation purpose, providing some semantic context. However, it omits entry and contractSize, and does not explain the relationship between parameters or the output units. It adds some value but does not fully compensate for the low schema 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 states a specific verb and resource: it turns account equity, risk tolerance, and a stop distance into a position size. This clearly distinguishes it from sibling tools like list_symbols, backtest, get_ohlc, and indicator, which are about data retrieval or backtesting. The purpose is unambiguous and not a tautology.

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 when to use the tool (when you need to compute a position size from risk parameters), but it does not explicitly mention alternatives or when not to use it. No exclusions are stated, and the context is clear enough that an agent could infer usage, but the guidance is not explicit.

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