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

The description discloses key behavioral traits beyond annotations: login masking, omission of broker/server/account holder names, and synthetic data indicators on replay. This adds significant value over the readOnlyHint and openWorldHint annotations.

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 three sentences long, front-loaded with the main purpose, and every sentence adds essential information. There is no redundancy or wasted language.

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?

Given the tool has no parameters and an output schema exists, the description adequately covers the return values and adds critical context about data masking and synthetic mode. It is complete for an agent to understand and invoke the tool correctly.

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 no parameters and schema coverage is 100%, so the baseline is 3. The description does not add meaning to any parameters because there are none to explain; it appropriately focuses on the tool's output and behavior.

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 clearly states the verb 'Return' and the specific resource 'connected account's balance, equity, margin and leverage'. This distinguishes it from sibling tools like list_symbols, get_quote, and get_bars, which operate on different data.

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 about when the tool returns synthetic data on the replay source and warns against restating it as real. It does not explicitly contrast with siblings, but the context is sufficient for an agent to understand when to use this tool.

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?

The description discloses critical behavioral traits beyond annotations: bars are in UTC labeling the open, the newest bar is always closed (never returns forming bar), the server caps count, and on replay source prices are generated (not recorded). The readOnlyHint annotation is consistent with the read-only nature described, and no contradiction exists.

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 concise (5 sentences) and front-loaded: first sentence states the core purpose and ordering. Every sentence adds distinct value (timezone, counting strategy, bar state, error handling, data source). No wasted words.

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?

Given the tool has 3 parameters, an output schema (present), and annotations (readOnlyHint, openWorldHint), the description covers all necessary context: purpose, parameters, error handling, alternatives, and data source behavior. The output schema likely describes return format, so no need to explain return values. Complete for a moderately complex 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 67% (only 2 of 3 parameters have descriptions). The description adds value: clarifies that 'count' is capped by server ('ask for a coarser timeframe rather than more bars'), that 'symbol' must match list_symbols spelling, and that 'timeframe' is the interval length. The description compensates for the missing schema description on 'timeframe' by listing enum values contextually (M1, M5, etc.) and implying the left-edge labeling. However, it doesn't explain the 'timeframe' enum beyond listing intervals, so a 4 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 clearly states the tool returns 'the most recent OHLCV bars for a symbol, oldest first'. It identifies the specific verb (return), resource (OHLCV bars), and ordering (oldest first), distinguishing it from siblings like get_quote (current price) and get_bars_range (range-based).

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 explicit guidance: when to use alternatives ('call get_quote for the current price'), when to call list_symbols first ('call list_symbols first if unsure'), how to handle timeframes ('ask for a coarser timeframe rather than more bars'), and error handling ('An unknown or unavailable symbol returns a tool error naming the symbol'). It also notes the 'count' cap and server limit.

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?

The description goes well beyond the readOnlyHint annotation, explaining the inclusive/exclusive bounds, UTC offset requirement, tiling behavior, error on exceeding limits, the nuance with forming bars, and the synthetic nature of replay data. This gives the agent a full behavioral model.

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 front-loaded with the core purpose, and every subsequent sentence adds essential behavioral or usage detail. It is concise given the complexity, with no redundant wording.

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 description covers not only the basic operation but also edge cases like limit-caused errors, the difference from get_bars, data source caveat, and formatting requirements. Given the output schema exists, return values need no explanation, and the description is fully sufficient for an agent to invoke the tool correctly.

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 already covers 75% of parameters with descriptions, but the description adds critical semantics for start/end (inclusive/exclusive, UTC offset, example format) and clarifies the meaning of range-related behavior beyond the schema. Timeframe is only an enum, but the values are self-explanatory.

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 clearly states the tool returns OHLCV bars within a half-open date range, ordered oldest first. The title 'Get bars in a date range' plus the explicit interval notation [start, end) distinguishes it from its sibling get_bars.

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 references get_bars multiple times, noting the same limit applies and highlighting a key difference regarding forming bars. This provides clear comparative context, though it does not include a direct 'use this when' statement or explicit when-not-to-use guidance.

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?

The description discloses crucial behavior beyond the annotations: 'On the replay source it is the last stored bar's open time rather than the current clock, so the answer is reproducible and is NOT a live market price.' It also details error handling for unknown symbols. This adds significant context for an agent deciding whether to trust the result as live.

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 plus a crucial behavioral note. Every sentence adds value, and the key action ('Return...') is front-loaded. No redundant or vague language. It is concise without omitting necessary information.

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?

Given the tool's simplicity (one required parameter, no nested types) and the existence of an output schema (not shown but indicated in context signals), the description adequately covers the return value, time source, error behavior, and a pointer to list_symbols. It is complete for an agent to use correctly.

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 input schema has 100% coverage for its single parameter 'symbol', with description 'Instrument name exactly as list_symbols spells it.' The tool description does not add new semantic meaning; it only repeats the schema's point about exact spelling. Baseline 3 is appropriate when schema already fully documents the parameter.

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 clearly states 'Return the latest bid, ask and spread in points for one instrument.' The verb 'return' and resource 'quote for one instrument' are specific. It implicitly distinguishes from sibling tools like get_bars (historical bars) and list_symbols (listing symbols).

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 explicit guidance: 'An unknown or unavailable symbol returns a tool error naming the symbol; call list_symbols if unsure.' This tells the agent when to use list_symbols instead. It does not explicitly state when not to use this tool (e.g., for historical prices use get_bars), but the sibling context and the mention of 'latest' imply the appropriate use case.

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?

Annotations already mark readOnlyHint=true. The description reinforces this with 'this server can place, modify and cancel nothing' and adds critical context about the replay source (list always empty, synthetic flag). This goes beyond what annotations provide, though it does not cover all possible behavioral traits (e.g., rate limits, auth needs).

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 three sentences, each earning its place: purpose, read-only assertion, and replay-specific behavior. No unnecessary words, front-loaded with the core action.

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 has no parameters and an output schema exists. The description covers return fields and a key behavioral detail about replay sources, making it fully adequate for the low complexity of this 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?

With zero parameters and 100% schema coverage, the description need not add parameter-level meaning. It correctly describes the output fields but not parameter semantics; baseline 3 is appropriate as the schema carries the full load.

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 clearly states the verb 'Return' and the resource 'every pending order', and specifies the data included (type, volumes, trigger price). It differentiates from sibling tools which deal with symbols, quotes, bars, account, and positions, leaving no ambiguity about what this tool does.

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 retrieving pending orders and includes the read-only note, but does not explicitly say when to use this tool over alternatives like list_positions. It lacks mentions of conditions under which the tool should or should not be used, nor does it reference sibling tools for comparison.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds value beyond annotations by stating the server can 'open, modify and close nothing', and explains the synthetic flag behavior on replay sources. This provides meaningful behavioral context without contradiction.

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, each providing essential information. No filler or redundancy. Perfectly sized for a tool with no parameters and clear purpose.

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?

Given no parameters and an output schema present, the description is largely complete. It explains the tool's purpose, return fields, and special behavior (read-only, synthetic flag on replay). One minor gap: it doesn't mention whether the list is always empty in certain modes beyond replay.

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 input schema has no parameters, so the description has no responsibility to document parameters. With 0 parameters and 100% schema coverage, the description adds value by explaining return fields (entry price, current price, floating profit), which aids correct invocation and interpretation.

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 ('Return') and resource ('open position'), and lists the fields returned (entry price, current price, floating profit). It clearly distinguishes this tool from siblings like `list_symbols` and `list_orders`.

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 clarifies that the tool is read-only and explains behavior on replay sources (always empty, payload has synthetic=true). However, it doesn't explicitly state when to use this tool over alternatives like `get_account` or `list_orders`, though the purpose is clear enough.

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?

Annotations already declare readOnlyHint=true (safe read) and openWorldHint=false (closed set). The description adds value by noting that missing symbols cause errors in other tools, and that replay sources return synthetic=true. This complements the annotations without contradicting them.

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 three sentences with zero wasted words. Each sentence serves a distinct purpose: stating the return value, explaining when to call and consequences, and describing the optional filter. Information is front-loaded with the core purpose first.

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?

Given the tool's simplicity (1 optional parameter, read-only, closed set), output schema exists, and annotations are clear, the description is fully complete. It covers purpose, usage guidance, parameter behavior, and edge cases (replay vs. live), leaving no gaps for an agent.

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 100% and already documents the group parameter syntax thoroughly. The description reinforces this by referencing the syntax explanation in the argument description, adding the context of how the filter interacts with the overall tool purpose, which is helpful for an agent.

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 clearly states the tool returns 'every instrument this server exposes, with its digits and point size'. It uses a specific verb ('Return') and resource ('every instrument'), and distinguishes itself from siblings like get_quote and symbol_info by positioning itself as the authoritative source of symbol names.

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?

Explicitly advises 'Call this before anything else', warns that missing names cause errors elsewhere, explains the optional group filter's syntax, and clarifies behavior differences on replay sources. No alternative tools are needed for this purpose, and it sets clear prerequisites for using other 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?

Annotations already declare readOnlyHint=true, so the tool is safe to call without side effects. The description adds behavioral context: it lists the exact return fields (digits, spread, tick value, etc.), notes that unknown symbols cause a tool error, and mentions that on replay sources synthetic=true is added. This goes beyond annotations without contradicting them.

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 concise (three sentences) and front-loaded with the purpose. Each sentence adds relevant detail (return fields, naming, edge cases). Slightly verbose in listing fields could be trimmed, but it remains efficient.

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?

Given that there is no output schema but an output schema exists (context says 'Has output schema: true'), the description thoroughly lists return fields and covers the key edge case of unknown symbols. With annotations providing read-only guarantee, and one simple parameter, the description is complete enough for an agent to use correctly.

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?

Even though schema coverage is 100% and the single parameter 'symbol' has a description, the description adds value by indicating that symbol names must match list_symbols exactly and that unknown symbols trigger an error. This aids correct invocation.

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 clearly states 'Return the contract specification for one instrument,' which identifies the action (return) and the resource (contract specification for one instrument). It distinguishes itself from siblings like 'list_symbols' (which lists symbols, not specifications) and 'get_quote' (which gets quotes) by focusing on static contract details.

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 when needing instrument specifications (digits, spread, tick value, etc.) but does not explicitly state when to use this tool versus alternatives. It mentions that an unknown symbol returns a tool error, which is helpful context. No explicit exclusions or alternatives are given, but the context is clear.

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