Central Command

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

No annotations are provided, so the description must cover behavioral traits. It mentions paper vs. live execution but does not disclose other important traits like destructive effects, authentication needs, or error behavior. Given the tool has 8 parameters and no annotations, more behavioral detail is expected.

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 with two sentences. It front-loads the tool's core identity and efficiently lists example actions and a key behavioral note. No unnecessary 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 8 parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, parameter relationships, or error handling, leaving significant gaps for an agent to use 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?

Schema description coverage is only 25% (only 'action' has a description). The description adds some meaning by listing action examples and indicating paper default/live confirmation behavior, but fails to explain the majority of parameters like 'id', 'body', 'goal', 'title', 'task_type', and 'force_paper'.

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 identifies itself as a 'Central Command agent console' and lists specific actions like 'create_strategy', 'deploy', 'execute', etc., making the purpose clear. It distinguishes from siblings which are mostly data/market tools.

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?

Provides examples of actions and states 'Paper by default; live orders need confirm_live' which gives usage context. However, it lacks explicit when-to-use or when-not-to-use guidance compared to 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?

With no annotations provided, the description carries full burden. It discloses the cost ($0.008 USDC) and included data types, but does not mention read-only behavior, rate limits, data freshness, error handling, or potential side effects. This is adequate but not thorough for a tool aggregating multiple data sources.

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 at two sentences, listing key components and cost without extraneous words. However, the first sentence is somewhat buzzword-heavy ('Comprehensive Market Context: All-in-one market intelligence'), which slightly reduces clarity.

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 returning multiple data types (candles, indicators, OI, news) and lacking an output schema, the description is incomplete. It does not explain the output format, structure, or how the data is combined. The input schema also allows additionalProperties without guidance. An agent would need more details to reliably use the 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?

The input schema descriptions are minimal ('symbol' and 'default: 1h'). The tool description does not add any additional meaning about parameters—no explanation of what symbol formats are accepted, what timeframes are available, or how the 'additionalProperties' field might be used. The description adds marginal value beyond the schema.

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 it provides 'OHLCV candles + computed indicators + Coinglass OI + news via Tavily' and frames it as 'all-in-one market intelligence'. This distinctively sets it apart from sibling tools like cc_coinglass_data, cc_market_news, or cc_funding_rates, which focus on individual data types.

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 use when comprehensive market data is needed ('Everything an agent needs in one call'), but does not explicitly state when to use this tool versus more specific siblings, nor does it mention when not to use it (e.g., when only one data type is needed).

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 provided; description lacks disclosure of side effects, authorization needs, rate limits, or output format. 'Generates inverse signals' is vague about behavioral impact.

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 concise sentences, front-loaded with name and algorithm. No redundant 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?

Missing output schema; description does not explain what the tool returns (e.g., signal type, data format). Incomplete for agent to leverage output 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?

Input schema has zero parameters and 100% coverage; description adds meaning by indicating no input needed. Baseline 4 for no params.

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?

Description clearly states tool identifies statistically proven bad traders and generates inverse signals. Distinct from siblings like cc_counter_trade_monitor, cc_cfe_risk_monitor.

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?

No guidance on when to use vs alternatives, no context or prerequisites provided. Only describes functionality and price.

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 should disclose behavioral traits. It mentions 'real-time monitoring' and 'detects new entries' but does not clarify if the tool is read-only, requires authentication, or has rate limits. The mention of a price ($0.008 USDC) is ambiguous and could indicate cost, but is not clearly a behavioral trait.

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 very short (two sentences) and front-loaded with the purpose. However, the inclusion of 'Price: $0.008 USDC' adds non-essential information that may not help tool selection, slightly reducing efficiency.

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 no output schema and no annotations, the description is too brief. It fails to explain what data the tool returns (e.g., format, fields, frequency of updates), leaving the agent uncertain about what to expect after 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?

The tool has zero parameters and 100% schema coverage, so no additional parameter information is needed. Per guidelines, baseline score is 4.

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 it monitors counter-trade targets live positions on BloFin and detects new entries for fading, which is a specific verb-resource combination. It distinguishes from siblings like cc_counter_trade_rankings and cc_cohort_fade_scanner by focusing on live positions and immediate fading.

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 monitoring live counter-trade positions and fading new entries, but does not explicitly state when not to use it or compare to alternatives. Context from sibling names suggests differentiation, but 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.

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

No annotations provided, so description carries full burden. Discloses 30-minute cache and cost of $0.0005 USDC, but does not explain read-only nature, rate limits, or other behavioral aspects.

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?

Four short sentences, each providing essential information: what it is, its features, cache, and cost. 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?

While the description gives a high-level overview (index value, historical, trend, cache, price), it lacks specification of the return format or fields. Without an output schema, the agent has to guess the exact response structure.

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?

No parameters exist; schema is empty with 100% coverage. Baseline is 4. Description adds meaning about the index (range, historical, trend) beyond schema.

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?

Clearly states it is the Crypto Fear & Greed Index with a 0-100 composite score, historical values, and trend direction. Distinct from all sibling tools, which cover other crypto data or strategies.

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?

No explicit when-to-use vs alternatives. The description implies it for fetching the fear/greed index, but does not mention when to prefer it over other tools like cc_market_news or cc_open_interest.

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 it generates executable code and simulates TP/SL/trailing stops, but fails to mention error handling, data sources, what happens if strategy is invalid, or output behavior. The price is included but not behavioral traits.

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 a single concise sentence with a price note, front-loading the core purpose. It has no waste, though the price note could be considered extraneous for tool selection. Still, it's well-structured and 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?

The description lacks explanation of return values or output format (no output schema). For a tool that simulates backtesting, it should mention what results are returned (e.g., metrics, equity curve). Missing details on data sources, error states, and limits leave the context incomplete.

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% with descriptions for all 4 parameters. The description restates that 'strategy' is a natural language description but adds no new meaning beyond the schema. Baseline 3 is appropriate since the schema already handles parameter documentation.

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 takes a natural language strategy, generates code, and runs backtest with TP/SL/trailing stop simulation. The verb 'backtest' and resource 'strategy' are explicit, and it distinguishes from sibling tools like cc_strategy_data_parser which parses strategy data rather than backtesting.

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 use for backtesting natural language strategies, mentioning price and code generation, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use agent_strategy or cc_strategy_data_parser). No exclusions or prerequisites are stated.

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