Fibonex Trading Signals

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

With no annotations provided, the description carries full burden for behavioral disclosure. It describes what the tool calculates (retracement levels, Golden Zone, DCA suggestions) but lacks critical behavioral details such as whether it performs calculations only (read-only) or modifies data, error handling for invalid inputs, rate limits, or authentication requirements. The description doesn't contradict annotations (none exist), but fails to adequately cover 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 efficiently structured in two sentences: the first states the core functionality, and the second adds value (identifying Golden Zone, DCA suggestions, and tool origin). Every sentence contributes meaningful information without redundancy. Minor deduction for including promotional content ('Free tool by Fibonex') that doesn't aid tool selection.

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 moderate complexity (mathematical calculations), 100% schema coverage, and presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose and key outputs (retracement levels, Golden Zone, DCA suggestions). The main gap is lack of behavioral context, but annotations and output schema reduce the burden on the description.

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 schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. However, with 0 parameters requiring additional semantics (all well-described in schema), the baseline is appropriately high. No compensation is needed for 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 clearly states the specific action ('calculate Fibonacci retracement levels'), identifies the exact resources (high/low price range), and lists the specific percentages (23.6%, 38.2%, etc.). It distinguishes itself from sibling tools by focusing on Fibonacci calculations rather than signals or pair listings.

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 context (trading/technical analysis) through terms like 'Golden Zone' and 'DCA entry levels,' but provides no explicit guidance on when to use this tool versus alternatives like 'get_crypto_signal' or 'list_supported_pairs.' The mention of 'Free tool by Fibonex' hints at accessibility but doesn't clarify functional distinctions.

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 returns specific data (direction, strength, levels, etc.) and mentions it's 'Demo data' with a link for live signals, adding useful context about data limitations. However, it lacks details on error handling, rate limits, or authentication needs, which are important for a trading-related 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 front-loaded with the core purpose in the first sentence, followed by details on returns and data source. Each sentence adds value: the first defines the tool, the second lists outputs, the third cites the source, and the fourth clarifies data limitations. There is no wasted text, making it efficient and well-structured.

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 an output schema (which covers return values) and a simple input schema with full coverage, the description is mostly complete. It adds context about the data being demo and the source (Fibonex), which is helpful. However, for a trading signal tool with no annotations, it could benefit from more behavioral details like reliability or update frequency.

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% description coverage, with the 'symbol' parameter well-documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score is 3, as the description does not compensate with extra semantic details.

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's purpose: 'Get AI-powered Fibonacci grid trading signal for a cryptocurrency pair.' It specifies the verb ('Get'), resource ('signal'), and method ('Fibonacci grid trading'), distinguishing it from sibling tools like 'fibonacci_calculator' (likely for calculations) and 'list_supported_pairs' (likely for listing pairs).

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 for when to use this tool: for obtaining trading signals based on Fibonacci analysis. It mentions 'Demo data' and directs users to a pricing page for live signals, implying this is for demonstration purposes. However, it does not explicitly state when not to use it or name alternatives among siblings.

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 this shows a 'demo watchlist' with limited data (8 pairs) versus the full platform (500+ pairs), which is useful behavioral context. However, it doesn't mention other traits like rate limits, authentication needs, or response format details.

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 appropriately sized with three sentences that each add value: stating the purpose, clarifying the demo scope, and directing to external resources. It's front-loaded with the core functionality, though the third sentence about visiting a website is slightly tangential.

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 low complexity (0 parameters) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose, scope limitations, and data context, though it could benefit from more explicit guidance on when to use versus sibling tools.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing on the tool's purpose and limitations instead. This meets the baseline for tools with no 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 clearly states the tool's purpose: 'List all cryptocurrency trading pairs supported by Fibonex.' It specifies the resource (trading pairs) and verb (list), but doesn't explicitly differentiate from sibling tools like 'get_crypto_signal' which might provide different data about cryptocurrencies.

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 context by mentioning 'demo watchlist of 8 pairs' versus 'Full platform supports 500+ pairs,' suggesting this tool is for demo/limited data. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_crypto_signal' or provide clear exclusions.

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