web3-signals

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

The description discloses that the tool performs a comparison (read-only) and returns a ranked result, which aligns with the readOnlyHint annotation. It also adds behavioral context by specifying the input format and the fact that it ranks by signal strength. No contradictions with the annotation exist.

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 compact and front-loaded with the purpose. Every sentence adds value: the rhetorical question sets the decision context, the second sentence states the core action, the third explains input, and the fourth clarifies return content and use case. No redundant or filler text.

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, the description provides all necessary context: input format and constraints, output summary (scores, direction, verdict), and a use case. The existence of an output schema and readOnly annotation further reduces the need to elaborate on return values or safety, making the description complete for agent 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 schema only defines an 'assets' string with no description, so the description fully compensates by specifying that it takes comma-separated tickers and requires 2-5 entries, with an example ('BTC,ETH,SOL'). This adds essential meaning beyond the schema's bare parameter name.

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 'Compare' with a clear resource: '2-5 cryptocurrencies ranked by signal strength.' It explicitly states the output ('ranked comparison with scores, direction, and verdict') and differentiates from sibling tools like get_asset_signal by focusing on multi-asset comparison rather than a single asset.

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 usage context ('Use for portfolio allocation decisions') and explicitly specifies the input range ('2-5 cryptocurrencies'), which helps the agent know when to apply it. However, it does not explicitly mention when not to use it or point to alternative tools for single-asset comparisons, so it stops short of full exclusion 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 annotations declare readOnlyHint=true, and the description adds valuable behavioral context such as the 15-minute update frequency and the extra response fields (portfolio summary, market regime, risk level). No contradiction with 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 that efficiently convey the purpose, output structure, update frequency, and alternative paid API. Every sentence earns its place, and the action is front-loaded. There is 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?

Given the presence of an output schema, the description need not enumerate return values. It covers the asset scope, scoring approach, direction, summary fields, and data freshness, which is complete for a no-parameter read-only tool. The mention of the paid API also sets expectations for limitations.

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, the baseline is 4. The description confirms no configuration is needed, and since the schema is empty, the description fully covers parameter semantics. It doesn't add parameter-specific details because none exist.

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 retrieves buy/sell signals for all 20 major cryptocurrencies, specifies the composite score and direction, and distinguishes it from single-asset tools like get_asset_signal. The verb 'get' plus resource 'signals' and explicit scope ('all 20 major cryptocurrencies') make the purpose highly specific.

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 this is the comprehensive overview tool for all assets and explicitly directs users to the paid REST API for full dimension breakdown and AI insights, providing an alternative. However, it could more explicitly state when to choose this over sibling tools like get_asset_signal.

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 annotation readOnlyHint=true already declares this as a safe read operation. The description adds value by detailing the specific metrics returned, but it does not disclose other behavioral traits such as how the 'days' parameter affects the data, aggregation details, or any access requirements. This is adequate but not rich.

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 and front-loads the purpose. The opening rhetorical question is a minor stylistic flourish but does not detract significantly. All sentences serve a functional role in communicating scope and usefulness.

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 output schema covers return values, and the description explains what the statistics include. However, the complete omission of the 'days' parameter and the lack of any mention of access scopes or usage limitations make the description incomplete for a tool with only one parameter. It is barely 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?

The input schema has one parameter 'days' with no description and the schema description coverage is 0%. The tool description does not mention this parameter at all, leaving its meaning and effect completely undocumented. This is a significant gap that the description fails to compensate for.

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 with a specific verb ('See') and resource ('API usage statistics'), and it lists the types of statistics included (total requests, unique clients, response times, breakdowns by endpoint/client type). This distinguishes it from sibling tools that focus on market data, signals, or asset performance.

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 a clear context for use: 'Useful for understanding adoption.' This implies when to use the tool but does not explicitly mention alternatives or when not to use it, so it falls short of explicit exclusions.

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 readOnlyHint=true, the annotation already indicates a safe read operation. The description adds valuable behavioral context beyond that by disclosing the specific metrics returned (30-day rolling accuracy, total signals evaluated, and comparison to overall accuracy). This gives the agent a clear picture of the tool's output without overwhelming detail.

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 concise sentences, front-loaded with a practical example question, and every word adds value. There is no redundancy or filler, making it easy for an agent to parse quickly.

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 simple with one parameter, an output schema exists, and readOnlyHint is present. The description covers the core purpose, usage context, and return contents sufficiently. It also implicitly differentiates from siblings, making it complete for its complexity level.

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 0%, so the description must compensate for the undocumented 'asset' parameter. It provides a concrete example ('BTC') and states 'any cryptocurrency', which implies an identifier like a ticker symbol. However, it does not specify the exact expected format (e.g., symbol vs. full name), leaving some ambiguity for a parameter that has no schema description.

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 a specific action ('Get per-asset accuracy metrics') and a specific resource ('for any cryptocurrency'). It distinguishes itself from sibling tools like get_performance and get_asset_signal by explicitly mentioning 30-day rolling accuracy and comparison to overall accuracy, making the tool's unique purpose evident.

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 opening question 'How accurate are the signals for BTC specifically?' provides clear context for when to use this tool, and the phrase 'for any cryptocurrency' indicates broad applicability. However, it does not explicitly exclude alternatives or name sibling tools, so it stops short of full 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?

With readOnlyHint=true in annotations, the description aligns correctly. It discloses the return fields (composite score, direction, signal label, momentum) and the list of supported assets. It does not contradict annotations and adds useful context about limitations and the paid API alternative.

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: two sentences that start with a hook question and clearly explain output and supported assets. The list of assets is long but necessary for clarity. No wasted words, though the list could be shortened with a reference to docs, but it's acceptable.

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 a single parameter and an output schema (mentioned in context), the description adequately covers the purpose, output structure, and asset list. However, it creates slight ambiguity by saying 'any cryptocurrency' before listing specific ones, and it doesn't explain how to interpret the 0-100 score beyond the label, but the output schema likely covers that.

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 provides only a parameter named 'asset' with no description (0% schema description coverage). The description compensates by specifying that 'asset' is a cryptocurrency and enumerates the supported assets (BTC, ETH, etc.), adding meaning that the schema alone lacks.

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 function: getting a 0-100 buy/sell score for a cryptocurrency, with specific elements returned (composite score, direction, signal label, momentum). It distinguishes itself from sibling tools by focusing on a single asset's signal, not all signals or comparison. The only minor flaw is the phrase 'any cryptocurrency' followed by a restricted supported list.

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 you need a quick bullish/bearish score for a supported asset and points to the paid REST API for deeper analysis. However, it does not explicitly contrast with sibling tools like get_all_signals or compare_assets, nor does it provide clear 'when not to use' guidance other than the paid API mention.

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 the description adds valuable context: data freshness (updated every 15 minutes), data sources (CoinGecko and Binance), and supported asset list. This goes beyond mere annotation and sets clear expectations for behavior with no contradictions.

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 well-structured, starts with the main purpose, then details return fields, freshness, and supported assets. Every sentence is informative, and the example clarifies usage. The asset list is long but necessary for parameter understanding, so it 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?

With an output schema present, the description doesn't need to detail return values. It covers purpose, parameter range, freshness, and data sources, making it complete for a read-only price lookup tool. No gaps are evident for an agent to invoke it 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 0%, so the description compensates by listing all 20 supported asset symbols and providing an example call. It clearly implies the parameter is a ticker symbol, though it doesn't specify case sensitivity or invalid input handling, but it adds meaning beyond the bare 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 the tool returns the current price, 24-hour change, volume, and market cap for major cryptos. The verb 'get' with resource 'crypto price' is specific, and the listed return fields and supported assets distinguish it from sibling tools like compare_assets or get_market_briefing.

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 obtaining current price data, but it doesn't explicitly state when to use this tool over alternatives like get_asset_performance or compare_assets. No exclusions are provided, but the context is sufficient for basic selection, though 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?

Annotations already declare readOnlyHint=true, so the description adds value by enumerating what the health check covers (specific pipelines) and what it returns (last run times, durations, errors). This goes beyond the simple read-only flag, though it doesn't delve into edge cases or detailed behavioral nuances.

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 long and front-loaded with a purpose-indicating question. Each sentence contributes meaningful information: what is checked and what is returned, with no redundancy or 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 simple health-check tool with no parameters and read-only annotations, the description is sufficiently complete. It covers the key components checked and the nature of the return value, and the existence of an output schema likely provides further structural detail.

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, so the baseline is 4 per the rubric. The description doesn't need to explain parameter semantics; it instead clarifies the scope and output, which is appropriate for a no-parameter tool.

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: checking the real-time status of all 5 AI data pipelines and the signal fusion engine. The verb 'check' and specific resource names make it distinct from sibling tools that focus on data content or performance.

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 implicitly signals when to use this tool—when you need to verify if AgentMarketSignal is operational—via the opening question. It doesn't explicitly list alternatives or when-not-to-use cases, but the context is clear enough for an agent to differentiate it from other data-retrieval 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 declare readOnlyHint=true, and the description does not contradict this. The description adds valuable behavioral context beyond the annotation: it explains the scoring range (0-100) with buy/sell thresholds (above 62 buy, below 38 sell) and what output elements to expect (regime, risk, momentum). This helps the agent understand the tool's decision logic without over-explaining.

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 and front-loaded: it opens with the core user question, then lists outputs, then provides usage guidance and scoring thresholds. Every sentence adds value, with no fluff or repetition of schema/annotation 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?

With zero parameters and an existing output schema, the description needs only to explain the tool's purpose, scope (20 cryptocurrencies), and decision thresholds. It does all of this in a compact form, making it sufficiently complete for an agent to select 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 zero parameters, so the schema description coverage is trivially 100%. Per the rubric, a baseline of 4 applies when there are no parameters. The description adds no parameter details because there are none to describe, which 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 what the tool does: returns top 3 buy and sell recommendations from 20 cryptocurrencies plus market regime, risk level, and momentum. It distinguishes itself from siblings like get_asset_signal or get_performance by positioning itself as a consolidated overview, with 'Best starting point for portfolio decisions.'

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 the tool: 'Best starting point for portfolio decisions.' While it doesn't explicitly name alternatives or state when not to use it, the positioning as a starting point implies a workflow of broad briefing followed by deeper dives with 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?

Annotations already declare this as a read-only operation, and the description adds meaningful behavioral detail: it returns 30-day rolling metrics, includes a reputation score (0-100), and breaks down by asset and timeframe. This gives the agent a clear picture of what to expect beyond just the read-only hint. No contradictions with annotations; the description aligns with the read-only nature.

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, front-loaded with a question that sets the context, followed by a concise list of returned metrics. There is no unnecessary detail, and every sentence contributes to understanding the tool's purpose and output. It is appropriately sized for a simple read-only reporting tool.

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?

With an output schema present, the description does not need to document the return structure. It covers the key aspects: the rolling 30-day window, the types of metrics (accuracy, reputation, breakdowns), and the timeframe options. It is complete for a no-parameter tool, though it could have briefly clarified whether this covers all signals or a specific asset context relative to get_asset_performance.

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 is empty with zero parameters, so there is no parameter semantics to explain. According to the guidelines, 0 params earns a baseline 4. The description appropriately focuses on return values instead, which is useful for a no-argument tool.

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 function: returning 30-day rolling accuracy metrics for crypto signals. It specifies what is included (overall accuracy, reputation score, breakdowns by asset and timeframe), which gives a clear sense of resource and output. However, it does not explicitly distinguish itself from the sibling tool get_asset_performance, so it doesn't fully meet the 'distinguishes from siblings' criterion for 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 description implies the use case: check how accurate crypto signals are. It gives context about the rolling window and metrics, but it does not explicitly say when to use this over alternatives (e.g., get_asset_performance) or when not to use it. There are no exclusions or alternative recommendations, so the guidance is implied rather than 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?

The readOnlyHint annotation already signals a safe read operation, and the description adds useful context about the output's components. Yet it does not disclose behavioral nuances such as the meaning of the time window, whether data is aggregated or raw, or any rate limits—so it provides only modest extra transparency beyond 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 two short sentences with no filler. It front-loads a relatable example, then specifies the exact metrics included, earning every word.

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 simple: one optional parameter, an output schema, and a read-only hint. The description covers the main output categories and the example clarifies intent. It only lacks a brief note about the 'days' parameter's effect, which prevents a perfect score.

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 only parameter, 'days', is not mentioned in the description. With 0% schema description coverage, the description was expected to compensate but does not. The schema alone provides the name and default, but no explanation of how the day range affects the metrics or whether it is a rolling window.

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 ('View x402 micropayment analytics') and enumerates concrete metrics (total paid calls, revenue in USDC, conversion rate, daily payment timeline), making the tool's purpose immediately clear and distinct from generic siblings like get_analytics.

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 opening question 'How much revenue has AgentMarketSignal generated?' establishes a clear use case for revenue monitoring. However, it does not explicitly mention when to avoid this tool or compare it to alternatives like get_analytics or get_performance, so it falls short of full guidance.

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