Stratalize Crypto & DeFi

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context about data source and metrics but does not disclose further behavioral details (e.g., rate limits, data freshness). It is consistent 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 a single dense sentence but front-loads the main purpose. It efficiently lists several metrics. Could be slightly improved with structure but 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 no output schema, the description covers the output metrics but lacks details on return format or structure. It mentions 'for x402 agent context' which is helpful, but completeness is limited for an agent needing to parse the result.

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 2 parameters with 0% description coverage. The tool description does not explain the parameters (limit, sort_by) or their allowed values beyond what the schema shows. Minimal additional meaning is provided.

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 live TVL by blockchain from DeFiLlama, listing specific metrics like rankings and comparisons. It distinguishes itself from sibling tools that focus on other benchmarks.

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 mentions 'for x402 agent context' but does not explicitly state when to use this tool versus alternatives. Usage is implied by the name and metrics, but no exclusions or alternatives are given.

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 destructiveHint=false, providing a safety baseline. The description goes beyond by detailing specific behavioral traits: returns HTTP 503 with no charge when upstream is unavailable, has a $0.10 USDC per call x402 SLA, and includes a 'data_source' field for provenance. This fully discloses error behavior and cost implications.

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 main purpose and provides additional context in a logical order. However, it contains redundancy (the 503 note appears twice) and some extra details that could be streamlined. Overall, it is fairly concise for the amount of information conveyed.

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 key aspects: what is returned (correlation matrix, beta, dominance, diversification), data source (DeFiLlama), intended users (crypto portfolio agents), live status, error handling, and SLA pricing. It lacks explanation of the parameter meaning and does not describe the output format, but given the absence of an output schema, the description provides sufficient orientation for a data retrieval 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?

There is only one parameter 'period' with enum values (7d, 30d, 90d), and schema description coverage is 0%. The description mentions '30-day rolling' but does not clarify that the parameter controls the rolling window length, creating ambiguity. The description fails to explicitly map the parameter to its effect, leaving the agent to infer its meaning.

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 explicitly states it provides a '30-day rolling correlation matrix for BTC, ETH, and SOL' with details on Pearson pairs, beta, dominance, and diversification. The verb is clear (retrieves/computes), the resource is specific (crypto correlation benchmark), and it distinguishes from the sibling 'get_stratalize_overview' through its specific focus on correlation analysis.

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 indicates this is 'for crypto portfolio agents' and mentions it is a 'live source' with SLA pricing and error handling. While it does not explicitly state when to avoid it or name alternatives, the purpose is clear enough for an agent to infer appropriate use cases. The context provides sufficient guidance for selection.

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 destructiveHint=false, indicating a safe read operation. The description adds context about the data source (DeepDAO public data) but does not disclose additional behavioral traits such as cache behavior, rate limits, or data recency. No contradictions 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 concise (two sentences) and front-loaded with the main purpose. However, by omitting parameter information, it sacrifices completeness for brevity, which is a minor structural flaw.

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 two optional parameters (one with enum), no output schema, and annotations covering safety, the description adequately covers the high-level return but lacks detail on parameters and return structure. It is sufficient for simple usage but incomplete for parameterized queries.

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%, yet the description does not explain the two parameters (`sort_by` and `min_treasury_usd`). The description focuses on output rather than input, leaving the agent without guidance on how to filter or sort. This is a significant gap for a tool with no schema 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 returns DAO treasury benchmarks, listing specific metrics like treasury size, stablecoin percentage, runway, and concentration. It provides example medians and a data source, distinguishing it from sibling tools that focus on other benchmarks (e.g., chain TVL, crypto correlation).

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 DAO treasury data but does not provide explicit guidance on when to use this tool versus alternative benchmark tools. No exclusions or comparative context is given.

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 adds value by noting the free public API with no key required and detailing the returned data structure, providing additional behavioral context 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 three sentences, front-loaded with key information, and every sentence provides value. 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?

The description fully explains the tool's purpose, data returned, parameters, and default behavior. No output schema exists, but the description compensates adequately. For a simple fetch tool with two optional params, it is complete.

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 100% schema coverage, baseline is 3. The description enhances parameter meaning by explaining that 'protocol' is a project slug substring and 'asset' is a symbol substring, also clarifying the default universe without filters. This adds useful context.

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 provides a DeFi yield benchmark from DeFiLlama, listing specific data (APY bands, TVL, chain, pool id). It distinguishes from sibling benchmarks by focusing on 'DeFi lending and stable yield' and mentioning stablecoin-marked pools as the default universe.

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 mentions optional filters and the default universe, but does not explicitly state when to use this tool versus siblings like get_stablecoin_yield_benchmark. Usage context is implied but not fully specified.

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?

Beyond readOnlyHint annotation, it discloses potential HTTP 503 errors, billing details, and the inclusion of a data_source field for provenance. These are valuable behavioral traits not in 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 front-loaded with the core purpose and efficiently covers outputs, costs, error handling, and source in just a few sentences. 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 simple schema and no output schema, the description covers all necessary aspects: purpose, return types, cost, error handling, and data source. It is fully self-contained.

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 single optional parameter 'chain' is fully explained by listing supported chains and their specific comparisons (e.g., Base vs ETH savings). This compensates for the 0% schema description 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 explicitly states that the tool provides live gas price benchmarks for Ethereum, Base, and Solana, and lists specific outputs like Gwei, USD cost, congestion category, and x402 context. It clearly distinguishes from sibling tools which focus on other metrics.

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 gives strong contextual cues such as cost per call ($0.10 USDC), error behavior (HTTP 503), and no API key required. While it doesn't directly compare to alternatives, the purpose and sibling names make appropriate usage clear.

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 indicate safe read operation (readOnlyHint=true). Description adds critical details: HTTP 503 on upstream failure with no charge, SLA pricing ($0.10 USDC), and data_source provenance field. 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?

Description is verbose, containing multiple details (metrics, source, pricing, error handling, SLA) in a single paragraph. While front-loaded with core metrics, it could be more concise and 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 single parameter and no output schema, description provides rich context about returned data (7D/30D IV, ratios, signals) and failure modes. Cost and SLA details enhance completeness. Slight lack of output format is mitigated by listing data points.

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?

Only one parameter 'asset' with enum values (BTC, ETH, all). Schema coverage is 0%. Description mentions BTC and ETH in metrics but does not explicitly describe the parameter. The enum values are self-explanatory, but description could have mapped them clearly.

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 it provides 'Crypto options implied volatility benchmarks' and lists specific metrics (BTC/ETH 7D/30D IV, put/call ratio, etc.). This distinguishes it from sibling tools like get_chain_tvl_benchmark or get_defi_yield_benchmark.

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?

Description targets 'options traders and volatility agents' and mentions sources (Deribit + FRED), but does not explicitly state when to use this tool vs. alternatives. However, the context of siblings being different benchmarks provides implicit 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's addition of specific data returned (yields, TVL, YoY growth) and source provides useful behavioral context 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?

Three concise sentences, front-loaded with the main purpose, and no extraneous information. Every sentence adds value.

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 optional parameter, no output schema, clear annotations), the description covers the essential: what data is returned, source, and market context. It could explicitly state how to use the category filter.

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 schema description coverage at 0%, the description indirectly ties the 'category' parameter to 'RWA market TVL by category' but does not explicitly list or explain the enum values. The schema provides the enum, so the description adds some meaning but not fully compensates.

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 'real-world asset tokenization benchmarks' including specific examples (Ondo, BlackRock BUIDL, etc.) and metrics (yields, TVL, growth). This differentiates it from sibling tools like get_chain_tvl_benchmark or get_defi_yield_benchmark.

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 RWA benchmarks are needed but provides no explicit guidance on when to use this tool versus alternatives. It does mention data source and total market size, offering some context.

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?

Beyond annotations (readOnlyHint=true, destructiveHint=false), the description adds critical behavioral context: the tool is a live source, may return HTTP 503 if upstream data is unavailable for >50% fields, and no charge is incurred on error. This enriches the agent's understanding of reliability and cost.

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 dense paragraph, front-loading the core purpose. It efficiently conveys key features (bands, TVL, spread) and caveats (source, error behavior). While verbose, it earns its length with specific details.

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 (multiple assets, protocols, chains, stats, and no output schema), the description covers input, data sources, error behavior, and output content (bands, TVL filter, spread). It does not detail the return format or TVL filter mechanics, but is sufficiently complete for an agent to understand what the tool returns.

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 0% schema description coverage, the description must compensate. It mentions USDC/USDT/DAI and 'all', which corresponds to the enum parameter 'asset', but does not explicitly explain the parameter or the 'all' option. This adds some meaning but not comprehensive clarification.

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 provides stablecoin lending yield benchmarks for USDC/USDT/DAI across specific protocols and chains, with statistical bands and spreads. It is distinct from sibling tools like get_defi_yield_benchmark which cover broader DeFi yields, but no explicit differentiation is made.

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 stablecoin yield benchmarks but does not provide explicit guidance on when to use this tool versus alternatives like get_defi_yield_benchmark or get_chain_tvl_benchmark. No exclusions or conditions are stated.

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 destructiveHint=false. The description adds valuable behavioral context: no auth needed for basic access, pricing tiers, and OAuth requirements for certain features, going 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?

Three sentences with clear front-loading ('START HERE'). Every sentence adds value: purpose, access details, and call to action. 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 no output schema and zero parameters, the description adequately covers what the tool returns (catalog across domains) and access methods. Could mention return format (e.g., list), but overall complete for a discovery 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?

No parameters exist, so baseline is 4. The description explains the tool's output (catalog listing) without needing param details, adding sufficient context for 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 the tool returns the complete Stratalize tool catalog, serving as a discovery entry point. It distinguishes from sibling benchmark tools by its broad scope and 'START HERE' directive.

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 says 'START HERE' and 'Call this first to discover tools by role or vertical.' Also details access modes (public MCP, x402 micropayments, OAuth), providing clear when-to-use guidance.

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