Askew x402

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

With no annotations, the description carries the transparency burden. It discloses that the call is free and acts as a verification/status check, implying a non-mutating read-only operation. It does not detail rate limits or auth, but for a simple health check this is sufficient.

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 cover purpose, returned content, and usage guidance without redundancy. The description is front-loaded with the tool's purpose and each 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 zero parameters, no output schema, and no annotations, the description is sufficiently complete: it states what is returned, that it is free, and when to use it. The 'x402 endpoint' specificity and distinction between free and paid calls round out the context.

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 the description correctly notes it returns status without requiring input. Baseline for 0 parameters is 4, and no further explanation is needed.

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 identifies the tool as a service status check for the Askew x402 endpoint, listing the exact output fields (wallet address, network, pricing, payment summary). This distinguishes it from sibling tools focused on intel, offers, or yields.

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 explicitly states when to use it: 'before making paid calls' to verify operational status. The 'Free' label contrasts with paid alternatives, providing clear context. It does not explicitly name alternative tools, so a score of 4 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?

With no annotations, the description discloses critical behavioral context: the $0.005 USDC fee, x402 payment requirement on Base mainnet, and the data sources (ChromaDB, Guardian log, staking.db). It doesn't explicitly state read-only behavior, but the term 'feed' and context strongly imply it. It also doesn't mention failure modes or response format, but coverage is strong for a feed 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?

Three concise sentences: purpose, sources, usage recommendation, cost/payment. Every sentence delivers essential information without 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?

The description covers what the tool returns (aggregated feed components), cost, payment network, and source systems. It lacks an explicit description of the output format, but given no output schema and zero parameters, the description is sufficiently complete for an agent to decide to invoke it.

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 already provides full coverage. The description adds no parameter details because none exist; the baseline of 4 is appropriate for a parameterless 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 identifies the tool as an 'aggregated intelligence feed' and explicitly names its components (research findings, security threats, staking APY). It distinguishes itself from sibling tools by stating it 'replaces three separate calls' to research, threats, and yields 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 explicit usage guidance: 'Best for: broad situational awareness — replaces three separate calls.' This directly tells the agent when to use this tool over alternatives, and the sources listed imply when specialized tools would be more appropriate.

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, the description carries the full burden of disclosure. It mentions the x402 payment requirement on Base mainnet and the $0.002 USDC cost, deduplication by category, and the lookback window. It does not cover failure modes or rate limits, but for this tool the key behaviors are disclosed.

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 information-dense: two sentences plus a usage recommendation and payment note. Every sentence adds value—purpose, data content, categories, best use case, and payment requirement—with 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?

Given the tool's low complexity (one optional parameter, no output schema), the description covers the essential aspects: what it returns, when to use it, and what it costs. It lacks a detailed output structure, but for a log-entry retrieval tool the description provides sufficient context for an agent to decide and invoke 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 only parameter, hours, is fully described in the schema with a default, min, and max. The description merely references 'last N hours' without adding any new meaning beyond the schema, so the baseline score of 3 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's function: it returns live threat intelligence from the Askew Guardian security monitor, specifically WARNING/ERROR/CRITICAL log entries. This distinguishes it from sibling tools like askew_intel_feed and askew_health by specifying the security-monitoring focus and the types of data returned.

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 recommends the tool for 'security triage before agent operations,' providing clear context for when to use it. It does not name alternative tools or state when not to use it, but the primary use case is well established.

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, the description must carry the full burden of behavioral disclosure. It notes 'No payment required,' implying the access itself is free. However, it doesn't explicitly state whether the tool is read-only, makes external calls, or if there are any side effects. For a catalog, the behavior is largely inferred rather than disclosed.

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, with the first sentence clearly stating purpose and contents, and the second adding usage guidance and a payment note. Every word earns its place; no fluff or repetition.

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 catalog tool with no parameters and no output schema, the description is complete. It tells the agent what the tool offers, when to use it, and that there's no cost. There is no missing critical information for making an invocation decision.

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 the rubric sets a baseline of 4 for 0-param tools. The description doesn't need to add parameter meaning because none exist, and it provides sufficient context about what the tool returns.

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 identifies the tool as a 'Curated catalog of all available paid Askew endpoints' with specific contents (pricing, sample calls, buyer intent context). This distinguishes it from sibling tools that focus on individual endpoints, and the verb 'catalog' implies a listing/informational purpose.

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 explicitly states it is the 'Best starting point for agents exploring what Askew sells,' giving clear usage context. It doesn't specify when not to use it or list alternatives, but the 'starting point' phrasing implies it should be used before delving into specific endpoint 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?

No annotations provided, so the description carries the full burden. It discloses the cost ($0.003 USDC), the payment requirement (x402 on Base mainnet), technical backend (ChromaDB), and update frequency (every 12h), going beyond the basics. However, it does not explicitly state whether the operation is read-only or describe error/side-effect behavior.

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, with each sentence conveying a distinct piece of information: function, technical details, use case, and payment. 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 purpose, usage, cost, and collections, but for a search tool with no output schema, it does not describe the shape of the results (e.g., snippets, scores, metadata), leaving a notable gap.

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 q, limit, and collection. The description's mention of collections mirrors the schema enum and does not add new parameter semantics 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 uses the specific verb 'semantic search' over a defined resource ('500+ Askew agent-economy research findings, operational insights, and experiments'), clearly distinguishing it from sibling tools focused on health, intel, offers, etc.

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?

It provides a 'Best for' clause indicating when to use it (finding what Askew already learned about agent monetization or DeFi strategy), giving clear context though it doesn't explicitly mention alternatives or when-not-to-use.

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, the description carries the full burden. It discloses data sources (DefiLlama + staking portfolio), caching (up to 6h), and a critical payment requirement on Base mainnet. It does not explicitly state read-only nature or return format, but the 'routing recommendation' implies non-mutating behavior.

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 five short sentences that each add value: what it is, what it does, data source, use case, and requirement. It is front-loaded and well-structured with clear labels like 'Best for' and 'Requires'.

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 parameters and no output schema, the description is complete. It covers purpose, inputs (implicitly none), outputs, data sources, caching, cost, and usage context. An agent can confidently decide when and how to invoke it.

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 doesn't require explanation. The description adds no parameter-related info, but the baseline for 0 params is 4, and there is nothing 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 is a 'staking yield router' for SOL and ATOM, with the specific action of comparing native PoS vs liquid staking and returning a routing recommendation per chain. It distinguishes from sibling tools by focusing on staking routing and explicitly identifies its best use case.

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?

It provides explicit usage guidance with 'Best for: deciding native vs liquid staking' and mentions a prerequisite (x402 payment). However, it does not explicitly name alternatives or exclusions, though the context implies other yield tools might be for different purposes.

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 several behavioral aspects beyond annotations (which are absent): it lists a specific cost ($0.002 USDC), a data source (DefiLlama), cache duration (6h), and a payment requirement with an unpaid-fallback behavior (returns payment requirements envelope). This is strong for a tool with no annotations, though it doesn't elaborate on rate limits or post-payment execution 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 compact and well-organized, with purpose, return data, cost, data source, and usage intent each in a short clause. No redundant content; each sentence carries distinct 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?

Despite lacking an output schema, the description explains what will be returned (top 5 pools per chain with APY, TVL, project name), the chains covered, payment flow, and data freshness, making it sufficient for an agent to decide whether and how to invoke 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?

The input schema has no parameters, so the description's mention of 'one call' and chain/cache details is the main semantic framing. Baseline 4 applies for zero parameters; the description does not need to explain parameter 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 it performs a live DeFi yield comparison across 5 chains and returns top pools with APY/TVL/project name. However, it does not explicitly distinguish itself from the sibling tool askew_yields_preview, so it doesn't fully meet the 'distinguishes from siblings' bar.

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?

It provides usage context via 'Best for: quick yield scanning before moving capital,' and mentions data cache and one-call efficiency, but does not state when to use an alternative like askew_yields_preview or when not 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?

With no annotations, the description carries the transparency burden. It states it 'Returns' data and 'No payment required,' implying a non-destructive read operation. It doesn't explicitly say 'read-only' but the preview language is clear enough.

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 concise sentences each serve a purpose: what it does, what it returns, when to use it, and cost. No redundant or fluff content.

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 purpose, output, chains, and payment. It doesn't detail the exact structure of the returned data (e.g., object shape), but given the tool's simplicity and lack of output schema, it is sufficiently 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?

There are 0 parameters, so baseline is 4. The description does not need to explain parameters; it adds value by clarifying the output and usage 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 it is a 'Free preview of top DeFi yield pool per chain' and lists the specific chains (Solana, Cosmos, Ethereum, Base, Arbitrum). It also distinguishes from the sibling tool askew_yields by explicitly mentioning 'Use before buying askew_yields for a full comparison.'

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?

It explicitly says 'Use before buying askew_yields for a full comparison,' giving a clear when-to-use context and naming the alternative full tool. It also hints that this is a lightweight preview for a single best APY per chain.

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