Strale - 290+ API capabilities for AI agents

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

With no annotations provided, the description carries the full burden. It discloses return format ('EUR cents (integer) and formatted EUR string'), authentication needs ('Requires an API key'), and error behavior ('returns an auth instruction if none is configured'). This is strong transparency for a simple read-only tool, though it stops short of mentioning potential rate limits or side effects.

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 the core purpose, then usage guidance, then output details and auth note. Every sentence adds value, and the structure is logical and easy to scan.

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?

This is a simple, parameterless tool. The description covers its purpose, when to use it, return format, and authentication requirement. Since there is no output schema, the description adequately informs the agent about what to expect. It is fully sufficient for the tool's complexity.

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 for this dimension is 4. The description doesn't need to explain parameter semantics, and it correctly focuses on output and usage rather than inventing unnecessary 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 the tool's function: 'Returns the current Strale wallet balance.' This is a specific verb+resource combination that distinguishes it from sibling tools like strale_transaction or strale_execute, which involve different operations.

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 explicit usage context: 'Call this before executing paid capabilities to verify sufficient funds, or after a series of calls to reconcile spend.' It doesn't explicitly name alternatives, but the guidance is clear and actionable, warranting a 4 rather than a 5.

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

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

With no annotations provided, the description takes full responsibility for disclosing behavior. It reveals that the tool returns a result object with output, latency, price, and provenance, explains free vs. paid capabilities including a 10/day limit, and notes that paid capabilities debit the wallet. It also mentions that execution fails if the price exceeds max_price_cents, which is significant behavioral context.

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 four sentences and each sentence adds distinct value: execution purpose, usage context, return object, and pricing/free-tier guidance. It is well-structured and front-loaded with the primary action, though it could be slightly more concise by merging the pricing and balance-check advice.

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 3 parameters, nested objects, and no output schema, the description is remarkably complete. It explains the return object's key fields, the prerequisite search step, the free/paid pricing model, and the max_price behavior. This gives an agent enough information to invoke the tool correctly without needing additional external documentation.

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%, so the schema already documents each parameter. The description adds value by providing example slugs, clarifying that inputs should match the capability's required fields from search results, and explaining the default and failure behavior of max_price_cents. This goes beyond the schema's basic property descriptions.

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 executes a Strale capability by slug and returns the result, with specific examples of use cases (verification, validation, lookup, data extraction). It also distinguishes itself from siblings by instructing to call strale_search first, making its role as the execution tool unambiguous.

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 says 'Use this when you need to perform any verification, validation, lookup, or data extraction' and directs the agent to call strale_search first to find the right slug and input fields. It also advises checking strale_balance for high-value calls, providing clear when-to-use and contextual guidance for related tools.

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

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

With no annotations available, the description carries the full burden. It discloses that no API key is required, what the tool returns (free-tier capability list, x402 route, full registry info), and the expected first-connection behavior. This is good coverage for a no-input, read-only onboarding 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 three sentences and front-loaded with the core purpose. Every sentence adds value: what it does, when to call it, what it returns, and that no API key is required. No redundant or filler 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?

This is a simple, zero-parameter onboarding tool with no output schema. The description fully covers the purpose, invocation timing, return contents, and authentication requirement, making it complete for its intended use.

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 schema coverage is 100% by default. The description appropriately focuses on behavior rather than parameter syntax, and the baseline of 4 is appropriate since no parameter 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 uses a specific verb ('Explains how to start using Strale') and clearly defines the resource and scope ('what is available without credentials'). It distinguishes itself from siblings by focusing on first-connection onboarding, free-tier capabilities, and the no-signup x402 route.

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 'Call this on first connection,' which provides clear usage context. It does not mention exclusions or alternatives, but for a getting-started tool this is sufficient and unambiguous.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that it returns a reference document and that no API key is required, which implies a read-only, low-friction operation. It does not mention rate limits, output size, or any state changes, but for a zero-parameter info tool these are minor gaps.

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?

A single, efficient sentence that front-loads the primary behavior (returns a reference document), then lists the covered topics, and ends with an important auth requirement. Every word adds value 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 zero-parameter, no-output-schema tool, the description fully covers what an agent needs: what it returns, its content scope, and whether authentication is needed. Nothing essential is missing.

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 schema coverage is trivially 100%. The description correctly adds no parameter-specific details because none exist; the baseline for a no-parameter tool is 4, and the description doesn't need to compensate.

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?

States a specific verb ('Returns') and resource ('Strale's trust methodology') and lists the document's contents (test cadence, audit records, provenance). While it doesn't explicitly distinguish itself from siblings like strale_getting_started or strale_trust_profile, the described content uniquely identifies it as a methodology reference.

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 contextual hints about when to use it (when you need trust methodology, test cadence, audits, provenance) and notes that no API key is required. However, it does not explicitly state when not to use it or name alternative tools, leaving the routing to inference.

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 and does well by disclosing the returned fields (status, version, tool count, capability count, solution count, timestamp) and authentication requirements. It could explicitly state that it has no side effects, but 'Checks' strongly implies a safe read-only operation.

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 deliver complete information: purpose, usage timing, return payload, and auth requirement. Every sentence earns its place 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 zero-parameter health check with no output schema, the description is fully complete. It addresses what the tool does, when to use it, what it returns, and access requirements. Nothing else is needed.

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 fully covers this aspect and the description correctly adds no parameter details. The baseline score of 4 applies because there is nothing to explain.

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 ('Checks') and clearly identifies the resource (Strale API reachability and MCP server status). Its scope is distinct from all sibling tools, which focus on transactions, searches, and profiles, making it unambiguous as a health check.

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 states when to invoke the tool: 'before a series of capability executions to verify connectivity' or 'when troubleshooting connection issues.' It also notes that no API key is required, giving a clear prerequisite.

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

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

With no annotations provided, the description discloses key behavioral traits: returns ranked results with specific fields ('slug, name, description, category, and price in EUR cents') and states 'No API key required to search.' This goes beyond a simple 'search' claim, although it omits potential rate limits or error 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 three sentences, front-loaded with the core action and immediately followed by usage guidance, return details, and auth note. Every sentence adds value with no redundancy.

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 search tool with no output schema, the description covers what it returns, how to use it (when to use), and access requirements. It is sufficiently complete for an agent to invoke the tool correctly, even without annotations.

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%, but the description adds meaning beyond schema by explaining that the query accepts natural language, that results are ranked by relevance, and that categories span company data, compliance, etc. This enriches the schema's simple parameter descriptions.

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: 'Searches the Strale capability registry by keyword, category, or natural language query.' This specifies the verb (searches), resource (capability registry), and scope (keyword, category, natural language), distinguishing it from sibling tools like strale_balance or strale_execute.

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: 'Use this when you need to find the right capability for a task but don't know the exact slug.' This tells the agent when to choose this tool over others, though it does not explicitly name alternatives or exclusion scenarios.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the return fields (inputs, outputs, latency, price, etc.) and the API key requirement for free-tier access. It does not mention potential failure modes, rate limits, or data retention, but the disclosed information is substantial and useful.

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 with no wasted words. It opens with the primary purpose, then lists return value specifics, and closes with usage context and access requirements. Each sentence earns its place and the structure is immediately scannable.

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 required parameter, no nested objects, no output schema), the description is complete: it specifies what the tool returns (compensating for the missing output schema), highlights the relevant sibling relationship to strale_execute, and mentions authentication nuances. No critical context is missing for an agent to 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 input schema describes transaction_id as 'Transaction ID returned from a strale_execute call', which already fully documents the sole parameter. The description echoes this ('previous strale_execute call') but adds no new semantic meaning beyond what the schema provides, so the baseline 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 uses a specific verb ('Retrieve') with a clear resource ('past execution record by transaction ID') and enumerates the returned content (inputs, outputs, latency, price, data provenance, success/failure status, failure categorization). This clearly distinguishes it from sibling tools like strale_execute, which creates executions.

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 states when to use this tool: to inspect previous strale_execute results, debug failures, or provide an audit trail. It also notes that free-tier transactions are accessible without an API key, providing important context. However, it does not mention when not to use it or name alternative tools explicitly, so it stops short of a 5.

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 reveals a deliberate design behavior: 'Strale deliberately exposes no single numeric quality score — judge from the test history and limitations.' It also states 'No API key required,' and outlines the return fields (lifecycle state, timestamps, etc.). With no annotations, the description carries the full burden and does so well.

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 4 sentences, front-loaded with the primary action, then usage, return contents, and a key caveat. Every sentence adds value, with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description adequately covers when to use it, what it returns, and a critical design constraint (no numeric score). It also notes authentication. This is sufficient for an agent to select and invoke the 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?

Schema coverage is 100% with both slug and type described, including examples. The description only adds general context (trust profile) and doesn't extend parameter syntax or format, so a baseline 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 states a specific verb ('Returns') and resource ('trust profile') and clarifies scope (capability or solution). It also notes usage context, making it clear what the tool does and when it applies.

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 'Call this before relying on a capability for high-stakes decisions, or when a user asks how reliable a specific check is,' giving clear when-to-use guidance. It doesn't list alternatives or exclusions, but the context is sufficient.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a simple 'returns data' statement by detailing the output structure (verdict, reason_codes, evidence map, audit_url) and performance characteristics (8s budget vs sub-second SLA). It does not explicitly state whether the tool is read-only or requires authentication, but the nature as an analysis tool is implicit. The transparency is strong but not exhaustive.

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 longer than average, but it is front-loaded with the primary purpose in the first sentence and then efficiently covers outputs, modes, and usage. Each clause adds value, and the structure is logical (what → what it returns → modes → when to use). It is slightly dense but not wasteful, earning a 4 rather than a 5.

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 that there is no output schema, the description thoroughly explains the return values (verdict, reason_codes, critical_flags, suggested_action, evidence map, audit_url) and the two operational modes with their SLA differences. It also provides concrete examples of supported targets and usage context. This is a comprehensive description that leaves little ambiguity for an agent.

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 100% coverage with detailed descriptions for all 8 parameters, including enums and defaults. The tool description adds minimal parameter-specific meaning beyond what the schema already contains—it restates the mode names and general context but does not clarify parameter syntax, formats, or edge cases. Therefore, the baseline score of 3 applies.

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 opens with a specific verb and resource: 'Returns a decision-ready answer about an on-chain counterparty...' It clearly enumerates the tool's outputs (verdict, reason_codes, critical_flags, etc.) and distinguishes it from sibling tools by focusing on risk assurance across multiple asset types. This is unambiguous and immediately scopes the tool's 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 when to use the tool: 'Use before any agent transacts on-chain — sending value, swapping, staking, minting, bridging, or interacting with a contract.' It also differentiates two modes ('outbound' vs 'reverse-call') with distinct use cases and SLA expectations. However, it does not mention when not to use it or name alternative sibling tools, so it falls short of a 5.

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