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 carries the full burden and does so admirably. It discloses the return object's contents (capability output, SQS, latency, price, data provenance), free capability limits (5 free, 10/day), paid wallet debiting, and the max_price_cents failure behavior. This is rich behavioral context beyond what structured fields provide.

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 yet dense, with every sentence adding value. It leads with the action, then explains use cases, prerequisites, return details, and cost implications. No wasted words; the structure is logical and 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 complexity (requires slug from search, nested inputs object, pricing constraints, no output schema), the description covers all essential aspects: how to obtain the slug, what inputs to provide, cost control via max_price_cents, free vs paid usage, and what the result contains. The agent has enough information to use the tool correctly without further research.

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?

Although the schema already describes all parameters (100% coverage), the description adds crucial semantics: slug must come from strale_search, inputs must match the capability's expected fields, and max_price_cents has a default and causes execution failure if exceeded. This contextualizes the schema and helps the agent construct valid calls.

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 use cases like verification, validation, lookup, and data extraction. It also distinguishes from siblings by referring to strale_search (for finding slugs) and strale_balance (for cost checks), making the tool's role 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 provides explicit usage guidance: 'Use this when you need to perform any verification, validation, lookup, or data extraction' and instructs to call strale_search first to find the right slug and input fields. It also advises checking strale_balance for high-value calls, covering both when and how to use the 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 provided, the description fully carries the burden. It discloses exactly what the tool returns (5 free capability slugs), including descriptions, example inputs, and instructions, and notes that no API key is required. No side effects exist to disclose.

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 no fluff. The first sentence gives the purpose, the second the usage timing, and the third the return details. Every sentence 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?

Given zero parameters, no output schema, and no annotations, this description is complete. It covers return specifics, the free vs. paid distinction, and the no-API-key requirement, fully enough for an agent to know what to expect.

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. The description does not need to explain parameter semantics; the schema already shows no properties, and the description reinforces that no input 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 states 'Lists the free capabilities available without an API key' with a specific verb and resource. It also tells when to use it ('Call this on first connection') and what it returns, distinguishing it from sibling tools like 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?

It explicitly says 'Call this on first connection' which gives a clear usage context. It does not explicitly mention exclusions or alternatives, but the 'first connection' guidance is sufficient for a getting-started 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 discloses that no API key is required and implies a read-only operation (returns a document), which are useful behavioral details. It does not mention rate limits or error handling, but for a simple static-document tool this is adequate.

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, well-structured sentence. It front-loads the main action, uses an em-dash to efficiently list contents, and includes the access note without extraneous 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?

For a simple tool with no parameters and no output schema, this description is fully adequate. It states what is returned, what topics are covered, and the access requirement, giving the agent enough context 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?

The tool has zero parameters, so the schema is inherently fully covered. The description adds no parameter-specific details, which is appropriate; a baseline of 4 is used for parameterless tools.

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 'returns' and clearly identifies the resource as 'Strale's trust methodology,' a short reference document. It also distinguishes from sibling tools like strale_transaction or strale_balance by focusing on methodology content.

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 mentions 'No API key required,' which sets access expectations, but provides no explicit guidance on when to use this tool over alternatives like strale_getting_started or strale_trust_profile. Usage context is implied but not articulated.

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, the description carries the full burden. It discloses return values (matching capabilities and solutions with specific fields), the scope of the registry (271 capabilities), ranking behavior, and the lack of an API key requirement. It does not mention pagination or rate limits, but for a search tool these are less critical; the offset parameter is covered in the schema.

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 five sentences, each contributing distinct information: purpose, usage context, return format, registry scope, and auth requirement. It is front-loaded with the action and resource, with no redundant phrases. Every sentence 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?

Despite having no output schema or annotations, the description fully explains what the tool returns (fields included) and provides important context about the registry and authentication. Combined with schema-covered parameters, an agent has all necessary information to invoke it correctly for search and understand the result shape.

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 baseline is 3. The description adds meaning beyond the schema by stating the query can be a keyword, category, or natural language query, whereas the schema's query description only mentions 'keyword.' This enriches the agent's understanding of how flexible the query parameter is.

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: 'Searches the Strale capability registry.' It clearly distinguishes this from sibling tools like strale_execute or strale_balance by focusing on discovery via keyword, category, or natural language query. The use case ('when you need to find the right capability... but don't know the exact slug') further sharpens its 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?

Explicitly states when to use the tool: 'Use this when you need to find the right capability for a task but don't know the exact slug.' This is clear contextual guidance, though it does not name alternatives or explicitly say when not to use it. The sibling tools are not referenced, so exclusions are implicit.

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?

With no annotations provided, the description carries the full burden. It discloses the return payload (SQS score, grades, execution guidance, history, limitations, cost envelope) and states 'No API key required'. This is good transparency for a read-only operation, though it doesn't explicitly mention that no changes are made.

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, each serving a purpose: purpose, usage, and return values. It is front-loaded with the core function and contains no filler. Every sentence contributes valuable 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 that there is no output schema, the description fully explains what the tool returns. It also covers authentication requirements and usage context. For a simple read tool with 2 well-documented parameters, this is complete and sufficient.

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' fully documented in the input schema. The description adds only that the tool works for 'a capability or solution', which mirrors the 'type' enum. No additional meaning beyond the schema is provided, so baseline 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: 'Returns the trust profile for a capability or solution'. This is a specific verb ('returns') and resource ('trust profile'), and it distinguishes itself from sibling tools like strale_execute or strale_search by focusing on reliability/quality assessment.

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 explicit when-to-use guidance: 'Call this before relying on a capability for high-stakes decisions, or when a user asks how reliable a specific check is.' It doesn't name alternatives or exclusions, but the context is clear enough to guide an agent.

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.