RNWY — AI Agent Trust Intelligence

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

With no annotations provided, the description carries the burden of behavioral disclosure. It indicates a read-only lookup of age in days and adds a trust-related note ('time cannot be faked'), but does not detail any side effects, prerequisites, or output format. This is adequate for a simple read 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?

The description is two short sentences, front-loaded with the primary action, and contains no filler. Every word contributes to understanding the tool's purpose.

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 lookup tool with full schema coverage and no output schema, the description covers the essential behavior and the unit of measurement. It could mention the output format explicitly, but the phrase 'age in days' implies the return value sufficiently.

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 already provides 100% coverage of both parameters (address and chain) with descriptions. The tool description adds no extra parameter-specific detail, so the baseline 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 uses a specific verb ('Look up') and clearly identifies the resource ('wallet age in days') for any address. The phrase 'uncheatable signal' also differentiates it from sibling tools that likely measure 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 no explicit guidance on when to use this tool versus alternatives. It states 'for any address,' which is a scope, but there is no 'when not to use' or mention of alternative 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, the description carries the burden of disclosure. It does state the output metrics and protocol scope, which is useful for a read-only stats tool, but it does not mention data freshness, pagination, error behavior, or parameter precedence. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence that front-loads the purpose and lists key metrics and protocols without any filler. Every phrase 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?

The description lists return metrics, partially compensating for the lack of an output schema, but it leaves ambiguity about parameter requirements (schema marks all as optional) and how id/address/chain combine. These gaps prevent a fuller understanding of successful invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes all four parameters with 100% coverage, so the description adds little beyond what the schema provides. It references agent vs. address but does not clarify required combinations or mutual exclusivity, 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 clearly identifies the tool as providing commerce activity data (job count, unique counterparties, repeat client rate, total earnings) for an agent or address, and specifies supported protocols. It is specific and distinct from siblings like network_stats, but it does not explicitly differentiate itself from all sibling 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?

The description gives clear context: it applies to an agent or address and covers Olas Mechs and Virtuals ACP protocols, implying when to use it. However, it does not provide explicit exclusions or mention alternative tools for different use cases.

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 behavioral disclosure. It reveals that the tool ranks agents by score and provides a reviewer quality summary, which is useful. However, it does not explicitly state that this is a read-only operation, how the threshold parameter affects behavior, or any error/edge-case traits such as handling invalid chain:id pairs.

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 that front-loads the core purpose (side-by-side comparison) and then supplies key specifics (2-10 agents, ranking, summary). No wasted words, and all information is relevant.

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 and lack of output schema, the description provides a good high-level summary but omits details like what 'score' means, how the threshold parameter is applied, and the exact structure of the output. It is adequate as a minimal viable description but not fully complete for all agent use cases.

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 100% for both parameters, so the baseline is 3. The description itself adds no additional meaning about the 'agents' or 'threshold' parameters beyond what the schema already lists. It doesn't explain how the threshold value influences the comparison or the output ranking.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('compare') and resource ('agents'), and clearly scopes the behavior: side-by-side comparison of 2-10 agents, ranked by score with reviewer quality summaries. This distinguishes it from sibling tools like trust_check (likely single-agent) and reviewer_analysis (likely focuses on one reviewer).

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 does not provide any guidance on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or comparative context with sibling tools. It simply states what the tool does, leaving the agent to infer applicability.

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 burden of disclosure. It details what data is returned (agents, trust scores, sybil signals, etc.), which adds transparency. However, it does not discuss return format, potential latency, or any operational side effects, limiting full behavioral transparency.

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 that front-loads the core action ('Full operator footprint') and then enumerates the included data points. 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 single-parameter lookup tool with no output schema, the description adequately communicates the scope of results by listing five data categories. It is complete enough for basic understanding, though it could briefly mention how results are presented (e.g., aggregated vs raw) to be fully self-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?

The schema already fully describes the sole parameter 'wallet' as 'Wallet address (0x...)', giving 100% coverage. The description adds no additional parameter context beyond the schema, 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 clearly states the tool's purpose: 'Full operator footprint for any wallet address' and lists specific data categories (agents owned, trust scores, sybil signals, wallet intelligence, MCP servers). This distinguishes it from sibling tools like address_age or trust_check, which focus on narrower 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 implies this is the go-to tool for a comprehensive operator overview ('Full operator footprint'), but it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or prerequisites beyond providing a wallet address.

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?

There are no annotations, so the description carries the behavioral disclosure burden. It does reveal the return payload (risk score, threat findings, signed envelope) and the verification mechanism (JWKS endpoint with kid rnwy-mcp-v1). However, it does not state whether the tool is read-only, whether any network calls are made, or if special permissions are required. This is moderate transparency 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 a single sentence that packs all essential information: signing algorithm, scope, output components, and verification mechanic. No redundant or filler text. It is front-loaded with the most important detail (signed attestation) and remains succinct.

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 single-parameter schema and absence of an output schema, the description appropriately explains what is returned (risk score, threat findings, signed envelope) and how to verify it. It does not elaborate on the meaning of the risk score or the format of threat findings, but those are secondary for correct invocation. The tool appears simple enough that the description is adequate for an agent to decide to call 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 schema already describes the only parameter canonical_id with a clear example. The description does not add any additional meaning about the parameter beyond the schema description. Since schema coverage is 100%, the baseline 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 clearly states it produces an ES256-signed attestation for any MCP server, and enumerates the outputs: risk score, threat findings, and a signed envelope. The verb is implicit but the noun 'attestation' with the details makes the function unmistakable. Sibling tools (address_age, network_stats, etc.) are thematically distinct, so no confusion.

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 context is clear: use this when you need an attestation for an MCP server, identified by canonical_id. It does not name alternative tools or explicitly say when not to use it, but the purpose is specific enough that the intended usage is implied. No exclusions are stated, but the tool's unique function is obvious.

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 disclosing behavior. It lists the exact breakdowns it returns (registry, chain, commerce job counts, trust score tiers) and notes the 180,000+ agent scale, which is useful context. However, it does not describe the response structure or any potential limitations, though the simplicity of a no-parameter stats tool reduces the need.

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, tightly packed sentence that conveys all essential information without redundancy. Every element contributes to understanding the tool's output and coverage.

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 fully covers what users need to know: the type of statistics and the scope. It is complete and self-contained, though adding an explicit statement that it returns aggregated data could marginally improve clarity.

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 zero parameters, so the baseline is 4. The description adds contextual meaning about the scope of the returned statistics (network-wide, 180,000+ agents), but there are no parameter details to elaborate on.

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 providing network-wide statistics, enumerating specific metrics like agent counts by registry, chain distribution, commerce job counts, and trust score tiers. While it lacks an explicit action verb, the intent is unambiguous and distinct from the sibling tools, though it does not directly differentiate itself from similar tools like commerce_stats.

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?

No guidance is given on when to use this tool versus alternatives. The description simply states what it does without mentioning any context, prerequisites, or exclusions, leaving the agent to infer appropriate usage from the tool name alone.

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 are provided, so the description carries full burden. It states the analysis performed but does not disclose output format, required permissions, data sources, or limitations. Like the 'update_drive' calibration example, this leaves significant gaps for a tool with no 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?

Two sentences with no fluff: the first states the core function, the second highlights a key detection capability. Every word 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?

For a tool with no output schema and no annotations, the description gives a general idea of the analysis but not the return structure or any prerequisites. It is adequate for a simple analysis tool but not fully 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?

The schema already provides basic descriptions for id and chain ('Agent ID' and 'Chain slug'), with 100% coverage. The description adds little beyond confirming that id refers to the agent whose reviewers are analyzed, but it does not elaborate on chain values or format.

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 ('analyze') and resource ('wallet ages of reviewers on an agent'), and it distinguishes itself from sibling tools like address_age by focusing on all reviewers and sybil pattern detection rather than a single address.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for detecting sybil patterns, but it does not explicitly state when to use it over alternatives like address_age or reviewer_wallet. No exclusions or alternative suggestions are provided, so the agent must infer usage from 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It lists the types of analysis performed (velocity, sweep patterns, etc.) but does not specify whether the tool is read-only, any access requirements, or operational limitations. This lack of tool-behavior context results in a score of 2.

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, front-loaded sentence that begins with the core concept 'Behavior profile' and efficiently enumerates the key metrics. Every word serves a purpose, making it highly concise and well-structured. Score 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?

The tool has no output schema, so the description is expected to convey return expectations. While it names several output aspects (velocity, sybil signals), it does not explain the overall output structure or how the 'summary' parameter affects the response. This leaves a meaningful gap, so a score of 3 is given.

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% description coverage for all three parameters (chain, address, summary), giving a baseline of 3. The description adds context about the ecosystem and wallet focus but does not clarify parameter usage beyond the schema. Thus, a 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 identifies the resource (reviewer wallet) and the specific behavioral metrics (velocity, sweep patterns, score clustering, sybil signals) within the ERC-8004 ecosystem, using 'Shows' as the action verb. However, it does not explicitly distinguish from the similar sibling tool 'reviewer_analysis', reducing the score to 4.

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 no guidance on when to use this tool versus alternatives like 'reviewer_analysis' or 'trust_check'. It only defines what the tool does, leaving the user to infer the appropriate use case. This warrants a score of 2.

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 transparently lists what the tool returns, includes a methodology reference link for deeper transparency, and implies a read-only behavior through 'risk intelligence.' It does not explicitly state side effects, but for a data lookup tool 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?

The description is two concise sentences: the first states purpose and outputs, the second gives target users and a methodology link. Every sentence earns its place with no redundant text.

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

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

Despite having no output schema, the description lists all return categories (risk tier, trust signals, data coverage, methodology reference). It gives a clear use case and a link for further details. It does not cover error handling or prerequisites, but the schema and use case cover most needs.

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 100%, so the schema already documents all three parameters. The description adds contextual context only in the phrase 'for any agent,' which loosely relates to agent_id. It does not add 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: providing counterparty risk intelligence for an agent, with specific outputs (risk tier, trust signals, data coverage, methodology reference). This is distinct from sibling tools like address_age or trust_check, which focus on different risk dimensions.

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 targets a use case: 'Designed for marketplace operators and escrow providers setting transaction parameters before a deal.' This gives clear context for when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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 are provided, so the description carries full burden for behavioral disclosure. It states what the tool returns but does not disclose side effects, permissions, idempotency, failure modes, or whether it performs any writes. This is minimal transparency for an unannotated 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 two sentences with no filler. It front-loads the core purpose and then lists the return fields, making it easy to scan and process.

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 moderate complexity and absence of an output schema, the description provides a useful summary of return values (score, tier, badges, reasoning) and covers the registries. It does not mention edge cases or error behavior, but for a check-like tool the provided context is largely adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so all four parameters already have descriptive meaning. The description adds a small amount by framing the result as a pass/fail verdict with score, tier, badges, and reasoning, but does not enrich 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 a specific verb phrase 'Pass/fail trust verdict' with a clear resource ('any AI agent') and scope ('across ERC-8004, Olas, or Virtuals registries'). It differentiates from siblings like compare_agents and risk_terms by focusing on trust verdicts with output types.

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 clearly implies this tool is for obtaining a trust verdict on an AI agent, giving context for when to use it. It does not explicitly exclude alternatives or mention when not to use it, but the context is clear enough for selection.

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