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 adds valuable context: 'Creates entries for unknown addresses' (indicating a side effect), 'Requires a paid API key ($100/mo)' (indicating cost and authentication needs). It does not mention rate limits or error handling, but provides key behavioral traits beyond basic functionality.

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 extremely concise and front-loaded, consisting of three sentences that each add critical information: purpose, side effect, and cost requirement. There is no wasted text, and it efficiently communicates essential details without 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?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is somewhat complete but has gaps. It covers purpose, side effects, and cost, but lacks details on output format, error conditions, or how the assessment decision is made. Without an output schema, the agent is left uncertain about return values, making this minimally adequate but not fully comprehensive.

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 parameters thoroughly. The description does not add any parameter-specific details beyond what the schema provides (e.g., it doesn't explain how 'min_grade' and 'min_score' interact). Baseline score of 3 is appropriate as the schema handles parameter semantics adequately.

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: 'Assess a wallet's trustworthiness and get an allow/deny decision.' It specifies the verb ('assess') and resource ('wallet'), but does not explicitly differentiate from sibling tools like 'check_wallet_reputation', which might have overlapping functionality. The description is specific but lacks sibling differentiation.

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

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

The description implies usage context by stating 'Requires a paid API key ($100/mo)', which suggests when to use this tool (i.e., when budget allows). However, it does not provide explicit guidance on when to use this tool versus alternatives like 'check_wallet_reputation' or when not to use it, leaving the agent to infer usage 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 full burden for behavioral disclosure. It mentions 'Free tier' which hints at potential limitations, but doesn't describe rate limits, authentication requirements, response format, pagination behavior beyond the cursor parameter, or what happens when no filters are applied. For a tool with 6 parameters and no annotations, this is insufficient.

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, efficient sentence that states the core purpose and key filtering options. 'Free tier' adds useful context without unnecessary elaboration. However, it could be more front-loaded with the primary action before listing filters.

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 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (agent details, counts, etc.), how results are structured, or behavioral aspects like rate limits. The 'Free tier' mention is insufficient to cover the complexity of this browsing/filtering 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 description coverage is 100%, so the schema fully documents all 6 parameters. The description mentions filtering by 'chain, score, grade, or entity type' which aligns with parameters but adds no additional semantic context beyond what's in the schema. This meets the baseline for high schema coverage.

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

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

The description clearly states the action ('browse') and resource ('registered ERC-8004 agents'), and mentions filtering capabilities. However, it doesn't explicitly differentiate from sibling tools like 'get_ecosystem_stats' which might provide related but different data. The purpose is specific but lacks sibling 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?

The description provides no guidance on when to use this tool versus alternatives like 'assess_wallet' or 'check_wallet_reputation'. It mentions 'Free tier' but doesn't explain implications or when to choose this over paid options. Usage context is implied through filtering parameters but not explicitly stated.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively adds context by specifying it's 'cached' data (implying potentially stale information), 'read-only, no writes' (clarifying safety), and 'Free tier' (hinting at rate limits or access constraints), which are valuable beyond basic functionality.

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

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

The description is front-loaded with the core purpose, followed by return details and behavioral context, all in two efficient sentences with zero waste. Every sentence earns its place by adding critical information.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is mostly complete: it covers purpose, return values (score, grade, etc.), and key behavioral traits. However, it lacks details on error handling or exact output structure, leaving minor gaps.

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 both parameters ('address' and 'chain') adequately. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or default behavior, meeting the baseline for high coverage.

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

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

The description clearly states the specific action ('Look up') and resource ('cached trust reputation for a wallet address'), distinguishing it from siblings like 'assess_wallet' by specifying it's cached data rather than a fresh assessment. It precisely defines what the tool does.

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

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

The description implies usage by mentioning 'Free tier — read-only, no writes,' suggesting it's for basic reputation checks without modifications. However, it doesn't explicitly state when to use this tool versus alternatives like 'assess_wallet' or provide clear exclusions, leaving some ambiguity.

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 tool returns statistics but doesn't disclose behavioral traits such as data freshness, rate limits, authentication needs, or whether it's a read-only operation. The description is minimal and misses key operational details needed for safe and effective use.

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, efficient sentence that front-loads the core purpose ('Returns ecosystem-level statistics') and specifies key data points without waste. Every word contributes to understanding the tool's function, making it appropriately sized and well-structured.

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

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks context on usage, behavioral traits, or output format. Without annotations or output schema, more detail on return values or operational constraints would improve completeness for a network statistics 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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, but this is acceptable as there are no parameters to explain. A baseline of 4 is appropriate since the schema fully covers the absence of inputs.

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 with a specific verb ('Returns') and resource ('ecosystem-level statistics about the AgentScore network'), including key data points (ERC-8004 agents, reputation scores, payment activity). It distinguishes from sibling tools like 'assess_wallet' or 'check_wallet_reputation' by focusing on network-wide metrics rather than individual entities. However, it doesn't explicitly contrast with 'browse_agents', which might also involve agent listings.

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. It doesn't mention prerequisites, timing, or compare it to sibling tools like 'browse_agents' (which might list agents) or 'check_wallet_reputation' (which focuses on individual wallets). Usage is implied by the purpose but lacks explicit context for selection.

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