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

While the description adds context about cost ($0.03 USDC) and the classification mechanism, it fails to disclose read-only nature, error handling, rate limits, or output format. Without annotations, the description carries full burden but provides only partial 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?

Three sentences, each serving a distinct purpose: function, mechanism, and cost. Front-loaded and no unnecessary words. Highly concise.

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 clarity on purpose and cost, the description is incomplete for an agent to correctly use the tool. It does not specify the output structure (e.g., list of transactions with risk labels, summary score), error conditions, or behavior when inputs are invalid. Given no output schema, this is a significant gap.

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

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

Schema coverage is 100% with descriptions for all parameters. The description does not elaborate on parameters beyond the schema, but it adds useful context about cost and classification. 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 scans wallet addresses for anomalous transaction patterns by classifying transactions based on counterparties. It provides specific verb ('scan') and resource ('wallet address'), and the classification logic distinguishes it from generic scan tools like anomaly_scan.

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 explicit guidance on when to use this tool versus siblings such as anomaly_scan or token_scan. The description is purely functional and does not indicate prerequisites, exclusions, or alternative 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, the description must fully disclose behavioral traits. It mentions cost ($0.05) only for Base mainnet, while the schema includes three chains, creating ambiguity. No disclosure of rate limits, permissions, or other behaviors beyond the return format.

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: the first covers purpose and scope, the second lists returns and cost. No redundant or filler content; every sentence adds distinct value.

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

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

Given no output schema, the description lists four return components but lacks detail on formats or interpretation. The cost note is incomplete for chains other than Base. Overall adequate but missing some context for full self-containment.

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?

Both parameters (chain, window) are fully described in the schema with enums and defaults. The description adds no additional semantic value beyond the cost note for Base mainnet. Schema coverage is 100%, so baseline 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 the tool scans a blockchain for sequence anomalies, listing specific patterns (whale movements, exchange flows, etc.) and returns defined outputs (story label, anomaly score, novelty level, peak symbol window). It effectively distinguishes from siblings by detailing unique scope and return values.

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 explicit guidance on when to use anomaly_scan versus alternatives like address_scan or whale_alerts. Cost is mentioned only for Base mainnet, but no context on when to choose this tool over others.

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 mentions cost and scanning action but does not disclose whether the tool is read-only, requires authentication, has rate limits, or any side effects. Key behavioral aspects are missing.

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, front-loaded with purpose and scope, and includes cost information without any wasted words. Highly concise.

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 (1 parameter, no output schema, no nested objects), the description covers the essential aspects: purpose, repos scanned, cost, and parameter. It could mention the return format or behavior on no results, but is otherwise 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?

Schema description coverage is 100% for the single parameter 'days', which is adequately described in the schema. The tool description does not add any extra semantic meaning beyond the schema, 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 watches Anthropic/Claude repos for recently merged features, lists specific repos (SDK, TypeScript, Claude Code, courses, cookbook), and mentions cost. It differentiates from sibling tools like github_watch and repo_scan by its specific focus on Anthropic/Claude feature updates.

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 for checking recent features from these repos but does not explicitly state when to use this tool versus alternatives like github_watch or repo_scan. No exclusions or when-not-to-use guidance is provided.

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?

Discloses cost ($0.03 USDC on Base) and return type (story label, anomaly score). However, with no annotations, it misses other behavioral traits like auth requirements, rate limits, or error handling.

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 covering purpose, usage, and cost. No wasted words; front-loaded with key 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?

No output schema, but description minimally explains returns. Lacks detail on 'story label' semantics or anomaly score range. Adequate for a simple 3-param tool but incomplete for full autonomy.

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 description adds little beyond schema. Restates protocol and mentions chain/window but doesn't provide additional meaning or format 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?

Clearly states it performs anomaly scans for DeFi protocols, listing specific contracts (Uniswap, Aave, etc.) and outputs (story label, anomaly score). Distinguishes from sibling tools like token_scan or nft_scan by focusing on DeFi lending/DEX flow anomalies.

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 input format (protocol name or address) and cost, but lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools. No mention of prerequisites or alternatives.

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 exist, so the description carries the full burden. It details the monitoring behavior, output (story label and anomaly score), polling design, and cost ($0.01 on Base mainnet). However, it lacks information on required permissions, rate limits, or side effects (though likely safe).

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 efficient with 5 sentences, each providing distinct information: purpose, value proposition, polling frequency, output format, and cost. 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?

Given 1 optional parameter and no output schema, the description covers core functionality, monitored assets, output format, and operational details (polling, cost). It does not cover error handling or latency but is sufficient for typical 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 single parameter (chain) has 100% schema coverage with enum and description. The description adds minimal extra meaning beyond the schema, only mentioning cost on Base mainnet which could relate to chain but not directly.

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?

Description clearly states it is a 'real-time stablecoin depeg detector' monitoring specific stablecoins (USDC, USDT, DAI) and detecting deviations from peg, spread, and volume spikes. This distinguishes it from sibling tools like address_scan or defi_scan which have different focus.

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?

While the description implies usage for stablecoin depeg monitoring and mentions 'Designed for 1-minute polling,' it does not explicitly compare to alternatives or state when not to use it. The sibling list is provided but no guidance on choosing this tool over others.

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

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

With no annotations, the description discloses behavioral traits: cost ($0.03 USDC) and engine (SequenceMiner). It does not mention rate limits or auth requirements, but the cost is a significant behavioral trait that aids agent decision-making.

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 concise sentences, front-loaded with the action and key details. Every word earns its place, 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?

Given one optional parameter with high schema coverage, no output schema, and no annotations, the description is reasonably complete. It explains the tool's function, engine, cost, and input region. Could mention return type but not critical.

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 a description for the region parameter. The description adds marginal value beyond the schema since the tool description already indicates named airspace regions. No additional parameter details are provided.

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 performs sequence anomaly analysis for a named airspace region, detecting specific anomalies like emergency squawks, rapid descents, and speed anomalies. It uses a named engine and distinguishes from sibling tools (e.g., anomaly_scan) by being flight-specific.

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 for flight anomaly detection but does not explicitly state when to use this tool vs alternatives like anomaly_scan or other scanning tools. No exclusions or contrasting guidance is provided.

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 must fully disclose behavior. It mentions cost and output format, but fails to clarify key traits: whether this is a one-time query or persistent watch, whether it requires authentication, or if it has side effects. The term 'watch' could imply ongoing monitoring, which is ambiguous.

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 (three sentences) and front-loaded with purpose, then output, then cost. 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?

The description covers purpose, output, and cost, but lacks details like whether the watch is persistent, the anomaly score range, or authentication requirements. For a tool with no output schema and no annotations, it is moderately complete but has 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?

The schema covers 100% of parameters with clear description ('GitHub repo in owner/repo format'), so the description adds no new parameter meaning. 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 purpose: watching a GitHub repo's activity stream for anomalous development patterns. It lists specific examples (commit bursts, force pushes, etc.) and describes the output (story label and anomaly score), making it distinct from sibling tools like repo_scan or anomaly_scan.

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 for anomaly detection in GitHub repos, but lacks explicit guidance on when to use this tool vs siblings (e.g., anomaly_scan). It does not mention prerequisites, when not to use it, or alternatives, leaving the agent to infer 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?

No annotations provided, so description must cover behavior. It implies a read-only, non-destructive check but does not specify return details 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?

One sentence, under 10 words, front-loaded with purpose. No wasted 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?

For a simple health check tool with no parameters and no output schema, the description is adequate. Could mention typical response status but not essential.

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?

No parameters in schema, schema coverage 100% (empty). Baseline 4 for zero parameters; description adds no unnecessary param info.

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?

Description clearly states verb 'check' and resource 'ForgeMesh Anomaly Tracker API health and uptime'. Distinguishes from sibling tools which are scanning or monitoring 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?

Implied usage as a preliminary health check before other operations, but no explicit when-to-use or when-not-to-use guidance.

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

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

No annotations provided, so description carries full burden. Discloses cost ($0.01 USDC on Base mainnet) and return structure (story label, anomaly score). Lacks details on rate limits or auth, but overall transparent for a real-time monitoring 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?

Single, focused paragraph with front-loaded key information (purpose, polling, cost, output). Every sentence earns its place 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?

Given simple schema (1 param, no output schema, no annotations), description covers core aspects: what it detects, polling suggestion, cost, output. Could mention side effects or read-only nature, but adequate 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?

Only one parameter 'chain' with enum and full schema coverage. Description adds minimal extra meaning beyond schema, just notes Ethereum and Base have RPC access. 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?

Description explicitly lists multiple specific anomaly types (gas spikes, MEV signals, etc.) and provides a clear verb+resource: 'detects mempool anomaly score'. Distinguishes from siblings like token_scan or defi_scan.

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 advises 'Designed for 5-second polling', giving strong context on polling frequency. Does not mention when to avoid or suggest alternatives, but the recommendation is clear and actionable.

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, description carries burden. Discloses cost and data returned, implying read-only behavior. Does not mention authentication or rate limits, but for a simple parameterless tool, transparency 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?

Single sentence, no waste. Front-loaded with action and resource. 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?

Tool is simple with no parameters. Description covers purpose, data returned, and cost. Missing details on per-chain behavior (since no chain parameter) and response structure. Without output schema, description partially addresses return values.

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?

No parameters exist, schema coverage is 100%. Description adds no parameter info, baseline for zero parameters is 4.

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?

Clearly states the action 'Get', the resource 'SequenceMiner model health and training stats per chain', and specific data returned (sequence count and last retrain time). Cost information adds clarity. Distinguishes from siblings through unique resource focus.

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 cost as usage guidance but no explicit when-to-use or alternatives. Siblings are listed but not differentiated. Lack of exclusions limits guidance.

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

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

No annotations provided, so description carries transparency burden. It discloses 'best-effort' nature, cost, and that it returns status and notes, implying read-only. However, it does not explicitly state no side effects or required permissions.

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 front-load key information: anomaly scan for NFT collections, detections, return content, and cost/chain context. No wasted 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?

With no output schema, the description explains return type ('source status plus coverage notes') and detection types, giving adequate high-level context. However, lacks detail on output format or behavior across chains beyond Base mainnet cost.

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 covers 100% of parameters with descriptions. The tool description adds 'Pass a contract address' confirming the token parameter and mentions cost on Base mainnet, but does not elaborate beyond schema for chain or window.

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 performs an anomaly scan for NFT collections, specifically detecting sweep accumulation, wash trading, and mint surges. It distinguishes from sibling tools like anomaly_scan (generic) by specifying NFT focus.

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 explains to pass a contract address and mentions cost on Base mainnet, but does not provide explicit when-to-use or alternatives guidance. It implies NFT anomaly detection but lacks exclusions or comparison to other scan 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 bears the full burden. It discloses the cost ($0.03 USDC) and the nature of the scan (star velocity, fork ratio, etc.), but lacks details on rate limits, authentication needs, or whether it's a read-only operation. The return format is partially described.

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: the first explains the core functionality and signals, the second covers output and cost. No wasted words, front-loaded with key 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 only one parameter, no output schema, and no annotations, the description adequately covers the purpose, input format, cost, and output type. It is sufficient for an agent to decide whether and how to 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?

The single parameter 'repo' is fully covered in the schema with a clear description. The main description reinforces the format with examples, adding value beyond the schema's own description. Baseline is 3 due to 100% coverage, but the extra examples earn a 4.

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 explains that the tool performs a deep anomaly scan on a single GitHub repository, listing specific signals (star velocity, fork ratio, etc.) and stating the return type (story label and anomaly score). This is specific and distinguishes it from siblings like 'github_watch' or 'anomaly_scan'.

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 the tool is for a single GitHub repository, but does not provide explicit guidance on when not to use it or contrast with sibling tools. The purpose is clear, but usage boundaries are implied rather than explicit.

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 full burden. It mentions 'Best-effort' indicating non-guaranteed results, and 'source status and coverage notes' hinting at limitations. However, it does not disclose error handling, rate limits, or behavior on empty results.

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: first states the core action and source, second details return content and cost. No wasted words, front-loaded, and 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 no parameters and no output schema, the description adequately explains the tool's return (aircraft with squawk codes, source status, coverage notes) and cost. It could be more explicit about return format but is sufficient for a simple read 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?

There are no parameters (schema coverage 100% trivially). The description adds value by explaining the tool's purpose and return content, compensating for the lack of parameters.

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 performs a 'Best-effort live global sweep of active aviation emergency squawk codes' and specifies the exact codes (7700, 7600, 7500). It distinguishes from sibling tools like flight_scan by focusing solely on emergency squawks.

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 for fetching emergency squawk data but does not explicitly state when to use or when not to use versus alternatives. No exclusions or alternative tool references are provided.

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 full burden. It discloses the read-only nature (scan), 'best-effort' service, cost, and coverage notes. But it lacks details on rate limits, error handling, or how 'anomalies' are determined. This is adequate but not fully transparent.

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, front-loading purpose and input, then cost. Every sentence contributes meaningful information with no redundancy or 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 3 parameters and no output schema, the description gives purpose, input constraints, and output type ('source status plus coverage notes'). It lacks detailed behavior on scoring or anomaly detection but provides enough context for a minimally viable tool. More detail on return format would improve completeness.

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 baseline is 3. The description adds no extra semantics beyond what the schema provides; it only reiterates that token accepts address or symbol. Cost info is context but not parameter-specific. No value added beyond 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 clearly states the tool's function: 'Best-effort anomaly scan for a single token — scores recent transfer patterns for unusual activity and returns source status plus coverage notes.' It specifies the primary verb ('scan'), resource ('single token'), and outcome ('anomaly detection'), distinguishing it from siblings like address_scan or anomaly_scan.

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 input guidance: 'Pass a contract address or well-known symbol.' It also mentions the default chain and cost. However, it does not explicitly state when to prefer this tool over siblings or when not to use it, which would elevate the score.

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

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

No annotations provided, so description carries full burden. It discloses cost ($0.02 USDC on Base mainnet) which is helpful, but does not explicitly state whether the tool is read-only or has side effects. The use case suggests safe querying, but the description could be more explicit.

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?

Description is three sentences: core purpose, detection details, and cost. No redundant words, front-loaded with main action, and efficiently provides context.

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 detection tool, the description covers main functionality, detection targets, and cost. No output schema is provided, but the description implies the tool returns a list of repos with signals. Some detail about output structure would improve completeness.

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% for the single parameter 'days' with enum values and description. The description adds no new semantic information beyond what the schema already provides, so 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?

Description explicitly states the tool finds GitHub repos with anomalous star velocity as early signals, and lists specific detection cases (viral repos, fork surges). This clearly distinguishes it from sibling tools like github_watch or repo_scan by focusing on trending anomalies.

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?

Description mentions use cases (trend hunting, VC scouting) and emphasizes 'early signals before mainstream discovery,' implying when to use. It does not explicitly compare to alternatives or state when not to use, but context from siblings and tool name provides some guidance.

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 exist, so the description fully discloses that the tool costs $0.02 USDC on Base mainnet and lists monitored addresses. This provides key behavioral context beyond a simple read operation, though rate limits or response details are omitted.

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, front-loaded with the action ("Get recent whale movements..."), and no wasted words. 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 no output schema, the description lacks details on return format, pagination, or result count. It adequately covers input and cost but not output, leaving gaps for a data retrieval 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%, so the description adds no extra meaning to parameters beyond what is already in the schema. The description itself does not elaborate on parameter usage.

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 explicitly states the tool retrieves whale movements, CEX flows, bridge activity, and stablecoin actions, listing monitored addresses. It clearly distinguishes from sibling tools like address_scan or token_scan, which focus on different data.

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 mentions a cost and data sources but does not specify when to use this tool over alternatives or provide exclusions. The context of siblings implies differentiation, but explicit guidance is missing.

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