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

With no annotations, the description must disclose behavior. It clearly indicates a read-only ranking operation and lists return fields. However, it does not mention rate limits, pagination, or side effects, which would be beneficial for a complete 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 concise and well-structured: a brief purpose statement, usage context, and a clear args list. Every sentence adds value, with no redundancy or unnecessary detail.

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 return fields adequately. It covers parameter details and implies differentiation from siblings. However, it lacks information on error handling, empty results, or performance limits, 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 0%, so the parameter explanations in the description are critical. The description provides clear semantics for each parameter: sort options, category examples, filter choices, and limit range. This fully compensates for the missing schema descriptions.

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

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

The description clearly states the tool ranks Polymarket whales by performance metrics, with examples of sorting keys and filtering by category. It distinguishes from siblings such as 'wallet_overview' (individual wallet) or 'markets' (market 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 explains when to use the tool (find top traders) but does not explicitly list alternatives or when not to use it. Sibling tools like 'wallet_overview' or 'whale_alerts' are not mentioned, leaving some inference needed.

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 disclosure burden. It details that two consensus reads can disagree, explains which to trust, flags a structural skew on longshots, and warns against over-interpreting divergence. This is exemplary 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 well-organized: core purpose first, then usage, then behavior nuance, then an argument spec. Every sentence adds useful guidance, with no 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?

Even without an output schema or annotations, the description conveys what data is returned (head_count, capital_weighted, price, divergence), how to interpret it, and the accepted input formats. An agent has enough to invoke it correctly and interpret results safely.

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 0%, but the description fully compensates by explaining that the single 'market' parameter accepts an id, slug, URL, or 0x condition id. This gives an agent actionable format guidance beyond the bare 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 states a specific resource ('one Polymarket market') and a precise purpose: comparing smart-money consensus to current price. It is clearly distinct from the sibling tools, which focus on wallets, leaderboards, or market 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?

It explicitly says to use the tool to answer 'what does smart money think about this market?' and to spot disagreement with the crowd. It does not name alternatives or state when not to use it, but the usage context is clear.

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 carry the behavioral transparency burden. It covers input behavior (accepts URL or slug, '' browses) and output content (question, YES price, smart-whale counts, volume, days left). This is good, but it doesn't disclose any potential side effects, rate limits, or whether this is read-only (likely, but not explicit). It also doesn't specify error behavior or pagination. However, for a search tool, this level of 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?

The description is reasonably concise, with a clear opening sentence and structured Args section. It front-loads the primary purpose and then details parameters. Each sentence adds value. The only minor issue is that the Args section includes some redundancy (e.g., category listing values, which is also in schema as a string but not enum, so it's useful). Overall, it's well-organized and not overly verbose.

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 optional parameters, no output schema, no annotations), the description covers the essential aspects: what it does, when to use, parameter semantics, and return fields. It lacks explicit error handling or edge cases (e.g., what happens with invalid category), but that's minor. The absence of an output schema makes the return description valuable, and it provides it. The tool is well-documented enough for an agent to call 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?

Schema description coverage is 0%, so the description must compensate. It does: for q, it explains it accepts a URL or slug and that '' browses. For category, it lists possible values. For min_volume and min_whales, it explains they filter by USD and counts, respectively. For limit, it says 'how many markets to return (1–100)' which adds range validation. However, it doesn't clarify the default behavior for each parameter when not specified, or how they interact. The description includes all parameter meanings, but the interaction among filters is left unclear, so a 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 it searches Polymarket markets and highlights the smart whales feature, distinguishing it from siblings like wallet_overview or leaderboard. It specifies the resource (markets) and the verb (search), and mentions the unique value of tracking smart money flows. However, it could be more explicit about how it differs from market_consensus, but the emphasis on 'smart whales' and 'returns each market's question, YES price, smart-whale counts' provides good 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 gives clear context: 'Use this to track smart money flows' and describes filtering options, which implies when to use it (when you need market data with whale activity). It doesn't explicitly mention when not to use it or alternatives, but the sibling list is available and the description's focus on whale-centric data suggests it's for a specific use case. It could improve by stating 'for general market info without whale focus, use market_consensus' but it's not misleading.

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?

Excellent. Even though no annotations exist, the description fully carries the burden by disclosing the async 'computing' state with retry_after_seconds and the instruction to poll after the delay, plus the design behavior of returning a digestible summary for heavy wallets. This is exactly the non-obvious behavior an agent cannot infer on its own.

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 well organized: headline purpose, supporting detail, async edge case, then parameter doc. It earns most of its sentences, and the computing-notice paragraph is vital. It loses a point because the parameter semantics ('Accepts... OrcaLayer nickname') are redundantly restated in the Args section after already appearing in the intro.

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 one parameter, no output schema, and no annotation support, the description is nearly complete: it covers accepted inputs, return-style behavior, the polling/retry contract, and the rationale for compact output. The only minor omission is that it never shows a sample response shape or mentions what happens on a malformed address, which is a marginal 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?

With 0% schema description coverage, the description is solely responsible for parameter meaning, and it fully delivers: the address parameter's accepted forms ('0x wallet address or OrcaLayer nickname') are documented both in the intro and the Args block. The bare schema only reveals a string titled 'Address,' so the description's value-add is substantial.

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 opening line uses a specific verb and resource: 'Summarize one wallet's trading profile and performance.' It names the domain (Polymarket), the accepted inputs (0x address or OrcaLayer nickname), and the output shape (compact summary with identity, activity, P&L stats). The phrase 'one wallet' plus the contrast with 'full raw record' sharpens the scope without ambiguity.

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 decision context: choose this tool when you want aggregate stats rather than the full raw record, and it explains the compact-summary tradeoff for heavy wallets. However, it never names sibling tools like wallet_positions or whale_alerts explicitly, so an agent must infer the routing rather than have it spelled out.

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 sorting by current value, returns compact form with omitted count, and that wallet may hold more than limit. No annotation provided, so description handles burden well.

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

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

Two short paragraphs with an Args section. Every sentence adds value; no filler. Well-structured and easy to parse.

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?

Covers inputs and some output behavior, but lacks description of individual position fields (especially given no output schema). Vague 'compact form' leaves agent guessing the structure.

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 has 0% coverage; description adds full meaning: address accepts 0x address or nickname, limit is from 1 to 50 with default 15. Compensates completely.

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 'list a wallet's largest open positions by current value' with specific verb and resource. Distinct from siblings which are leaderboard, markets, overview, alerts.

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?

Explains inputs (address, limit) and output behavior (sorted, truncated with omitted count). No explicit when-not or alternatives to siblings, but context is clear.

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 that the tool returns real-time alerts, requires a Premium key, and explains exactly what happens without a key: it returns a short notice, does not call the API, and is not an error. It also reveals default constraints like minutes max and limit range.

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 well structured: purpose sentence, return summary, usage sentence, auth requirement, and a compact Args block. Every sentence adds necessary information and the most important details are front-loaded.

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 no output schema and no annotations, the description explains the return content, all parameters, the authentication prerequisite, and the no-key fallback. It is sufficiently complete for an agent to invoke the tool correctly and interpret its response.

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 0%, so the description must compensate. It explains every parameter: minutes as lookback window max 1440, min_usd as minimum trade size, category as optional single market category, and limit as alert count 1–100. This is exactly the level of detail 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 opens with a specific noun phrase and verb: 'Recent trades by smart-money whales' and 'Returns whale trades...' It clearly states what is returned (who traded, buy/sell, side, amount, price, market) and distinguishes this tool from sibling tools focused on leaders, wallets, and markets.

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

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

The description explicitly says when to use it: 'Use it to get alerts when profitable Polymarket wallets open or close positions.' It also states the API key requirement and the fallback behavior without a key. It does not name alternatives, but the use case is clear enough for an agent to pick it correctly among siblings.

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