CryptoPulse Data API

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 pricing ($0.002 USDC per call via x402) which is genuinely useful operational context beyond the schema. However, it doesn't describe return format, error cases, or rate behavior — but for a zero-parameter read-only sentiment tool this is reasonably 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?

One compact sentence conveys pricing, the resource, the value type (index + classification), and the additional previous-day trend data. It's front-loaded with the most important scoping information first. Slightly under-specified on what the 'classification' values might be (e.g., 'Extreme Fear', 'Greed'), but no explicit waste.

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

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

For a zero-parameter, no-output-schema read tool, the description is nearly complete. It states the data returned (value, classification, previous day for trend) which covers the practical return contract. It could mention the classification scale band, but that's a minor gap for a simple sentiment endpoint.

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

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

The tool has 0 parameters, and schema coverage is 100% (trivially so, since there are no parameters to document). The description fully covers what the tool returns. There's nothing more parameter semantics could add since no parameters exist.

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 returns the current Crypto Fear & Greed Index value, classification, and previous day for trend. The verb 'Current... value and classification' with the specific resource (Fear & Greed Index) is distinct from siblings like gas, price, and market_summary which cover different data domains.

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 doesn't explicitly state when to use vs alternatives, but the domain (Crypto Fear & Greed Index) is highly specific and distinct from all siblings (gas, price, screener, yields, etc.), making the use case self-evident. The 'previous day for trend' hint clarifies this is for sentiment/market-mood context rather than price data.

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 the behavioral disclosure burden. It does disclose the cost ($0.002 USDC per call via x402), the data source (public RPC), and the output units (wei and gwei). However, it doesn't mention whether this is a safe read-only operation, response format details, or failure behavior when RPC is down. The cost disclosure is notable transparency but the overall behavioral picture is incomplete.

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 critical pricing/cost information and then states the core function with units and supported chains. Every element earns its place with zero redundancy or 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?

For a simple 1-parameter tool with 100% schema coverage and no output schema, the description provides the essential context: cost, chains, output units, and data source. It could add what the response looks like (though output schema is absent, not required), but for a tool of this simplicity it covers the agent's key selection needs adequately.

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% and there's only one parameter (chain) which is fully described in the schema as 'base (default) or ethereum'. The description adds the default behavior ('base (default)') context and the units of output, but the schema already documents the parameter adequately. The description adds minimal additional value beyond confirming the chain options and default.

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 provides live gas price in wei and gwei for Base or Ethereum mainnet via a public RPC. The verb 'gas price' combined with the specific chains and units makes the purpose unambiguous, and it distinguishes itself from sibling tools like price, ohlc, and market_summary which serve different market data purposes.

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 specifies the supported chains (Base or Ethereum mainnet) and implies when to use it (when live gas price data is needed). While it doesn't explicitly state when NOT to use it or name alternatives, the sibling tools are clearly different domains (market sentiment, OHLC data, screening), so the usage context is reasonably clear. It doesn't mention any exclusion 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?

No annotations are provided, so the description carries the full burden. It discloses the cost model upfront ('$0.01 USDC per call via x402'), which is valuable behavioral transparency for an agent deciding whether to invoke this metered tool. It also implies read-only behavior by the nature of a snapshot brief. The fee disclosure is a notable transparency feature beyond typical descriptions.

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 and front-loaded with the most important info (pricing and one-call nature). Every clause carries meaning. Minor deduction: the pricing disclosure could arguably be structured as separate metadata, but it earns its place given no annotations exist. It's appropriately minimal 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?

For a zero-parameter aggregate tool with no output schema, the description reasonably covers what's returned (prices, 24h change, fear/greed, top-5 trending). It could improve by noting the exact data precision/format, but given the simplicity of a snapshot tool with no parameters, this is adequately complete. The aggregate nature across sibling tools is communicated well.

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

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

The tool has 0 parameters, and schema coverage is trivially 100% (empty schema). Per guidance, 0 params = baseline 4. The description adds value by clarifying what data the returned brief contains, which effectively documents the semantics an agent would otherwise learn from parameters. No parameter ambiguity exists since there are none.

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 verb ('one-call market brief') and lists the exact resources covered: BTC/ETH/SOL prices with 24h change, Fear & Greed index, and top-5 trending coins. This bundles several sibling tool concerns (price, fear_greed, trending) into a single snapshot, clearly distinguishing its all-in-one aggregate purpose from the individual 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 explicitly frames it as ideal 'for agents that need a single snapshot,' giving clear usage context. It does not explicitly name alternatives or when NOT to use it, but the breadth of covered data (prices + fear/greed + trending) implies when an agent needs all three at once versus individual sibling tools. A clear use case is stated even without exclusions.

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 disclosure burden. It mentions the $0.005 USDC per call cost, which is useful. However, it doesn't describe the response format, whether data is historical capped, data granularity per range, or any rate limits. For a data-fetching tool with zero annotations, this is a meaningful gap.

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 packs the cost, resource type, and supported ranges efficiently. It's front-loaded with the cost disclosure. Minor waste: the enumerated day values duplicate what's in the schema's days description, but this is lightweight.

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 data-retrieval tool with 3 params and full schema coverage, the description covers the core need: what data, what ranges, and cost. However, with no output schema and no annotations, it omits return format (candle structure, OHLC fields), which could be ambiguous. Acceptable but not thorough.

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 context by enumerating valid 'days' values (1, 7, 14, 30, 90, 180, 365) which reinforces the schema's vague '1 | 7 | ...' list. It doesn't add format/syntax details for 'id' or 'vs' beyond schema, but the schema already covers these with examples.

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 verb+resource: 'OHLC candlestick data for any CoinGecko coin id' with specific time ranges enumerated. It distinguishes this from siblings like 'price' (current) and 'market_summary' by specifying it's historical candle data. However, it doesn't explicitly contrast with siblings, so not a 5.

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 it's for retrieving candlestick data but gives no when-to-use guidance or exclusions. It doesn't mention that 'price' might be better for current spot prices or when one might prefer different ranges. The supported range values (1-365 days) are listed, providing some guidance, but no explicit alternatives are named.

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 the burden. It discloses the pricing model ($0.002 USDC per call via x402) which is useful cost context. However, it doesn't describe response format, rate limits, or whether it returns a single price or full market data blob for each id.

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—two compact sentences covering cost and function. The pricing info is front-loaded, which is useful. No wasted words, though it could be slightly more complete.

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 2-param tool with 100% schema coverage and no output schema, the description is largely adequate. However, it omits what the response looks like (since there's no output schema) and doesn't state any limit on number of ids or error behavior for invalid CoinGecko ids.

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 both parameters (ids, vs) are already documented in the schema. The description adds the default quote currency (usd) context, which the schema also covers. It adds marginal value by confirming the comma-separated format for ids, but this mostly mirrors 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 clearly states it provides spot prices for cryptocurrencies in various quote currencies, using CoinGecko ids. It distinguishes from siblings like ohlc (history) and market_summary, though it doesn't explicitly name alternatives.

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 (spot price lookup) but doesn't explicitly state when to use it vs siblings like market_summary or ohlc. No exclusions or alternative tool names are given, leaving the agent to infer based on purpose.

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

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

With no annotations provided, the description carries the full burden. It discloses the pricing model ($0.10 per call), the revenue model (x402), and behavioral traits like dropping honeypots/balance-modifiable tokens during safety screening. It doesn't disclose rate limits or response time, but the core behavioral disclosure (paid, safety semantic) is present.

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 compact at roughly 50 words yet covers purpose, filtering, safety, and output. It front-loads the pricing note and primary purpose. Slightly dense with parentheticals, but efficiently packed 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?

For a moderately complex multi-parameter screener with no output schema and no annotations, this description covers the key elements: purpose, filters, safety behavior, and output fields. It doesn't describe the ranking criteria in detail, but given no output schema and no annotations, it does a solid job. Minor gaps around what 'ranked opportunities' means and the exact safety screening limitations.

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% and each parameter already has description with defaults (e.g., mode defaults to trending, limit defaults to 10 max 20, network defaults to base). The description adds context around how parameters interact (safe_only running on Base tokens), and clarifies that 'safe_only' drops dangerous tokens. Most meaningful semantics are already in the schema, so the description adds marginal value.

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+resource structure ('Token screener: trending or newly-launched pools on a chain') and clearly specifies the scope (chains, filtering criteria, safety screening). It distinguishes itself from siblings like 'trending' by adding liquidity/volume filters and safety screening, and lists concrete outputs (price, liquidity, volume, buys/sells, safety flags).

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 states the tool is for finding 'trending or newly-launched pools' with filtering criteria, which establishes a clear context. It doesn't explicitly name alternatives or when-not-to-use, but the sibling tool 'trending' is implicitly differentiated by the additional filtering and safety screening capabilities. The pricing note also sets usage expectations.

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 the full burden. It discloses the pricing model ($0.01 USDC per call via x402), which is valuable cost transparency for the agent. It also discloses the data breadth (across DEXes). It doesn't detail pagination or response format, but with an undefined output schema and 1 param, the provided behavioral details are reasonably solid.

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 dense, well-structured sentence conveys pricing, data scope, and search modalities. Zero wasted words, no redundancy with the schema.

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 search tool with full schema coverage and no output schema required, the description covers purpose, pricing, scope, and search options. It could add example result categories or disambiguation behavior (e.g., multiple tokens matching a symbol), but current coverage is strong for the tool's simplicity.

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% and the description reiterates the parameter's meaning ('Search by symbol, name, or contract address'), which matches the schema's own description. The description adds marginal breadth by explaining that the query expands across DEXes, but it doesn't add substantive syntax, format, or example-level detail beyond the schema. 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 verb ('search') and resource (DEX trading data for a token) while enumerating specific data points: pairs, price, liquidity, volume, 24h txns/change across DEXes. It also specifies the search modalities (symbol, name, or contract address), distinguishing it effectively from sibling tools like price, ohlc, and market_summary.

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 implicitly signals usage context: this is a DEX-focused data tool for a single token, contrasting with price (likely single price point) and screener (multiple tokens). However, it doesn't explicitly state when NOT to use it or name alternative tools, so it gets a 4 rather than 5.

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

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

No annotations are provided, so the description carries the burden. It discloses the pricing ($0.02 USDC per call) and outlines what checks are performed, which is helpful transparency. However, it doesn't disclose return format, whether it's a read-only operation, or whether partial results are returned when a check fails or times out.

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 pricing disclosure and core purpose. The list of checks (honeypot, mintable, owner privileges, tax, LP holders) adds value without bloat. Minor inefficiency: the pricing note at the start could be positioned as secondary, but overall it's tight.

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 security-check tool with no output schema and 100% schema coverage, the description reasonably covers purpose and some behavioral aspects (pricing, checks performed). However, it leaves unanswered what the output looks like, how risks are scored/returned, and whether the 2-cent cost covers failed checks. A trading agent needs to know what response format to expect before invoking.

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%, meaning both chain and address are documented in the schema. The description adds the token security context but doesn't add parameter-level meaning beyond what the schema already provides — it lists which checks the token undergoes but doesn't detail how each parameter affects results. 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 checks token security / rug-pull risk for any ERC-20, listing specific checks (honeypot, mintable, owner privileges, tax, LP holders). It uses a specific verb (risk check) plus resource (ERC-20 token), which distinguishes it from sibling tools like price, gas, yields, and token_score.

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 it is an 'Essential pre-trade safety check for trading agents', giving clear usage context. It doesn't explicitly name alternative tools or when-not-to-use scenarios, but the pre-trade safety positioning distinguishes it from the price/score/market siblings implicitly.

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 the burden. It does disclose the cost ($0.05/call), the verdict scale, and that it combines two analysis dimensions. However, it doesn't state that returns a structured or paginated result, whether the call is rate-limited, or what the '0-100' score entails beyond the label tiers. Helpful 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?

Single dense paragraph, front-loaded with the key question the tool answers and the price signal. Every clause adds value: cost, composite score, verdict list, one-call positioning. Zero waste.

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 two simple parameters, no output schema, and no annotations, the description is nearly complete for a scoring verdict tool. It explains inputs (address, chain), the output verdict ladder, the cost, and the purpose. Missing detail on what the numeric 0-100 maps to exactly, but verdict tiers are already listed.

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 value by explaining what the address input produces (a composite verdict) and clarifying the chain field defaults. The 'default base' and enum list in the schema handle most parameter detail; description adds situational meaning around the address parameter's role in scoring.

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 states a specific verb+resource ('Composite 0-100 buy-safety score for any token') with clear scope and a concrete output verdict scale. It distinguishes itself from the sibling token_risk by explicitly combining contract analysis with market depth into a single score, and from price/screener by being a one-call verdict tool.

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 frames the use case explicitly ('One call answers: should my agent touch this token?') and mentions the pricing condition. However, it doesn't explicitly name alternatives or say when NOT to use this vs token_risk, though the composite-vs-single-dimension distinction is implied.

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?

The description discloses the cost ($0.002 USDC per call via x402), which is useful behavioral context not in annotations (none provided). However, it doesn't disclose output size, refresh rate, or how 'trending' is determined beyond 'most-searched.' With no annotations to carry the safety profile, some burden falls on the description, which partially addresses it but lacks depth.

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 concise sentence that front-loads the pricing information before the purpose. It's efficient with no waste, though the pricing detail could arguably be considered extraneous in the description (it might belong in annotations or metadata). Still appropriately compact.

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 is very simple (0 params, no output schema), so the description need not be extensive. It states what data is returned (rank, price, 24h change). However, with no output schema, it doesn't detail how many items are returned or the exact response format, leaving some ambiguity for a tool agents will use for market data.

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

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

The tool has 0 parameters, so there's no parameter semantics to document. The schema coverage is 100% (empty properties), and the description doesn't need to add parameter meaning. Baseline 4 applies for zero-parameter tools since there's nothing for the description to explain.

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

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

The description clearly states the tool returns top trending cryptocurrencies (most-searched coins) with rank, price, and 24h change. It uses specific verbs and resource, and the naming 'trending' distinguishes it clearly from siblings like market_summary or price.

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 doesn't explicitly state when to use this vs alternatives, but the 'trending' concept and 'top trending cryptocurrencies' framing make the use case reasonably clear. No exclusions or alternatives are named, but the context of it being the trending/popularity tool among siblings is implied.

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 the burden. It discloses the pricing ($0.02 USDC via x402) which is a notable behavioral trait, the data source (DefiLlama), and the fact that it returns filtered APY rankings. The description adds useful context beyond what a bare schema would provide, though it doesn't describe return format specifics.

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?

A single, dense sentence that packs in the pricing, purpose, filtering dimensions, output fields, and data source. Every phrase earns its place with zero filler or 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 reasonably covers the tool's purpose and filtering capabilities. With 100% schema coverage and no output schema requirement, the description sufficiently covers what the agent needs. Could add where sorted results land (e.g., pagination behavior) but for a filter-and-list tool with well-documented params, this is largely 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 coverage is 100%, so parameters are already well documented with descriptions (chain default, limit range, min_tvl default, stable_only value). The description adds context about what 'stable_only' filters for (stablecoin pools) in the output, but the schema already covers the parameter semantics well. 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 'Top DeFi yield opportunities' with a specific verb and resource. It specifies the output details (project, symbol, APY breakdown, stablecoin flag) and data source (DefiLlama), distinguishing it well from the financial-ish siblings like fear_greed, price, gas, etc.

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 the filtering dimensions (chain, minimum TVL) and what data is returned. It doesn't explicitly name sibling alternatives or state when NOT to use this tool, but the filtering criteria and data source give clear context for when to invoke it.

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