ScrapeMole Quotes

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

Annotations cover the safety profile (readOnly, idempotent, openWorld), but the description adds genuinely new behavior: x402 USDC pricing on Base at $0.002 per successful call, the PaymentRequired flow, symbol-to-coin resolution to the highest-ranked match, and the exact returned fields. This is far beyond what annotations provide.

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?

Front-loaded with the use case and routing signals, and every clause carries information (limits, defaults, return shape, pricing). It is dense and slightly run-on, but no sentence is wasted.

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?

There is no output schema, and the description compensates by enumerating returned fields (price, 24h change, market cap, 24h volume, last-updated). Combined with limits, defaults, and payment handling, an agent has everything needed 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 coverage is 100%, so the baseline is 3, but the description adds value beyond the schema: the fallback semantics of symbol resolution ('highest-ranked coin with that symbol'), the mutual requirement of ids or symbols, and the spread of supported vs currencies. Marginal but real gain over structured fields.

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?

States a specific verb and resource: cryptocurrency prices across thousands of coins/tokens, with volume of scope. It explicitly contrasts itself with '/v1/crypto/search' (id lookup) and 'ScrapeMole Onchain' (contract-based DEX prices), so an agent can route without opening a schema.

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?

Says when to use it (coin/token prices by id or symbol), how many identifiers each path accepts, and points to two concrete alternatives for adjacent needs. The 'call without payment to receive the PaymentRequired object' note also clarifies invocation behavior.

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?

Beyond the readOnly/openWorld/idempotent annotations, it discloses the result cap (up to 25 matches), the ordering rule (CoinGecko relevance), the exact returned fields, and the payment model ($0.001 per successful call via x402 USDC on Base). Crucially it reveals the unauthenticated behavior: calling without payment returns a PaymentRequired object rather than an error, which the agent would otherwise not know.

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, front-loaded with the purpose and examples, then results, then the payment caveat. Every clause carries information the agent needs; nothing is filler or restated from the title.

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 compensates by enumerating the returned fields and the match ordering, and it covers the non-obvious paid-invocation path. An agent has everything needed to call it correctly and interpret the 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 coverage is 100%, so both parameters are already documented, setting the baseline at 3. The description adds ordering semantics (CoinGecko relevance) and result-shape meaning that the schema does not express, plus echoes the 25-result ceiling, putting it slightly above baseline.

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?

States a specific verb+resource: resolving a coin/token name or ticker to its CoinGecko id, with concrete examples ("solana", "pepe", "usdc"). It also ties its output to the downstream consumer (/v1/crypto), which separates it cleanly from sibling tools like quote or search.

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

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

The description clearly frames this as an id-resolution step for /v1/crypto, giving a concrete condition for use. It does not, however, name an alternative sibling (e.g., a generic search tool) or state a when-not case, so it stops short of full routing 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?

Beyond the readOnly/idempotent/openWorld annotations, it discloses interval-range validity constraints, that the default interval depends on range, that dividends/splits and period return % are included, and the full payment model (x402 USDC on Base, $0.002 per successful call, unpaid call returns PaymentRequired). This is rich, non-obvious behavioral context.

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?

Front-loaded with the primary use case and tightly packed with no filler, though it is a single dense paragraph mixing returns, constraints, and billing; a light structural split would improve scanability.

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 carries the return-shape burden and does so (OHLCV+adj close+volume bars, period return %, high/low, dividends/splits). Validity constraints, defaults, and the payment/auth path are all covered, so an agent has everything needed 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 coverage is already 100%, but the description adds meaning the schema lacks: the combinatorial constraint that 5m-30m intervals only work up to 1mo and 1h only up to 2y, plus 'limit' keeping the most recent bars. That is genuine added value over the enum/default documentation.

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?

States a specific verb+resource: returns OHLCV bars (open/high/low/close/adjusted close/volume) for one ticker over a range at an interval. It is clearly distinguishable from siblings like quote/quotes (current price) and crypto_search/search (lookup), so an agent can select it without opening the schema.

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?

Opens with concrete use cases ('charts, backtests, returns and volatility') and gives scoping rules (one ticker, intraday limits). It does not, however, explicitly name an alternative such as quote for a single snapshot or state when-not to use it, so it stops short of full routing 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?

Goes well beyond the readOnly/openWorld/idempotent annotations: it discloses that data may be delayed, that the tool is paid via x402 USDC on Base at $0.002 per successful call, and that an unpaid call returns a PaymentRequired object. Payment and latency behavior are exactly the traits annotations cannot express.

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?

Front-loaded with the use case, then return fields, then the search-first caveat, then pricing — a sound ordering with no filler sentences. The inline ticker catalog is long and partly duplicates the schema examples, slightly diluting density.

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 carries the return-shape burden and does so fully: price, previous close, change (absolute and percent), day high/low, volume, 52-week range, exchange, currency, instrument type, market time and a source link. Combined with the payment and delay notes, an agent has everything it needs to call and interpret this 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 already 100%, so the baseline is 3. The description adds value by demonstrating the breadth of accepted symbol formats across asset classes and venues (7203.T for Tokyo, VOW3.DE for Xetra, ^GSPC, EURUSD=X, GC=F), though it largely overlaps the schema's own 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?

States a precise verb+resource — 'latest market price of a listed instrument' — and enumerates the instrument classes (stock, ETF, index, FX, crypto) it covers. It is clearly distinguishable from siblings like history and search, which the description itself routes away from.

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?

Opens with an explicit trigger ('Use when an agent needs the latest market price'), and names an alternative workflow: 'Use /v1/search first if you only know the company name.' Together these tell the agent both when to use this tool and when to use another one first.

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?

Goes well beyond the readOnly/idempotent/openWorld annotations: partial-failure semantics (unknown symbols go to 'notFound' rather than failing the call), billing semantics (charged only if at least one symbol resolves), and the exact payment rail and price (x402 USDC on Base, $0.002 per successful call). This is exactly the pre-call context an agent needs.

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?

Front-loads the purpose and the batch limit, then layers failure, billing, and payment behavior in tight sentences. Dense but nearly every clause carries operational weight; only the payment specifics could be trimmed slightly.

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 usefully characterizes the return ('same fields as /v1/quote', plus a 'notFound' list) and the payment handshake. The residual gap is that an agent must already know what /v1/quote's fields are, which the description externalizes rather than explains.

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% on the single 'symbols' param, so the baseline is 3, and the description adds real value on top: the Yahoo-style format and a mixed-asset example ('AAPL,MSFT,NVDA,SPY,BTC-USD') that clarifies equity vs crypto ticker syntax.

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?

States a specific verb (price) and resource (a watchlist/portfolio) plus batch scope ('up to 10 comma-separated tickers'). It references '/v1/quote' as the single-symbol equivalent, which helps distinguish it from the sibling 'quote' tool, though it never explicitly routes the agent to 'quote' for single tickers.

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?

Gives a clear when-to-use condition ('price a watchlist or portfolio in one paid call') and explains the payment precondition, including how to obtain the PaymentRequired object. It lacks an explicit 'use X instead' for the single-ticker case, but the batch framing makes the boundary inferable.

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?

Annotations only cover the read-only/idempotent/open-world safety profile; the description goes well beyond them by disclosing the paid-call mechanic (x402 USDC on Base, $0.002 per successful call) and the exact behavior of an unpaid call. It also caps behavior at 20 results and enumerates the returned fields, which is meaningful context for a tool with no output schema.

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?

Purpose and workflow position are front-loaded in the first clause, followed by examples, return shape, and cost. Every sentence carries distinct information — routing, examples, output fields, billing — with no restatement of the title or name.

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 carries the burden of describing returns and does so (match count, symbol, names, quote type enum, exchange, sector, industry). Combined with the cost/payment disclosure and routing guidance, an agent has everything needed to call this correctly and interpret the 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 100%, so both parameters are already documented and the baseline is 3. The description adds real value on top by showing the normalizations 'q' accepts (common name, index name, non-US ticker, crypto pair) and by clarifying the result ceiling that 'limit' operates within. It does not, however, explain the string-typed limit or default of 8 beyond what the schema says.

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 names a specific verb+resource (resolve a name to a tradable ticker) and immediately grounds it in concrete input→output examples ("apple" -> AAPL, "s&p 500" -> ^GSPC, "bitcoin" -> BTC-USD). It also names the downstream tools it feeds (/v1/quote, /v1/history), so an agent can place it in a workflow without opening the schema. Overlap with the crypto_search sibling is not addressed, but the stated return types and examples make the scope clear.

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 gives explicit sequencing guidance: use this to resolve a name "before calling /v1/quote or /v1/history," which routes the agent away from those siblings. It also tells the agent what happens if it calls without payment (a PaymentRequired object), which is a usage precondition spelled out rather than inferred.

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