Money Reactor

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

With no annotations, the description carries the full burden and does notable work: it discloses the price ($0.002), the payment rail (x402, USDC Base), the no-signup property, and the one-shot nature. It omits rate limits, failure behavior, and output shape, but the payment/auth context is genuinely useful disclosure.

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 tight sentences, front-loaded with the cost/payment model and capability, then the argument contract. Every clause carries information; nothing is padding.

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 4-param, no-annotation, no-output-schema tool it covers cost, model, invocation modes, and constraints adequately. It does not explain what a successful response looks like or what happens if neither prompt nor messages is supplied, which are the only meaningful 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 coverage is already 100%, so baseline is 3, and the description adds the non-obvious relationship that 'prompt' and 'messages' are alternative input modes rather than cumulative. 'optional system, max_tokens' reinforces the optionality already in 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?

States a specific verb+resource ('LLM chat completion') plus the exact model and provider (Llama 3.1 8B, Cloudflare Workers AI). It is unmistakably distinct from every sibling, all of which are crypto/market/data utilities.

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 notes the two input modes (prompt OR messages) and that it is 'one-shot AI inference per call, no signup,' which implies usage, but it never states when to prefer one mode over the other or when this tool is the right choice. No exclusions are given, and no sibling competes for the same job.

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 burden and does disclose the critical behavior: the call costs $0.001 via x402 on USDC Base. That is exactly the kind of non-obvious side effect an agent must know before invoking. It stops short of explaining what happens on an unpaid/failed payment (402 challenge) or per-call vs per-session charging.

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 front-loads price and protocol, then the output, then the use cases. No filler, and every clause (price, chain, UUID v4, idempotency keys, test target) carries 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?

For a zero-param, no-output-schema tool, the description covers cost, payment rail, output type, and typical uses. Remaining gaps are how the UUID is returned (raw text vs JSON field) and the payment handshake behavior on first call, which matter mildly for an x402 tool that could be misused.

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 has zero parameters and zero required fields, so there is nothing for the description to disambiguate. Baseline 4 applies; the description correctly implies a fire-and-forget call with no inputs.

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

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

States a concrete resource and output type: 'random UUID v4', plus the payment context. There is no UUID-generating sibling to confuse it with, so no explicit differentiation is required, though it never uses a clean verb like 'generate a UUID'.

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 concrete usage contexts ('idempotency keys and x402 requestKeys on demand', 'canonical $0.001 target for testing x402 payment stacks'), which is enough for an agent to know why it would pick this tool. No exclusions or when-not guidance, but there is no competing alternative in the sibling list.

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 behavioral burden and does disclose some traits: it is free, returns a limited set (top-3), and includes promotional content (honeypot sample, ROI pitch). But it omits auth requirements, rate limits, and any note on whether results are deterministic. Moderate context, notable gaps.

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 front-loaded sentence led by 'Free:' that wastes little space. The 'honeypot sample + ROI pitch' phrasing is somewhat jargon-heavy marketing shorthand, but the sentence is tight and 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?

With no annotations, no output schema, and no parameters, the description should fully describe the return. It gestures at the content but leaves 'honeypot sample' ambiguous and does not clarify the shape of the preview, so an agent knows the gist but not the details.

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 takes zero parameters, so there is no parameter meaning for the description to supply. Baseline 4 applies; the description neither helps nor hurts here.

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 the resource (bounties) and specifies the exact content returned: top-3 funded bounties, a honeypot sample, and an ROI pitch. It distinguishes itself from the sibling get_bounty_feed by framing itself as a free preview of that paid feed, so an agent can tell them apart without opening schemas. It lacks a clear verb, but the content scope is 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 word 'Free' and 'preview of the paid feed' imply this is the no-cost alternative to the sibling get_bounty_feed, which is usable routing information. However, it never explicitly states when to prefer this over the paid feed or what conditions/limits apply. Usage is implied rather than prescribed.

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 burden and does so well: it discloses the exact cost ($0.001), the payment rail (x402, USDC on Base), the required X-PAYMENT header, the 402 fallback when unpaid, the hourly refresh cadence, and the trust >= 50 filter. Rate limits and data freshness beyond 'hourly' are unstated, so it is not exhaustive.

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 key facts — paid, price, protocol — are front-loaded in the first clause, followed by data sources and then the payment mechanics in the last sentence. The middle clause is dense with enumerated sources but each detail (USDC/USDG, $500-$10k, trust scores) is informative rather than 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?

There are no annotations, no output schema, and no parameters, so the description must supply all invocation context. It covers the cost, auth flow, refresh cadence, sources, and filtering well; only the response shape/pagination behavior is left unspecified, which is a minor gap for a feed 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 tool takes zero parameters, so the schema has nothing to document and the description adds no parameter meaning because none is required. The baseline for a 0-param tool is 4, and nothing here contradicts that.

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 resource (multi-source bounty feed) and enumerates its sources — Superteam Earn listings, GitHub bounty radar, GitLab bounty projects — so an agent knows exactly what it returns. It does not explicitly contrast itself with the sibling get_bounty_demo, which is the one alternative an agent would plausibly confuse it with, so it stops short of 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?

Usage is implied: it is the paid/live feed, refreshed hourly, with a trust >= 50 filter. However, there is no explicit when-to-use guidance and no routing to or away from get_bounty_demo. The payment mechanics (X-PAYMENT header, 402 challenge) tell the agent how to invoke but not when to prefer this over 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?

With no annotations, the description carries the full burden and it delivers the single most important behavioral fact: the tool is paid ($0.001 via x402, USDC Base), which an agent must know before invoking. It also discloses the aggregation sources and the per-article return fields. It omits rate limits, refresh cadence, and failure/payment-error behavior, so it is not exhaustive.

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, zero waste, and the highest-value constraint (cost and payment rail) is front-loaded before the content description. The closing audience clause is mildly promotional but still conveys scope.

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 read tool with no output schema, the description covers what is returned (headlines, source links, publish times), where it comes from, and what it costs. The remaining gap is freshness/cadence and what happens on payment failure, which an agent would need to call it reliably.

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 takes zero parameters, so per the rubric the baseline is 4 and there is nothing for the description to disambiguate. The description correctly implies a parameterless call by describing a fixed daily digest rather than any filtering options.

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 (crypto headlines aggregated from Cointelegraph/Decrypt/NewsBTC RSS) and enumerates the payload (per-article source links and publish times), which clearly separates it from price/balance/market-pulse siblings. It never names a sibling explicitly, so differentiation is inferred from content rather than stated.

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?

"Daily brief for trading and research agents" implies the intended context, and the paid-news framing hints at when it is worth the cost. There is no explicit when-to-use vs. when-not guidance and no alternative tool is named for news-adjacent needs (e.g. get_market_pulse, get_crypto_price).

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 behavioral burden and does well: it discloses the payment requirement and mechanism (x402, USDC on Base), the data provenance (Coinbase public price APIs), and the edge-cache window (up to 30s). It stops short of describing failure/error behavior or latency expectations beyond caching.

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 with the cost, resource, examples, provenance, and caching front-loaded. Every clause earns its place, with no padding.

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 one-parameter, no-output-schema tool, this covers cost, source, and freshness, which is what an agent needs to decide and invoke. It lacks only explicit sibling discrimination and error-handling notes.

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% and the single symbol parameter is already documented as BASE-QUOTE with format guidance. The description reinforces the format via examples but adds little beyond what the schema already provides, 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?

Specific verb+resource: fetches a live crypto spot price in USD for a BASE-QUOTE pair, with concrete examples (BTC-USD/ETH-USD/SOL-USD). It is clear and unambiguous, though it never explicitly distinguishes itself from the sibling get_usd_price, leaving a minor routing question for an agent.

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 flags that the call is paid ($0.001 via x402/USDC Base), which is a meaningful usage consideration, but it never states when to use this over alternatives or any preconditions. Usage is only implied by the resource it fetches.

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 burden and does well: it discloses the cost and payment rail ('Paid $0.001 (x402, USDC Base)'), the read mechanism (public Base RPC eth_call balanceOf), and the return shape (raw + human balance, decimals, symbol). It stops short of failure modes, rate limits, or behavior for non-ERC20 contracts.

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: cost and payment rail first, then the operation, mechanism, and return values. Zero filler and nothing redundant.

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 two-parameter tool with no output schema, the description covers what is returned, how it is fetched, and that it costs money. Nothing essential for invoking it correctly is missing, though edge-case behavior (invalid token, non-ERC20 contract) is unaddressed.

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, and the description adds only indirect meaning ('any Base address' for the wallet, balanceOf implying the contract is an ERC20 token). No format, checksum, or validation details are added beyond 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?

States a precise verb+resource: 'on-chain ERC20 token balance for any Base address'. It also names the mechanism (eth_call balanceOf) and the chain (Base), which distinguishes it from price-oriented siblings such as get_crypto_price or get_usd_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 implicitly scopes usage by naming Base as the network and ERC20/token contract as the resource, so an agent can infer it must not be used for other chains or native-asset balances. However it never states when to prefer this over price or verdict siblings, and gives no exclusions or prerequisites beyond the implicit ones.

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 disclosure burden and does so for the most consequential trait: it is a paid call at $0.001 via x402/USDC Base, which an agent must know before invoking. It also states the return contents. It does not explain the payment handshake, failure behavior, or whether repeat calls are re-billed, which keeps it short of a 5.

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 front-loads the cost constraint before the data description — the right ordering for an agent deciding whether to spend money. Minor redundancy in 'today + yesterday + week ago + 10-day history', since the first three are contained in the last, costs it a point.

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 and no annotations, yet the description covers the cost, the returned data, and the scale interpretation, which is enough to call it correctly. Freshness/cadence and payment-failure behavior are the remaining unknowns, but they are secondary for a zero-arg read.

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 takes zero parameters, so per the baseline there is nothing for the description to disambiguate, and it correctly adds none. No misleading hints about optional filters are introduced.

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 concrete resource (crypto Fear & Greed index) and precisely enumerates the payload: today, yesterday, week-ago and 10-day history, with the 0-100 scale meaning. An agent can distinguish this from get_market_pulse or get_crypto_price purely from the text.

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?

'Market sentiment signal for trading agents' implies a use context but gives no explicit when-to-use/when-not guidance and never names an alternative among the many crypto siblings. The caller must infer that this is a sentiment read rather than a price or news tool.

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 burden and does disclose the critical trait: this is a paid call ($0.001, x402, USDC on Base), plus the data source (public RPC) and the return value (block height). It omits failure/retry behavior, cache/freshness, and rate limits, so it is strong but not exhaustive.

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 compact clauses, front-loaded with the cost — the first thing an agent must know before calling — followed by what is returned and how. No wasted sentences.

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, single-value tool with no output schema, the description covers cost, mechanism, and return type adequately. It leaves out edge behavior (payment failure handling, staleness) but nothing blocks a correct invocation.

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 takes zero parameters, so per the baseline there is nothing for the description to disambiguate. No parameter-level meaning is needed or missing.

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 ('get latest ... block height'), the chain (Base mainnet), and the underlying call (eth_blockNumber via public RPC). This clearly separates it from siblings like get_crypto_price, get_erc20_balance, or get_time, which all return 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?

'Cheapest chain-tip probe for agents' frames the intended use case — fetching the chain tip cheaply. It gives clear usage context but names no explicit alternative or when-not condition, so an agent must infer that alternatives would be a costlier or differently-scoped probe.

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, and it does disclose a major trait: the tool is paid via x402 in USDC on Base, plus that it batches three data sources. It does not cover rate limits, payment-failure behavior, or response shape/error modes, leaving meaningful behavioral gaps for a no-annotation 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?

Front-loaded with the most decision-relevant fact (it costs money), then the value proposition, then details. It is dense but every clause adds signal; the 'ONE call' / 'One poll replaces three calls' phrasing is slightly redundant but deliberately emphasizes the aggregation benefit.

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 and no annotations, the description still names the three data components returned and the default symbols, which is enough for an agent to decide and invoke. It could be more complete on payment mechanics and failure behavior, but the essential decision inputs are present.

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

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

Schema description coverage is 100%, so the baseline is 3, but the description earns credit by stating the default symbol set (BTC/ETH/SOL/XRP/DOGE) and clarifying that symbols is an optional batch override in BASE-QUOTE format — meaning beyond the schema's terse 'Comma-separated pairs BASE-QUOTE (optional)'.

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 ('full market snapshot') and enumerates exactly what it composes: batch USD prices, Fear & Greed sentiment, and latest Base block. It explicitly distinguishes itself from siblings by noting it replaces three calls, so an agent can tell it apart from get_crypto_price, get_fear_greed, and get_latest_block without opening any 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?

'One poll replaces three calls; ideal for monitoring loops' gives clear context for when to reach for this over the individual siblings. The paid framing ($0.003) implicitly signals when not to use it (single one-off lookups), but no explicit exclusion is stated, so it stops short of a 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 behavioral burden, and it discloses the non-obvious traits: this is a paid call ($0.001 via x402, USDC Base) and returns ISO-8601 UTC with unix seconds. It does not state whether the charge applies per call or what happens on payment failure, leaving a small 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?

Two compact sentences: cost first (the most decision-relevant fact for an agent paying per call), then return format, then positioning against alternatives. 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 tool with no output schema, the description supplies everything needed: the price/mechanism of access, the exact return format, and the intended use case. Nothing required to call it correctly is missing.

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 takes zero parameters, which sets the baseline at 4 per the rubric. There is nothing further the description could meaningfully add about inputs.

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

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

Names a specific verb+resource (get_time) and immediately specifies the payload: current server time in UTC ISO-8601 plus unix seconds. The trailing 'cheapest liveness/time probe' distinguishes it from other status-style siblings like reactor_status.

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?

'Cheapest liveness/time probe' gives a clear usage context (liveness checks, time retrieval) and implicitly ranks it against alternative probes via 'cheapest'. It stops short of an explicit 'when not to use' or naming the alternative tool, so it is clear context rather than 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.01), payment method (x402, USDC Base), data source (DexScreener), and output structure (grade plus reasons). It does not explicitly state that the operation is read-only or list any rate limits, but the payment and data-source details are substantial 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?

The description is a single, front-loaded sentence that packs payment, purpose, output, and usage into one efficient statement with 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 the tool's complexity and the absence of an output schema, the description adequately explains what the agent will receive (grade plus reasons) and the factors considered. It stops short of detailing the return format, but the core information needed to call and interpret the tool is present.

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%, and the single parameter (address) is fully documented in the schema. The description adds no additional parameter constraints or format details, so the 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 names a specific resource (Base token onchain safety verdict) and a concrete output (grade GREEN/MID/YELLOW/RED), plus the data sources used. It is clearly distinguishable from all sibling tools, which cover prices, balances, news, repos, and generic utilities.

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 provides an explicit use case: 'Screen tokens before interacting.' This tells the agent when to invoke it, but it does not mention alternatives, prerequisites, or when not to use it.

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 burden and does disclose the critical behavioral fact that this is a paid call ($0.001 via x402/USDC on Base), plus the 25-pair cap and default behavior. It omits error handling, invalid-symbol behavior, and rate limits, leaving some gaps.

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 but front-loaded sentence: cost and capability lead, batching rationale trails. Every clause carries information, though the parenthetical symbol list makes it heavier than necessary and could have been left to 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 optional-parameter, annotation-free, no-output-schema tool, the description covers payment, batching limits, and defaults. The one notable omission is the shape of the returned price snapshot, which no output schema documents; otherwise an agent has what it needs 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 'symbols' is already documented as comma-separated BASE-QUOTE. The description adds meaning the schema does not: the maximum of 25 pairs and the default 10-major set when the parameter is omitted, which matters for an optional param.

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 ('multi-asset USD price snapshot in ONE call') with concrete scope: up to 25 pairs and the exact set of 10 default majors. It also implicitly separates itself from the per-pair sibling get_crypto_price by noting the batch advantage, so an agent can choose without opening schemas.

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 clear usage context — 'Batch beats per-pair calls for portfolio and dashboard agents' — which tells the agent when this tool wins. It does not explicitly name or exclude a sibling alternative (e.g. get_crypto_price), so guidance stops short of full when/when-not routing.

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 burden and does disclose the most consequential trait: a $0.002 charge settled via x402/USDC on Base, plus the upstream provider (Open-Meteo) and that city-name geocoding happens. It stops short of covering failure modes, rate limits, or caching behavior, but the payment/auth disclosure is genuinely valuable 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?

One dense sentence with the cost/mechanism front-loaded ahead of the capability and the return fields. Every clause earns its place and there is 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 one-parameter tool with no output schema, the description usefully enumerates the returned metrics and discloses the payment model, so an agent can call it correctly. The lack of any error or availability caveat is a minor residual 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 description coverage is 100% for the single 'city' parameter, so the schema already documents format and example. The description only adds that any city worldwide is accepted and that the value is geocoded, which is marginal but consistent with the baseline 3 for high-coverage schemas.

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 ('current weather for any city worldwide') and enumerates the returned fields (temperature, feels-like, humidity, wind, conditions). The weather domain is unmistakably distinct from every sibling (crypto, repo, time, chat tools), so no disambiguation is needed.

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?

Usage is only implied: 'current weather' signals this is not a forecast tool, and 'any city worldwide' signals scope. There is no explicit when-to-use, when-not-to-use, or named alternative, so the agent must infer intent from the adjective 'current' alone.

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 burden, and it does disclose real traits: 'Free' signals no cost/auth barrier and 'live' signals fresh data. It stops short of stating read-only safety, rate limits, or caching behavior, so it adds some but not rich 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?

Two short clauses, no padding, and the most important cue ('Call this first') is placed at the end where it is easily seen. 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?

With no output schema, the description compensates by enumerating the returned fields (base URL, health, prices, receiver wallet). For a zero-param, no-annotation status endpoint this is nearly complete, missing only freshness/latency details.

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 takes zero parameters, so per the rubric the baseline is 4. There is no parameter surface for the description to clarify or for the schema to cover.

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 the specific resources returned (Money Reactor base URL, health, prices, receiver wallet), which distinguishes it from every sibling tool. The action verb is only implicit ('status'), and 'Money Reactor' is undefined jargon, so it falls short of a crisp verb+resource statement.

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?

'Call this first' gives an explicit ordering directive that tells the agent when to invoke it relative to other tools. There is no stated when-not-to-use condition, but no sibling offers a comparable status endpoint, so the routing guidance is largely sufficient.

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 burden and does substantial work: it discloses the cost ($0.003, x402, USDC Base), the output cap (8000 chars), the cleanup behavior (scripts/styles stripped), and a security constraint (private/internal hosts blocked). It omits failure modes and rate-limit behavior, but this is far more behavioral context than most tools 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?

A single dense sentence with cost, capability, output contract, and safety constraint front-loaded; every clause earns its place and nothing is padded.

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 one-parameter tool with no output schema, the description covers capability, return format, size limit, price, and host restrictions. Only error/edge-case behavior is left unstated, a minor 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 description coverage is 100% and the single 'url' parameter is fully documented as an absolute http(s) URL. The description adds no syntax or format detail beyond the schema, so the baseline of 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?

States a specific verb (fetch), resource (any http(s) web page) and the exact shape of the output (clean plain text, title + visible body). No sibling tool does this, so it is immediately distinguishable from the rest of the list.

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 phrase 'Gives text-only agents web reading' supplies clear context for when the tool is appropriate, and the paid-price note signals the cost precondition. It stops short of naming alternatives or explicit when-not conditions, but no sibling overlaps its function.

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, and it does disclose the single most consequential trait: this is a paid call ($0.001 via x402, USDC Base), which an agent must know before spending. It also names the return shape (one-line verdict with three possible values). It omits error behavior for invalid repos and any latency or rate-limit context, keeping it short of a 5.

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, zero filler, with the payment cost and output format front-loaded before the positioning phrase. Every clause 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?

For a one-parameter paid tool with no output schema, the description covers the essentials: cost mechanism and output shape. However, it never explains what the three verdicts mean or how x402/USDC payment is actually settled, and it omits the sibling differentiation an agent needs given score_repo_trust exists.

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 is only one parameter and schema coverage is 100%, with the schema itself documenting the 'owner/name' format, so the baseline is 3. The description adds nothing beyond the schema about the repo argument.

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 verb and resource ('one-line GO / CAUTION / HONEYPOT_RISK verdict for a repo') and even enumerates the output values, so an agent knows exactly what it produces. It does not, however, distinguish itself from the sibling score_repo_trust, which appears to operate on the same resource, leaving the boundary between them unstated.

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 phrase 'Impulse-priced pre-flight check' implies the usage context (a quick sanity check before acting on a repo), which is better than nothing. But there is no explicit when-not guidance and no pointer to the obvious alternative score_repo_trust, so an agent cannot confidently choose between them.

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 behavioral burden and does a good job: it discloses that the call costs $0.001 and requires x402/USDC-on-Base payment, which is critical pre-invocation context. It stops short of describing return format details (structured vs text) or any rate/error behavior.

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?

Compact single sentence that front-loads the pricing/payment requirement and then the output. The closing sales pitch ('one avoided rug pays for 1000 calls') is extraneous but brief enough not to crowd out the useful 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?

For a one-parameter tool with no output schema, the description covers the essentials an agent needs: cost/auth mechanism, return values (score, verdict, reasons), and intended use case. It is nearly complete; only sibling disambiguation and return-type detail are missing.

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 and schema description coverage is 100%, so the 'owner/name, e.g. facebook/react' format is already fully documented in the schema. The description adds no extra syntax or constraint beyond identifying the target as a GitHub repo, 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?

States a specific verb+resource: returns a trust score (0-100), a GO/CAUTION/HONEYPOT_RISK verdict, and reasons for a GitHub repo. The output shape makes the purpose unambiguous. It does not differentiate itself from the sibling repo_verdict, which is the only gap.

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?

Offers a concrete trigger ('screen bounties before working them') but no explicit when-not conditions and never names an alternative tool, notably the sibling repo_verdict. The guidance is present but incomplete for an agent choosing between near-identical repo-scoring siblings.

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