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

With no annotations, the description carries the full behavioral burden. It usefully discloses the price and chain (0.02 USDC on Base), but it does not state whether the tool only reads data, what permissions or payment flow are required, how fresh the data is, or what the response contains.

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 dense sentences with no filler: the analytical capabilities come first and the price/chain note second. Every phrase contributes 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 composite analytics tool with no annotations and no output schema, the description is thin. It lists data domains and cost but says nothing about return structure, coverage, limitations, or data freshness, leaving the agent under-informed about what to expect.

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 both parameters are fully documented in the schema. The description does not add syntax, defaults, or interpretation beyond the schema, 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 specific domains — CLOB orderbook imbalance, smart-money wallet tracking, and Limitless/Polymarket cross-venue arbitrage spreads — so the agent can infer the tool's analytical purpose. However, it does not explicitly distinguish itself from related siblings such as polymarket_top_whales or polymarket_alpha_divergence.

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 no guidance on when to use this tool versus alternatives, nor any preconditions or exclusions. The pricing line adds commercial context but does not help an agent choose between this and related Polymarket tools.

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

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

With no annotations, the description must carry the burden, and it does disclose two useful traits: the data is pre-screened against honeypots/malicious taxes/prompt injections, and the call costs 0.01 USDC. However it omits return format, ordering, how many pairs, and any rate limits, which are relevant for a pre-paid data-fetch 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?

Two short sentences, front-loading the data scope and then the cost, with zero redundant or filler text. 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?

There is no output schema and no annotations, so the description is the only contract. It covers what data and the price, but says nothing about the shape of the result (fields, count, ordering), leaving an agent partially informed for a paid data 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?

Only one parameter exists and the schema already documents it at 100% coverage ('Target blockchain network'). The description adds nothing about the chain parameter, so it sits at the baseline where the schema does the work.

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 identifies a specific resource ('Top trending Base DEX pairs') and a concrete scope ('Base'), so an agent knows exactly what data comes back. It does not need sibling differentiation here since no sibling tool overlaps this Base DEX-pair listing function.

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 states what the tool returns but gives no when-to-use guidance, no preconditions, and never points to alternatives among the many sibling tools. Usage is left entirely to inference.

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

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

With no annotations, the description carries full disclosure burden, and it does surface two useful facts: a payment cost (0.01 USDC on Base) and that outputs are pre-sanitized for agent execution. It omits whether the call is read-only, latency/rate-limit behavior, and the return shape, so it is only partially 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?

Two short sentences, front-loaded with the core capability followed by the payment terms. Every clause carries information, though the pricing sentence sits slightly awkwardly alongside the data description.

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 and no annotations, the description conveys the data domain and cost but does not describe the returned fields or ordering ('top' by what metric). Enough to call it, not enough to predict the response 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?

Schema coverage is 100% and the single 'asset' parameter is fully documented in the schema, setting the baseline at 3. The description's mention of 'stablecoin and ETH' loosely corresponds to the asset options but adds no new format or default semantics 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?

The description names a specific resource (top stablecoin and ETH APY yields) with a specific scope (live, on Base), so the agent understands what data comes back. The verb is implicit rather than stated ('retrieve/list'), which keeps it short of a 5, but the noun phrase is unambiguous and no sibling overlaps this DeFi-yield niche.

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?

There is no when-to-use vs when-not-to-use guidance and no named alternative. The phrase 'pre-sanitized for autonomous AI agent execution' hints at the intended caller but does not tell the agent in which situations it should reach for this tool versus the many sibling tools.

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

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

With no annotations, the description carries the full burden, but it does disclose two non-obvious traits: the paid x402 requirement (0.01 USDC on Base) and an 'injection-free' sanitization guarantee. It omits rate limits, caching/recency behavior, and what happens on payment failure, so the safety and cost profile is only partially covered.

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 with no filler, and the core resource is front-loaded ahead of the price disclosure. The price sentence is short but reads slightly like marketing copy rather than functional detail.

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

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

For a one-parameter read tool with no output schema, the description adequately states the return format (Markdown stories) and the payment precondition. It does not cover recency/ordering of 'top' stories or what happens with limit boundaries, leaving a modest 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 'limit' parameter is documented as 'Number of stories', so the baseline of 3 applies. The description adds no syntax, range, or ordering semantics beyond 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?

Names a specific resource (top HackerNews AI and autonomous agent stories) and the output form (clean LLM Markdown), which is more specific than a bare noun phrase. It does not distinguish itself from the overlapping sibling research_topic_news_scanner, which also surfaces topical news.

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?

There is no when-to-use guidance, no condition selecting this over research_topic_news_scanner or stealth_scrape_and_sanitize, and no mention of freshness or scope limits. The agent must infer applicability from the name 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. It does disclose a genuine behavioral trait beyond the schema — that the call costs 0.02 USDC on Base, implying x402 payment — which is valuable and non-obvious. However, it says nothing about read-only nature, latency/freshness, rate limits, which exchanges are covered, or response shape, leaving significant 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?

Two well-formed sentences with no padding: the capability is front-loaded and the cost disclosure is compactly appended. 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 data-oracle tool with no output schema and no annotations, the description should clarify return format or at least what a 'signal' contains. It conveys the domain and price but leaves the agent guessing about response structure and payment mechanics required to actually invoke it successfully.

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 single 'assets' parameter is fully documented in the schema, which itself gives the ['BTC','ETH','SOL'] example. The description's mention of BTC/ETH/SOL only mirrors that example, adding no syntax, defaulting, or scope detail (e.g., unsupported assets, case sensitivity) beyond the schema. Baseline 3 applies.

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

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

The description names a specific resource domain — cross-exchange perp funding rate skew, basis spread, and spot-futures arbitrage signals — for concrete assets (BTC/ETH/SOL). No sibling in the list covers perpetual funding/basis, so an agent can route here without schema inspection, though the phrasing lacks an explicit verb (e.g., 'fetch') and reads more like a product label than an action 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?

There is no when-to-use, when-not-to-use, or alternative guidance. The agent must infer from the arbitrage/signal framing that this is for funding-rate or basis analyses, and nothing tells it how this differs from siblings like polymarket_crypto_odds or defi_yield_radar.

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. It usefully discloses sanitization via CanaryGuard and the non-obvious cost (0.02 USDC on Base), but says nothing about whether it is a read-only scan, rate limits, latency, or what form the returned alpha takes.

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 with the core scanning behavior front-loaded and the cost stated compactly at the end. No filler, though the price clause could arguably live in separate metadata.

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, so the description must do more. It names the return concept but not its structure, and offers no differentiation from siblings, leaving the agent with gaps for a paid, sanitized-signal 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 description coverage is 100% with all three parameters documented in the schema, so the baseline is 3. The description adds no meaning about limit, category, or strict_mode beyond what the schema already states.

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 (Scans), resource (Polymarket CLOB orderbooks), the signals it detects (volume spikes, smart-money spread divergence), and the output artifact (CanaryGuard sanitized alpha). It is clear on its own, but does not distinguish itself from closely related siblings such as alpha_polymarket_whale_orderflow or polymarket_top_whales.

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

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

No guidance on when to prefer this tool over the Polymarket siblings, no prerequisites, and no exclusions. The only contextual note is a price, which is operational rather than a usage cue.

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, but it does add one genuinely useful behavioral fact: the call costs 0.01 USDC on Base, implying a paid x402 endpoint the agent must be funded for. It does not confirm read-only behavior, data freshness, or rate limits, and 'Sanitized' is left unexplained.

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 with no padding, and the resource scope leads before the pricing note. Slightly under-specified rather than verbose, so it lands just short of 5.

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 read tool with no output schema, the description gives the rough return content (spreads and liquidity depth in bps) and the access cost, which is the most critical operational fact. It still leaves the exact return shape ('spreads' of what), data freshness, and the meaning of 'sanitized' undefined.

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 single parameter already documents its allowed values (BTC, ETH, SOL) with a default. The description repeats the same asset list but adds no format, casing, or edge-case detail beyond the schema, 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?

Names the specific resource (Polymarket probability spreads and liquidity depth) and scopes it to BTC/ETH/SOL, so the agent knows it returns market-derived metrics rather than raw prices. It does not differentiate itself from sibling Polymarket tools like polymarket_alpha_divergence or polymarket_top_whales, leaving overlap ambiguous.

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?

There is no statement of when to use this tool versus the other Polymarket siblings, nor any prerequisite or exclusion. The only implicit usage cue is the asset scope, which is already in the schema.

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, but it does disclose two useful behavioral facts beyond the schema: the data is 'pre-sanitized with CanaryGuard' and costs 0.01 USDC on Base. It still omits return shape, rate/limit behavior, and whether it is a pure read.

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 tightly packed sentences with no filler; the core capability is front-loaded before the sanitization and pricing notes. Slightly jargon-dense but efficient.

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 read tool with no output schema the description is workable, but it leaves the return format, the meaning of 'CanaryGuard', and the overlap with the sibling whale-orderflow tool unaddressed, which are the details an agent needs to pick and use 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% and the single 'limit' parameter is fully documented in the schema ('Max whales to analyze'). The description adds no syntax, bounds, or meaning beyond that, so the 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 concrete data product: Polymarket whale orderbook imbalances and CLOB skew, with an explicit temporal scope ('right now'). However, it never distinguishes itself from the near-identical sibling alpha_polymarket_whale_orderflow, leaving the agent to guess which whale-flow tool to pick.

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?

Only 'right now' implies real-time use; there is no when-to-use guidance, no prerequisites, and no reference to the overlapping sibling tools. Given two whale-orderflow siblings exist, the absence of routing guidance is a real gap.

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 meaningful traits: determinism, a binary TRUST/BLOCK decision output, and a 0.01 USDC cost on Base (a payment prerequisite). It does not state read-only status, behavior on failure/timeout, latency, or what happens for the solana chain, so gaps remain.

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 that are front-loaded with the core capability, followed by the pricing constraint. Nothing is wasted, though the phrasing is dense jargon ('CanaryGuard injection scrubbing') that could be clearer.

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 gate tool with no output schema and no annotations, the description covers purpose, decision semantics, and cost but omits when to prefer it over security siblings, error/failure behavior, and the distinction between base and solana execution. It is minimally adequate rather than complete.

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

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

Schema description coverage is 100%, so all four parameters are already documented in the schema. The description mentions Base/on-chain context but adds no syntax, format, or default-override meaning beyond what the schema already provides, making the baseline 3 correct.

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+resource ('pre_trade_agent_gate' that returns TRUST or BLOCK) and enumerates its components (RPC liquidity, honeypot checks, injection scrubbing). It clearly conveys what the tool does, though it never names or contrasts itself against the several security siblings (security_prompt_firewall, security_x402_endpoint_verifier, security_attestation_bundle), leaving differentiation implicit.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative is named despite a crowded field of security-oriented siblings. Usage is only weakly implied by the word 'pre_trade' and the 'gate' framing, so an agent must infer the intended context.

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

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

No annotations are provided, so the description carries the burden. It does add genuine behavioral context: the tool costs 0.02 USDC on Base (a payable call, presumably x402) and includes an injection firewall, which matters for trust. It still omits latency, source count, failure behavior, and what the firewall actually blocks.

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 with the capability statement front-loaded and pricing last. Sizing is appropriate, though the jargon density slightly hurts immediate comprehension.

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 paid research tool with no output schema and no annotations, the description covers cost and security posture but leaves return shape, depth semantics, and source scope unexplained. Adequate minimum, but gaps remain for 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?

Schema description coverage is 100%, so the schema already documents both parameters, and 3 is the correct baseline. The description adds nothing about the 'depth' values (no enum, no enumeration of levels) or how 'topic' is scoped to an entity, so it does not improve on 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?

It conveys that this is a research tool producing a markdown dossier from multiple web sources, which distinguishes it loosely from siblings like research_topic_news_scanner and stealth_scrape_and_sanitize. But the core wording is buzzword-stacked ('stealth web synthesis', 'CanaryGuard injection firewall'), so the actual operation is inferred rather than stated with a clear verb+resource.

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

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

No guidance on when to use this versus the nearby research/news/scrape siblings, and no prerequisites or exclusions. The agent must guess whether 'comprehensive' research is warranted over research_topic_news_scanner.

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. It usefully discloses the cost and payment rail (0.02 USDC on Base) and implies filtering via "sanitized," and "real-time" sets a freshness expectation. It still omits rate limits, source/result caps, latency or failure behavior, and the shape of what comes back.

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 sentences, front-loaded with the capability and followed by the cost. No filler, no repetition of the tool 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?

For a one-parameter scanner with no output schema and no annotations, the description covers capability, sources, and pricing, which is the essential context. It stops short of describing what a result looks like or how results are bounded, leaving an agent unable to predict the return payload.

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 query parameter, so the baseline is 3. The description only restates the field's domain ("keyword or protocol") without adding syntax, format, or multi-term handling guidance 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 specific verb (scan) plus the resources covered (news, HackerNews, ArXiv) and the input domain (any keyword or protocol), so an agent can tell what it does without opening the schema. It partially differentiates from the overlapping sibling hackernews_ai_digest by claiming multiple sources, but never names or contrasts with that sibling explicitly.

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?

"For any target keyword or protocol" implies the trigger condition, so usage is inferable. However, there is no when-not-to-use guidance and no routing against close siblings like hackernews_ai_digest or research_deep_web_dossier, which matters in a sibling set this large.

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 behavioral burden. It does disclose a cost signal ('0.02 USDC on Base'), which is genuinely useful context, but it omits everything else: whether it is read-only, what auth/wallet it needs, how the three sub-checks are combined, and what the response looks like.

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 with the functional scope front-loaded and the price appended. Every clause carries information, though the price sentence could have been folded in more economically.

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 must be self-sufficient, yet it says nothing about the merged return format of a three-part bundle or the payment/auth mechanics implied by the USDC price. An agent cannot predict what it will receive or what a call requires.

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 three parameters are already documented. The description implicitly maps each parameter to one of the three checks but adds no syntax, format, or constraint 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?

The description names three concrete verification functions (prompt-safety, URL threat, token contract) and frames the tool as a bundle, which is more specific than a generic 'security check'. It does not differentiate from the sibling security_prompt_firewall, which likely overlaps on the prompt-safety portion, 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?

The only usage context is the vague phrase 'for autonomous AI agent workflows'. There is no when-to-use guidance, no exclusions, and no routing to alternatives like security_prompt_firewall or security_x402_endpoint_verifier that cover subsets of the same ground.

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 behavioral burden. It discloses determinism, ultra-fast performance, and a price of 0.01 USDC on Base, but omits what actually happens to the input (is it modified, flagged, or blocked?), what the return value is, and any auth requirements beyond payment.

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: the first front-loads the tool's purpose and key traits, the second states the price. Every sentence earns its place with no wasted words.

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

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

With no output schema and no annotations, the description should explain the return behavior, but it does not state what the scrubber returns or how results are communicated. For a security tool, this leaves a critical gap for an agent deciding whether and how to use it.

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

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

Schema coverage is 100% with one well-described parameter ('Raw text context to scrub for prompt injections'). The description adds no additional parameter meaning, so the baseline of 3 applies when the schema does the heavy lifting.

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 and function: a prompt-injection and wallet-drainer scrubber for agent context windows. It clearly distinguishes itself from most siblings like security_x402_endpoint_verifier or research tools, though it does not explicitly state the verb 'scrub' and overlaps somewhat with stealth_scrape_and_sanitize's sanitization scope.

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 'for agent context windows' implies the intended use case, but there is no explicit when-to-use, when-not-to-use, or comparison with alternatives such as stealth_scrape_and_sanitize or pre_trade_agent_gate. Usage is only implied, not guided.

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 behavioral burden. It usefully discloses that invoking the tool incurs a real cost (0.01 USDC on Base), which is material for an agent deciding whether to call it, but says nothing about network behavior, whether it is safe/read-only against the target, rate limits, or failure modes.

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 tightly written sentences with zero filler; the audit scope is front-loaded and the cost caveat follows. 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?

There is no output schema and no annotations, so the description is the only source of behavioral and return-value information — and it does not say what the audit returns (pass/fail verdict, risk flags, report structure) or how results should be interpreted. Adequate for triggering the tool, thin for using its result.

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 endpoint_url parameter, so the schema already carries the parameter meaning. The description adds nothing beyond 'target x402 endpoints' — no URL format, scheme, or example. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (audits) against a specific resource (x402 endpoints) and enumerates the exact checks performed: payTo wallet authenticity, pricing, challenge headers, and schema hijack risks. No sibling tool operates in the x402 verification space, so an agent can route to it unambiguously.

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 the use case (validate an x402 endpoint's legitimacy and price before transacting) but never states when to prefer this over alternatives or what preconditions apply. The cost disclosure (0.01 USDC on Base) is a useful invocation signal, but there is no explicit when/when-not 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?

With no annotations, the description carries the full burden. It usefully discloses the anti-bot bypass mechanism and the paid cost (0.015 USDC on Base), which is real operational context, but says nothing about failure modes, rate limits, what CanaryGuard actually strips/redacts, or payment preconditions beyond the price tag.

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, mechanism front-loaded and price last; nothing is wasted. Slightly telegraphic, with tool names dropped in without explanation, but well-sized for the 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?

No output schema exists, and the description only implicitly signals the return format ('LLM Markdown'). It omits error behavior for blocked or failed scrapes and what sanitization output looks like, leaving meaningful gaps for a paid, multi-stage 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 description coverage is 100%, so the three parameters are already documented. The description adds no syntax or effect detail beyond restating the pipeline stages (e.g. what strict_mode true/false produces), so the 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?

Names three specific actions (Cloudflare bypass via Scrapling, DOM-to-Markdown extraction, CanaryGuard sanitization) tied to a scrape-and-sanitize resource, so the agent knows exactly what pipeline runs. It does not name or contrast itself with the nearest sibling (research_deep_web_dossier), so it falls 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?

There is no statement of when to choose this over the sibling research/scraping tools, nor any exclusion or prerequisite (e.g. 'use for bot-protected pages; prefer X for plain HTTP'). Usage must be inferred from the mechanism described.

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