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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions 'using Workers AI' but does not clarify whether the operation is read-only, modifies input in place, returns new text, or how redaction is performed. This lack of safety and outcome details is a significant gap.

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

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

The description is a single, front-loaded sentence with no filler words. It conveys the essential action and scope efficiently, earning a maximum score for conciseness.

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 simplicity (one parameter, no output schema), the description is mostly sufficient but omits expected return behavior or side effects. It does not state whether the text is returned redacted or mutated in place, which is crucial for agent usage. The lack of annotations further reduces completeness, so a middle score is appropriate.

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 covers 100% of parameters, but its description ('Text content containing sensitive PII') is vague. The tool description adds concrete meaning by specifying which types of PII (SSN, phone, email, ZIP codes) are targeted, thereby enriching the parameter's semantic beyond the schema baseline.

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

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

The description clearly identifies the action (redact) and the target data (SSN, phone, email, ZIP codes), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools by naming alternatives or unique constraints, so it falls just 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?

No guidance is given on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description simply states what the tool does without contextualizing its appropriate use cases, leaving the agent without direction on tool selection.

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 disclosure burden. It correctly signals a read-only metadata check and describes what categories of information are returned, but says nothing about pagination, rate limits, permissions, or output format.

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 with no filler; the three deliverables are listed compactly and the read-check framing comes first.

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 usefully enumerates the return categories (coverage, supported pairs, date boundaries), which compensates for the missing output documentation. Only output shape/format details remain unspecified for this simple metadata lookup.

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 the single optional 'pair' parameter already documented in the schema (with an example). The description only implies that coverage can be scoped to pairs, adding no syntax or format detail beyond the schema, 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 specific verb ('Check') and enumerates concrete resources ('data coverage, supported pairs, and date boundaries'), making the tool's scope clear. It does not explicitly name or distinguish itself from sibling crypto tools like crypto_spread_candles or crypto_dislocations, which prevents a 5.

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

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

The description implies a discovery/pre-flight role (checking what data exists before querying), but never states when to use this versus the other crypto tools or when it should be skipped. Usage is inferred rather than instructed.

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. 'Fetch' implies a read, but it says nothing about whether results are historical vs. live, how events are thresholded, return shape, or pagination/rate limits.

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 naming the verb and resource with no filler. It is efficient, though terse enough to leave the behavioral gaps unfilled.

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 and no output schema, the description is the only place to explain what a 'dislocation event' contains and how the date/time slices interact. It leaves that entirely unexplained for a domain-specific analytical 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 date, pair, and time parameters are already documented in the schema. The description reinforces the token-pair scope but adds no format or default detail beyond what the schema provides, matching the baseline 3.

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') and a specific resource ('cross-venue market dislocation and spread arbitrage events') scoped to a token pair. It is distinguishable from siblings like crypto_spread_candles and crypto_impact_simulation, though it doesn't explicitly contrast itself with them.

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 crypto_spread_candles or dex_price_summary, and no stated preconditions or exclusions. Usage is only inferable from the name and the word 'events'.

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 but discloses almost nothing: it does not say whether the tool is read-only, whether it requires credentials/API keys to reach venues, whether it is rate-limited or slow, or what a benchmark run returns. 'Benchmark' implies a read, but that is inference, not 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?

A single front-loaded sentence with zero filler; the core action and the three measured quantities come first. Nothing redundant and nothing 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?

There is no output schema and no annotations, so the description should explain what a benchmark result looks like (per-venue latency figures, fill-rate metrics) and how it is scoped. It names the metrics but leaves the return shape and any execution caveats unstated, which is thin for a tool with no structured support.

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 date, time, and venue are fully documented in the schema itself, and the description adds no format or semantics beyond it. Baseline 3 applies since 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 gives a specific verb ('Benchmark') and three named outputs (cross-venue execution speed, venue latencies, fill rates), which is enough to distinguish it from siblings like crypto_dislocations or crypto_impact_simulation. It stops short of stating scope boundaries (e.g. which venues, live vs historical), so it is clear but not fully differentiated.

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 prerequisites, and no reference to any sibling tool. An agent must infer that this is a read-only analytical benchmark run over a date/time slice, with nothing telling it when this tool beats crypto_impact_simulation or the other crypto 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 and discharges the most important risk: it explicitly says 'Read-only PAPER simulation — no order is placed' and that it runs against the live L2 book. It does not mention permissions, rate limits, or staleness of book data, so it is not fully transparent.

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

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

Two sentences, both load-bearing: the first front-loads purpose and outputs, the second immediately resolves the obvious safety question about order placement. 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?

There is no output schema, so the description correctly compensates by enumerating the returned fields. Combined with the no-side-effect statement, an agent has enough to call it correctly; minor gaps remain around error behavior and whether the simulation models market impact of the order itself.

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 pair, side, size_usd and size_base semantics are already documented in the schema. The description restates order-sizing concepts ('fillable size') but adds no syntax or constraint detail beyond what the schema provides, which is the baseline case for a 3.

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 ('pre-trade impact simulation against the live L2 book') and enumerates the exact metrics produced (VWAP fill price, slippage in bps, fillable size, fill probability). An agent immediately knows what it gets back, though no sibling (e.g. dex_price_summary) is named for contrast.

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?

'Pre-trade' establishes the decision context in which this tool belongs, and the second sentence makes clear it is a simulation only, with no order placed. It gives no explicit exclusions or alternative tools for cases where only a static price is needed, 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?

With no annotations, the description carries the full behavioral burden. It does disclose the data source (cross-venue CEX-DEX) and output shape (OHLC candles), which is useful context, but it omits any mention of read-only safety, authentication needs, rate limits, or pagination 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?

A single, front-loaded sentence with zero filler. The core resource and scope appear immediately, and 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?

For a simple fetch tool with fully documented parameters, the description is adequate. However, with no output schema it should say more about the return values (e.g., candle granularity, aggregation across venues, timestamp alignment) to be fully self-contained.

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 all four parameters are individually documented, so the baseline is 3. The description adds only the token-pair scoping, repeating what the schema already states, and provides no additional semantics for date, time, or interval.

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) and a precisely defined resource (cross-venue CEX-DEX spread candles in OHLC format) scoped to a token pair. It is clear enough that an agent knows what it returns, but it does not explicitly differentiate itself from adjacent siblings like dex_price_summary or crypto_dislocations.

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 never states when to use this tool versus alternatives, nor does it mention prerequisites, time-range limitations, or when-not to call it. Usage can be inferred from the purpose, but no explicit guidance is provided.

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 of behavioral disclosure. It states that the tool fetches real-time data points, implying a read-only operation, but it does not mention potential limitations, such as the ambiguity of token symbols or whether an exact contract address is required. Some details are missing but the core behavior is conveyed.

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

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

The description is a single, concise sentence that lists the tool's primary outputs without any redundancy. It is front-loaded and immediately comprehensible, earning a high score for structure.

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

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

The tool is simple with one parameter and no output schema. The description lists the intended outputs (price, volume, liquidity, pair stats), which gives a sufficient overview of what the tool returns. It lacks details on response structure or error handling, but for this level of complexity it is reasonably 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?

The input schema provides full coverage for the single parameter 'query' with the description 'Token symbol or contract address.' The tool description adds no additional meaning beyond what the schema already states, so the baseline 3 is appropriate.

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

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

The description uses the specific verb 'Fetch' and clearly identifies the resource: real-time DEX price, 24h volume, liquidity, and top pair stats across chains. It effectively distinguishes this tool from the unrelated sibling tools by focusing on DEX market data.

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

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

No explicit usage guidance is provided, such as when to use this tool versus alternatives. However, the purpose is clear enough that the usage is implied: when a user needs DEX token metrics. Since there are no closely related sibling tools, the lack of exclusions is acceptable.

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

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

No annotations are provided, so the description must carry full behavioral burden. It discloses that the tool performs a query (read-only) and explains the data source (RDAP) and edge execution, but omits details such as return format, potential errors, or whether the data is live or cached. This is adequate but not rich.

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, tightly worded sentence with no filler words. It is front-loaded with the verb and resource, making it immediately scannable and 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 simple tool with one parameter and no output schema, the description provides sufficient context: it states what it does, what data source it uses, and what information is returned (availability and WHOIS status). A slightly more detailed explanation of the output format would push it to a 5, but it is complete enough for this simplicity level.

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 input schema already provides 100% coverage for the only parameter, domain, with a clear example. The description adds no extra meaning to the parameter itself beyond the schema, only explaining the overall query scope. Thus, it meets the baseline but does not exceed it.

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

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

The description uses a specific verb "Query" and identifies the resource "global RDAP registry" along with the intended outcome "domain availability and WHOIS status." This clearly distinguishes the tool from its unrelated siblings and fully clarifies its purpose.

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 a clear usage context: it is for looking up domain registration data via RDAP. While no explicit alternatives or exclusions are listed, the sibling tools are entirely unrelated, so no points are deducted for missing comparative 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 primary behavior (extracting text and tables) and the underlying model (Llama 3.2 via Workers AI), which gives some context. However, it does not mention limitations, failure modes, or output structure beyond 'clean text and table markdown', so transparency is partial.

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 with a clear verb and object. Every word is informative, and there is no wasted text.

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

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

The tool is simple with one parameter and no output schema, so the description should explain return values more fully. It mentions text and table markdown but not the exact format or limitations. The name 'shrink' is also left unexplained, creating 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%, so baseline is 3. The description does not add extra parameter details beyond the schema's clear definition of 'imageUrl'. It does not compensate with additional context, so a 3 is appropriate.

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

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

The description clearly states the tool extracts clean text and table markdown from images, using a specific verb and resource. It distinguishes itself from sibling tools which focus on text, embeddings, or code, making its purpose unmistakable.

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 usage is implied by the description—it's for OCR on images—but no explicit 'when to use' or 'when not to use' is provided. There is no mention of alternatives or exclusions, so it lands at the 'implied usage' level.

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 'bypassing simple IP blocks' behavior, but omits critical details such as whether the operation is read-only, potential rate limits, legal/ethical implications, or failure modes. This lack of transparency could lead an agent to misuse the 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?

The description is a single, concise sentence that front-loads the verb and includes the key qualifier. Every word earns its place, with no redundancy or fluff.

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

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

The tool is simple with one parameter, but with no output schema and no annotations, the description does not explain the return format or any prerequisites/constraints. The core purpose is clear, but an agent may need more information to invoke it confidently beyond a basic fetch.

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 already provides 100% coverage for the single parameter ('Target URL to fetch'). The description adds no further parameter meaning, so it meets the baseline for high schema coverage.

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

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

The description clearly identifies the action ('Fetch web pages') and the distinguishing characteristic ('from Cloudflare edge bypassing simple IP blocks'). It differentiates itself from sibling tools by specifying this niche, making it unambiguous what the tool does.

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

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

The description gives clear context for use: fetching web pages that are IP-blocked by Cloudflare. It does not explicitly state when not to use it or name alternatives, but the context is sufficient to infer appropriate usage, especially given no sibling performs a similar function.

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