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 a real behavioral trait the schema cannot: the tool auto-handles an HTTP 402 microtransaction of 0.080 USDC on Base, i.e., it is a paid operation. It also states the return shape (credibility score 0-100 plus risk signals). It omits failure/payment-failure behavior and rate limits, so it is informative but not complete.

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

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

Three sentences, front-loaded with what the tool does, followed by what it returns and then the payment caveat. No filler sentences, though the third sentence could be tightened. Structure is clean and scannable.

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 must carry the load. It covers purpose, return shape, and payment handling, but leaves the actual content of 'risk signals,' the failure mode when payment fails, and interaction with contract_address unspecified. Adequate but with clear 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 description coverage is 100%, so both 'url' and 'contract_address' are already documented as the URL to audit and an optional EVM address verified alongside it. The description adds nothing parameter-level 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 a specific verb (audits/analyzes) and resource (website or smart contract landing page), and specifies the analysis dimensions: security, credibility, and phishing risk. It clearly distinguishes the tool from a generic scrape/search, though it never names a sibling. The purpose is unambiguous without opening the schema.

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

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

It says the tool works 'for any website or smart contract landing page,' which implies a use case, but there is no explicit when-to-use versus alternatives (e.g., clean_web_scrape or clean_web_search) and no exclusions or prerequisites. An agent is left to infer that this is the risk-assessment path rather than the content-retrieval path.

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 a non-obvious trait: automatic HTTP 402 microtransaction handling at 0.005 USDC on Base, i.e. this call can incur cost. It leaves out rate limits, JS-rendering behavior, and failure modes for blocked or dynamic pages, so it is good but not complete.

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: the purpose and output contract come first, and the payment 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?

For a single-parameter, no-output-schema tool, the description covers purpose, return format, and cost behavior adequately. It stops short of describing how the tool behaves on pages requiring JS, login, or anti-bot measures, which matters for a scraper.

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 a single well-documented url parameter, so the schema does the heavy lifting and the baseline is 3. The description adds no format or constraint detail (e.g. handling redirects or non-HTML content) 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 (scrapes) and resource (any public webpage), plus the output form (clean, sanitized, token-efficient Markdown for LLM ingestion). This clearly separates it from siblings like clean_web_search or synthesize_web_digest, though no sibling is named 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?

The description never says when to pick this over clean_web_search or synthesize_web_digest, nor what prerequisites exist. The only implicit guidance is the 'public webpage' scope constraint, which mildly excludes authenticated/private pages but is not framed as usage 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 full behavioral burden. It does disclose a genuinely non-obvious trait: automatic handling of HTTP 402 microtransactions at 0.05 USDC on Base, which tells the agent a cost/payment flow exists. It omits rate limits, whether the operation is read-only, and any failure behavior beyond the 402 case.

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; the core capability is front-loaded and the payment detail follows. Slightly short of a 5 only because the second sentence is a cost side-note rather than routing or scoping 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 two-parameter tool with no output schema and no annotations, the description covers purpose and payment mechanics but says nothing about result volume, latency, or how summaries are structured. Adequate but with clear gaps around usage and behavior.

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

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

Schema description coverage is 100%, so both parameters (query, limit) are already fully documented in the schema. The description adds no syntax, format, or default information beyond it, 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 and resource ('deep web research across multiple sources') and names the output form ('clean Markdown summaries from top results'). It does not, however, distinguish itself from close siblings like clean_web_scrape or synthesize_web_digest, leaving the agent to infer the difference.

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 or when-not-to-use guidance, no prerequisites, and no mention of alternatives despite four plausible siblings. The agent must guess whether this or clean_web_scrape is appropriate for a given task.

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 add genuine behavioral context: the underlying Edge LLM (Llama 3), and notably an automatic HTTP 402 microtransaction of 0.025 USDC on Base, which tells the agent this call has a real monetary cost. However, it omits auth requirements, failure/retry behavior, latency, and rate limits, so the disclosure 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?

Two tight sentences with the core action front-loaded and the payment caveat second. Nothing is wasted, though the payment sentence is dense enough that the cost detail could be more clearly flagged.

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 2-parameter tool with no output schema and no annotations, the description compensates well by naming the return artifacts (summary, takeaways, entities) and disclosing the microtransaction cost. It leaves some operational gaps (auth, failure handling) but is broadly adequate to call the tool 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 description coverage is 100%, so both 'url' and 'focus' are already documented in the schema. The description adds no syntax, format, or constraint detail beyond what the schema provides, 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+resource chain (scrape webpage, run LLM synthesis) and enumerates the concrete outputs (executive summary, key takeaways, structured entities). This distinguishes it in spirit from a plain scrape sibling, but it never names clean_web_scrape or otherwise explicitly differentiates itself from the sibling set.

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 guidance and no mention of alternatives such as clean_web_scrape. Usage is only inferable from the fact that this is the 'synthesis' variant, which is weak 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?

With no annotations, the description carries the full disclosure burden. It usefully reveals the payment behavior (automatic HTTP 402 handling, 0.03 USDC on Base), which is critical for an agent that will incur per-call cost, but omits rate limits, failure/refund behavior, and whether the charge applies per invocation.

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 that front-load what is extracted before the cost/payment caveat. The '$100/mo API fee' framing is mildly promotional but is genuinely informative about why the tool exists.

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 adequately names the return contents (bio and recent tweets) and the cost model. It would be stronger with the count/format of returned tweets and error behavior.

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 is documented with an example handle, so the description need not restate it. The description adds no syntax, normalization, or accepted-format guidance beyond the schema's own example.

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 (Extracts) and resource (public Twitter/X profile bio and recent tweets) scoped to 'any username'. This distinguishes it implicitly from the sibling twitter_search, which is query-oriented rather than per-handle, though no sibling is named 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?

Usage is only implied: the 'for any username' framing suggests per-handle lookup versus a search tool, but there is no explicit when-to-use, when-not-to-use, or named alternative among the siblings. An agent must infer the routing from the phrase 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 a genuinely non-obvious trait: automatic HTTP 402 microtransactions at 0.05 USDC on Base. However, it omits auth/wallet prerequisites, rate limits, failure behavior when payment fails, and pagination or result volume, so significant behavioral 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 tight sentences with the capability statement front-loaded and the payment mechanism second. 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?

The tool is simple (2 params, no nesting, no enums), and the description covers purpose and cost behavior. Since there is no output schema, the description should have described the return shape (tweets, sentiment fields, counts), and it also omits wallet/auth prerequisites for the paid path.

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 query and limit are already fully documented in the schema; this sets the baseline at 3. The description only reinforces that cashtags (e.g. $BTC, $BASE) are valid query forms and adds nothing about the limit parameter.

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 ('Searches') and resource ('public tweets, cashtags, and sentiment across Twitter/X'), which cleanly separates it from the sibling twitter_profile_lookup (profile-centric) and the web-scraping siblings. An agent can route between search and profile lookup without opening either 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?

No when/when-not guidance and no mention of the sibling alternatives such as twitter_profile_lookup. The '$100/mo API fee' line implies a motivation for using this tool but does not tell the agent in which situations it should be preferred over other tools.

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