Landfall

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

Annotations already cover the safety profile (readOnly, openWorld, idempotent), and the description layers on genuinely new operational facts: a 0.05 USDC cost per completed call, automatic x402 payment, and — critically — that failed calls are never charged. That cost/charging behavior is exactly the kind of trait structured fields cannot express.

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

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

Front-loaded with purpose and return shape, then pricing. The middle enumeration of return values is long but each item is informative. No filler sentences, though the output list could be tightened.

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

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

With no output schema, the description correctly carries the return contract (0-100 score, verdict values, tag detection, conversion paths, top 5 fixes), so an agent knows what it gets. It also covers cost and refund behavior. Minor gaps remain around latency/pagination, but the essential contract is present.

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

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

Schema description coverage is 100% and both parameters (url, keyword) are already documented in the schema. The description adds no syntax, format, or interpretation detail for either parameter, 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 and resource ("Audit a landing page") plus a concrete scope ("before sending paid ad traffic"). It does not name or distinguish itself from the close siblings preview_landing_page or sample_audit, so an agent must 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?

Gives a clear usage trigger — run it before spending on paid traffic — which tells the agent when this tool is relevant. It offers no exclusions or explicit routing to alternatives such as preview_landing_page or sample_audit, which would be valuable given the sibling set.

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

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety and idempotency are covered. The description goes beyond them with substantive commercial behavior: 0.01 USDC per completed call, automatic x402 payment if the client supports it, and explicitly no charge on failure. It does not mention rate limits, auth prerequisites, or latency, keeping it out of the 5 range.

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

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

Front-loaded with the primary action and its return contents, then the pricing terms, with no filler sentences. The detection enumeration is long but every item is load-bearing scope information. Only minor tightening is possible.

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, so the description must convey return contents, and it does so concretely (pixel names with IDs, CMS platform, consent tools). The cost/payment mechanic is also disclosed. A little more on response shape or failure modes would be needed for a 5.

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

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

There is a single parameter with 100% schema description coverage ('Public http(s) URL of the page or website'), so the schema already carries the semantics. The description adds nothing about the url argument — no accepted forms, trailing-path behavior, or redirect handling — 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 a specific verb ('Check') and resource (a website's ad pixels/analytics), then enumerates exactly what is detected: Meta Pixel, Google Ads, TikTok, GA4, tag managers, consent tools, CMS platform, booking/chat tools. That is far more precise than a tautology. It does not, however, differentiate itself from the nearby audit_landing_page or sample_audit siblings, so it stops short of a 5.

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

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

Usage is implied by the scope list — an agent can infer it should call this when it needs pixel/tag detection for a given URL. But there is no explicit when-to-use, no when-not-to-use, and no mention of how this differs from audit_landing_page or preview_landing_page, which appear to overlap topically.

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

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

Annotations cover safety (readOnly, idempotent, openWorld), and the description adds substantial non-obvious behavior: an explicit price of 0.02 USDC per completed call, automatic x402 payment, a guarantee of no charge on failure, and the two-page crawl strategy. These cost/billing and crawl-scope details are exactly the kind of context an agent cannot get from structured fields.

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

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

Front-loaded with the extraction purpose and field list, then crawl behavior, provenance, and pricing in tight successive sentences. Every sentence carries distinct information with no padding.

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

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

With no output schema, the description compensates by enumerating the returned fields and disclosing the billing model and failure behavior. An agent has everything needed to decide to call it and understand the cost implications.

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

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

There is one parameter with 100% schema description coverage ('Public http(s) URL of the page or website'), so the schema already fully documents it. The description adds no format or constraint detail about the URL beyond what the schema states, 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 (Extract) and resource (contact and business details from a company website) and enumerates the exact fields returned. This clearly distinguishes it from siblings like audit_landing_page, check_tracking, and preview_landing_page, which are analysis/preview tools rather than data extraction.

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 explains internal scope (reads homepage plus contact page when the homepage lacks a phone or email), which implies when it is appropriate, but it never states when to prefer this over the sibling audit/preview tools or any exclusions. Usage is implied rather than explicitly routed.

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

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds real value beyond them: the rate limit ('Limited per hour') and the shape of the result (verdict tiers, score range, issue counts, top blocker). It does not say what happens on an unreachable URL or how the limit is enforced.

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

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

Two tight sentences, front-loaded with what the tool returns before the routing hint and the rate-limit caveat. No filler and nothing redundant with the schema.

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

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

There is no output schema, so the description correctly spends words summarizing the return payload (verdict, score, counts, blocker) plus the throttling constraint. Combined with full schema coverage and read-only annotations, an agent has everything needed to call this 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?

The single url parameter is fully documented in the schema (100% coverage, with format example), so the schema carries the parameter burden. The description adds no additional syntax, constraint, or example for url; baseline 3 applies when schema coverage is high.

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 (preview/quick check), resource (landing page), and the concrete payload the caller gets: verdict, 0-100 score, issue counts, top blocker. It clearly distinguishes itself from audit_landing_page as the lightweight version.

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?

Explicitly names the alternative (audit_landing_page) and the condition that selects it ('for the evidence and fixes'), so an agent knows this tool is the fast triage call and the sibling is the deep-dive. It also flags the per-hour limit, which shapes call-frequency decisions.

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

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

Annotations already cover the safety profile (readOnly, idempotent, closed-world). The description adds genuinely useful context beyond them: the returned data is synthetic and it mirrors the exact field set of the paid audit, which stops an agent from treating the output as a real audit result.

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

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

One sentence, front-loaded with the action and resource, with the two qualifiers (fictional page, full field parity with the paid audit) appended efficiently. Nothing is wasted.

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

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

With no output schema, the description's promise of 'every field the paid audit returns' is the main signal about the return value, which is adequate for a zero-argument sample tool. It could say more about format or size, but nothing needed to invoke it correctly is missing.

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

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

The tool takes zero parameters, so the baseline is 4. The description correctly implies no input is required by describing a canned sample, and there are no parameters for it to document.

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 (returns an example audit report) and adds the key qualifier that the page is fictional. It implicitly differentiates from audit_landing_page by being the sample/free variant, but never names the siblings, so an agent must infer the distinction from context rather than being told.

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

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

The word 'example' and 'fictional page' imply this is for inspecting the report shape rather than auditing a real page, but the description never states when to choose it over audit_landing_page or preview_landing_page. Usage is left to inference.

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