SiteAnalyzerFree™

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 output dimensions and flags the operation as FREE (a cost signal), but says nothing about whether the page is fetched live, auth/rate-limit requirements, or how failures on unreachable URLs are handled. The output disclosure is the main value add.

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 that leads with the FREE qualifier and then lists capabilities. Every item in the list is a distinct output, so nothing is wasted, though the run-on enumeration is slightly dense.

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 single-parameter read tool with no annotations and no output schema, the description adequately compensates by enumerating what is returned (word count, boilerplate split, reading time, readability, keyword density). Only edge-case behavior for invalid or unreachable URLs is left unspecified, which is minor here.

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 with 100% schema description coverage, so the schema already documents the url field fully. The description's phrase 'any webpage or domain' merely restates the schema's 'URL or domain name' without adding syntax, format, or constraint detail. Baseline 3 is 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 names a specific verb (Analyzes) and resource (webpage content), then enumerates the exact outputs: word count, article-vs-boilerplate split, reading time, readability, and keyword density. This is well differentiated from the DNS/SEO/hosting siblings by subject matter, though it never explicitly contrasts itself with run_full_seo_audit, which could overlap on content analysis.

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 the input domain ('for any webpage or domain') but gives no when-to-use guidance, no when-not-to-use, and no mention of alternatives such as run_full_seo_audit or run_quick_seo_checkup. The agent must infer that this is the content-metrics tool from the enumerated outputs 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 the pricing/payment model ($0.005 USD / x402) — genuinely useful behavioral context. However, it omits whether the check makes live requests, rate limits, or what the result looks like, 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?

One front-loaded sentence with no filler; the cost signal is appended compactly. Slightly list-dense, but every clause identifies a distinct check performed.

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 stops at naming the checks performed rather than indicating the return shape (pass/fail, scores, per-check detail). For a low-complexity single-parameter tool this is adequate but leaves the agent guessing about results.

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 ('Target domain name or URL (e.g. example.com)'), so the schema already carries the semantics. The description adds no format or normalization guidance beyond what the schema states, which is the baseline 3 case.

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 ('Checks') and enumerates the concrete resources inspected: robots.txt AI rules (GPTBot, ClaudeBot), llms.txt, sitemap access, and AI indexability. This is clearly distinguishable from siblings like check_url_status or check_noindex_status by content, though it never names or contrasts with those siblings.

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 says nothing about when to run this versus alternatives such as check_noindex_status or run_spider_view_scan, which overlap in the crawlability/AI-visibility space. No prerequisites, no when-not-to-use, no workflow context — the agent must infer usage entirely.

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, and it does disclose the cost (5 credits) — a genuinely useful trait not available elsewhere. It says nothing, however, about authentication/permission needs, whether the scan is read-only and non-mutating, how long it takes, or what the result 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?

A single front-loaded sentence enumerating the scan targets with the credit cost parenthetically appended. Every clause carries information; 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?

With no output schema and no annotations, the description should ideally indicate the shape of the result (per-platform findings, scores, or citations) and any failure modes. It covers input scope and cost adequately but leaves the return value entirely unspecified.

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 (domain, brand_name) are already documented in the schema. The description adds no parameter-level meaning — it does not explain how brand_name interacts with domain or when the cross-check is needed — 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?

The description pairs a specific verb ("Scans") with concrete resources: review platforms, Google Business Profile, local NAP directories, and AI brand citations. This scope is clearly distinct from all siblings (DNS, noindex, tech stack, WHOIS, SEO audits), though it never explicitly names or contrasts with an alternative.

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 SEO/DNS siblings, nor any prerequisites or exclusions. Usage is only implied by the tool name and scanned-source list.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'FREE' (a cost trait) and lists checks, but does not state that it is read-only, whether it requires authentication, any rate limits, or what the return format 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?

A single, front-loaded sentence with no wasted words. The 'FREE:' prefix is a useful cost signal, though slightly promotional; otherwise the structure is efficient 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?

For a simple read-only diagnostic tool with one fully documented parameter, the description adequately covers the scope of analysis. It does not explain the return format, but given the absence of an output schema and the tool's straightforward nature, it is nearly 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% for the single domain parameter, so the schema already documents the parameter fully. The description adds no additional parameter semantics, which is the baseline expectation when the schema is complete.

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 (Analyzes) and enumerates exactly what is checked: SSL certificate validity, HTTP security headers, SPF/DMARC email security, and DNS TTL records. This clearly distinguishes it from siblings like check_web_hosting, lookup_whois_and_domain_age, and the SEO audit tools.

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 provides no when-to-use guidance, no alternatives, and no prerequisites. It only says what the tool analyzes, leaving the agent to infer that it should be used for security/DNS diagnostics.

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 behavioral burden. It discloses the full scope of checks and the $0.003 USD / x402 cost, which is useful operational context, but says nothing about permissions, rate limits, or whether results include raw record data versus verdicts.

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 that lists the analysis scope and appends the price without filler. Every clause carries information.

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

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

For a one-parameter, read-only analysis tool with no output schema, the description gives an adequate picture of what is inspected and what it costs. It would be fully complete with a note on prerequisites (e.g., domain must be publicly resolvable) or the shape of the 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?

Only one parameter ('domain') exists and schema coverage is 100%, so the schema fully documents it. The description adds no syntax, format, or validation detail beyond the schema, 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?

States a specific verb ('Analyzes') and enumerates the resources examined (DNS zone records, SPF, DMARC, mail connectivity), so the agent knows this is an email-authentication-focused DNS check. It does not explicitly differentiate from close siblings like check_dns_and_headers or run_dns_snapshot_check, 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 description never states when to use this tool versus the many DNS-adjacent siblings, nor any prerequisites or exclusions. The only contextual note is a price, which is not 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?

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the four directive types it inspects and implies a read-only lookup, but says nothing about authentication, rate limits, or what the response contains for a hit vs a miss.

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 value proposition and immediately followed by the concrete detection list. Every clause earns its place; only the 'FREE'/'Instantly' marketing padding is marginal.

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 single-argument read-only check with no output schema, the description covers what is inspected but not what an agent gets back (boolean, directive list, headers). Adequate but leaves a real gap on result interpretation.

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 coverage, so the baseline is 3. The description's 'domain or URL' phrasing matches the schema's own 'Target domain or URL' text, adding essentially no new syntax or format guidance.

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 ('checks') and resource ('domain or URL') and enumerates exactly what is being detected: noindex, nofollow, X-Robots-Tag, robots.txt. This is far more specific than a tautology, though it never differentiates itself from siblings like check_dns_and_headers or run_full_seo_audit.

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 only markets the tool as 'FREE' and 'Instantly'; it gives no indication of when to reach for this versus run_quick_seo_checkup or run_full_seo_audit. No prerequisites, no exclusions, no alternatives named.

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 does contribute one real behavioral fact — the operation costs 1 credit — but says nothing about authentication, rate limits, whether the request is a safe read against the target, or how results are returned. For a tool with zero annotation coverage, that leaves most behavioral context unstated.

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 front-loaded sentence that names the capability and ends with the cost marker. No filler, no redundancy, and the most decision-relevant information (what it inspects) is 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 a single required parameter, no output schema, and no annotations, the description reasonably covers what the tool inspects and what it costs. However, it omits any output shape hint, usage context, or routing to the overlapping sibling tools, so it is adequate but not fully 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%, with the single 'domain' parameter already documented with a format example (e.g. example.com). The description adds no format syntax, URL-vs-host guidance, or constraints beyond what the schema provides, 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 ('Identifies') and enumerates concrete resources: web server, CMS platform, CDN, SSL certificate details, and security header configuration. That clearly separates it from sibling tools like check_brand_reputation or lookup_whois_and_domain_age, though it doesn't explicitly distinguish itself from the overlapping check_dns_and_headers and check_web_hosting.

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 statement of when to use this tool versus alternatives such as check_dns_and_headers or check_web_hosting, and no prerequisites. The only situational hint is the cost marker '(1 credit)', which touches on economics but not on selection criteria.

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, so the description carries the burden. It usefully discloses redirect-following, latency measurement, the returned final URL, and a per-call price ($0.001 USD / x402), which implies a paid x402 endpoint. However it omits timeout behavior, failure modes for unreachable hosts, and whether the payment/auth step is required before the call.

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 that front-loads the core action and packs the sub-behaviors plus cost without filler. Nothing extraneous.

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 no-annotation, no-output-schema tool, the description covers what it does and roughly what it returns, plus cost. It falls short on error/timeout semantics and the x402 payment requirement an agent must satisfy before invoking, which matters for a paid endpoint.

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?

Single required 'url' parameter with 100% schema description coverage, including an example. The description adds no extra semantics 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?

States a specific verb and resource (checks HTTP status code) plus concrete sub-behaviors (follows redirects, measures latency, returns final URL). This clearly distinguishes it from siblings like check_dns_and_headers or check_noindex_status, which cover adjacent but different concerns.

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-to-use guidance or exclusions. With siblings such as check_dns_and_headers, run_full_seo_audit, and detect_website_changes, the agent gets no signal about which URL-checking tool to pick or when this narrow check suffices.

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 supplied, so the description carries the full burden; it does disclose the exact categories of information returned, which implies a passive read-only lookup. It says nothing about auth requirements, rate limits, failure modes, or whether results are cached, leaving behavioral gaps for a tool with zero annotation coverage.

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 tightly written sentence with the value proposition ('FREE') front-loaded and the enumerated outputs following. No filler, though the 'FREE:' marketing token is not strictly necessary for tool selection.

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 usefully enumerates the returned data categories, which is the main thing an agent needs. However, it omits any usage context or sibling differentiation, so it is adequate but not fully 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?

There is a single parameter and schema coverage is 100%, so the schema already documents 'domain' fully with an example. The description adds no format, validation, or subdomain/protocol nuance beyond what the schema states, which is the expected baseline here.

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

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

States a specific verb ('Identifies') and a concrete resource set (web server type, hosting provider, IP, CDN, response headers) scoped to a domain. It is clearly distinguishable from lookup_whois_and_domain_age or run_full_seo_audit, though it overlaps partially with check_dns_and_headers without acknowledging that overlap.

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 signal is the 'FREE:' prefix, which hints at cost but says nothing about when to choose this over check_dns_and_headers or the SEO audit siblings. No prerequisites, exclusions, or alternative-routing guidance are given.

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 statefulness and a pay-per-call cost model ($0.005 USD / x402), which an agent must know before invoking. However, it omits failure behavior (what happens on a first check with no stored snapshot), snapshot retention, and whether payment failure aborts the call.

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 operation and then the cost model. 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 two-parameter tool with no output schema and no annotations, the description covers the core mechanic and cost but leaves the stateful workflow (store before check), return shape, and first-run behavior unexplained. Adequate but with clear gaps an agent would hit in practice.

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 the check/store enum are already documented in the schema; the baseline is 3. The description adds only the vague notion of 'past snapshots', which loosely maps to the store action, but supplies no extra syntax, defaults, or ordering semantics.

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 ('DOM snapshotting and diff detection', 'compares page content against past snapshots'), which is far more informative than the name alone. It doesn't explicitly contrast itself with siblings like run_spider_view_scan or extract_website_metadata, but the change-detection purpose is unambiguous.

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 versus the many sibling checks, nor of the prerequisite workflow (that a snapshot must be stored before a check is meaningful). The 'stateful' wording hints at a store-then-check sequence but never spells it out.

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 a meaningful trait beyond the schema: the $0.005 USD / x402 cost, which tells the agent each call is paid. However, it says nothing about rate limits, whether dynamic pages are rendered, robots.txt/ToS handling, or failure behavior when no contact info exists.

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, fully front-loaded with the core capability, with the pricing detail tucked into a parenthetical at the end. No filler and nothing redundant.

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

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

For a one-parameter extraction tool with no annotations and no output schema, the enumerated output types partially substitute for a return-value spec. Still missing is any usage context and behavioral detail (auth, limits, absence-of-results handling), leaving 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?

There is a single parameter with 100% schema description coverage ('Target website URL or domain name'), so the schema already documents it fully. The description adds no additional meaning about the URL parameter, making the baseline 3 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 gives a specific verb ('Extracts') plus the exact resource types returned: emails, phone numbers, social profiles, and contact page links. This enumeration distinguishes it well from generic siblings like extract_website_metadata, but no sibling is named explicitly, 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?

There is no guidance on when to choose this tool over alternatives such as extract_website_metadata, nor any prerequisites, page-selection rules, or exclusions. The agent must infer usage entirely from the tool name.

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 usefully surfaces a behavioral trait structured fields cannot express — the $0.002 USD / x402 cost — but says nothing about read-only semantics, rate limits, partial-failure behavior for unreachable URLs, or response shape. Cost disclosure is real added value, so this is above a bare 2 but well short of 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?

A single front-loaded sentence: verb first, the full field inventory next, cost in parentheses at the end. No filler, no restatement of the tool name, and every element earns its place.

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

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

With no output schema, the enumerated field list (title, meta description, OpenGraph, Twitter Cards, canonical URL, JSON-LD, headings) effectively stands in for a return-value spec, which is exactly what the agent needs for this simple one-param tool. What is missing is failure behavior on invalid or unreachable URLs, which keeps it from 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?

Only one parameter exists and schema description coverage is 100%, so the schema already documents 'url' as 'Target webpage URL or domain name.' The description adds no format, normalization, or edge-case detail (e.g., how a bare domain is handled versus a full URL), 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 ('Extracts') plus the exact set of resources returned (title, meta description, OpenGraph, Twitter Cards, canonical URL, JSON-LD, headings), which is far more concrete than a generic 'get metadata' phrasing. It does not, however, distinguish itself from overlapping siblings such as run_full_seo_audit or run_spider_view_scan, so it lands at 4 rather than 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 when-to-use guidance, no mention of prerequisites, and no routing to or away from alternatives, even though siblings like run_full_seo_audit and run_spider_view_scan plausibly overlap. The agent must infer usage purely from the purpose text.

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 burden and does disclose the key traits: a paid operation ($7.00 / 70 credits from agent balance), an external Google Autocomplete dependency, and the exact output artifacts produced. It stops short of stating whether anything is published externally or what happens on failure for an unreachable page_url.

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 front-loaded sentence that packs purpose, method, deliverables, and price with no filler. The cost parenthetical is essential decision information, not padding.

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

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

For a no-annotation, no-output-schema tool this covers the essentials: inputs implied, outputs enumerated, and the billing consequence surfaced. Only edge-case behavior (invalid page_url, what the WordPress XML is for) is absent.

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 ties the fixed '20 FAQs' to the max_questions default and hints at the output-family for the format param, but adds no format syntax or constraints beyond what the schema already documents.

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

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

Specific verb-plus-resource: 'Discovers customer search questions via Google Autocomplete and generates ... FAQs' with the exact deliverables (JSON-LD, HTML, WordPress XML) listed. No sibling tool does anything comparable, so the agent can immediately tell this is the content-generation tool rather than an audit/check tool.

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 by the required page_url and the 'target product or service page' framing; there is no statement of when to choose this over siblings like run_full_seo_audit or run_keyword_report. Nothing is misleading, but the agent must infer the scenario.

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 add a genuinely useful trait ('FREE', implying no credit is consumed) and enumerates the returned fields, but it says nothing about authentication requirements, rate limits, or what 'status' actually signifies.

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 the cost signal ('FREE') placed first and zero wasted words. Nothing could be trimmed without losing 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?

There is no output schema, so the description should describe return values; it does so at a high level (balance, status, account information), which is enough for a zero-parameter read tool, though it omits the response format and units.

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

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

The tool takes zero parameters, so there is nothing to document and the baseline of 4 applies. No parameter ambiguity exists.

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 ('Retrieves') and resource ('current API key credit balance, status, and account information'), so the purpose is unambiguous. It does not need to differentiate from siblings (which are all SEO/DNS tools), but it also never explicitly frames itself as the account/billing counterpart to 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?

Usage is implied by the purpose - an agent would call this when it needs to know remaining credits - but there is no explicit when-to-use statement, no prerequisites, and no alternatives mentioned. Adequate but leaves the routing decision 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?

No annotations are provided, so the description bears the full burden. It usefully discloses the returned data set and the zero-cost trait, and the operation is implicitly read-only, but it says nothing about failure modes (unsupported TLDs, missing WHOIS records) or whether the query is live.

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 that opens with the cost badge and then enumerates the exact data retrieved. No filler; 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?

With no output schema, the description compensates well by listing the return fields (age, creation, expiration, registrar, nameservers). It is nearly complete for a simple one-parameter read lookup, falling short only on error/degradation 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?

There is a single parameter with 100% schema description coverage, so the baseline is 3. 'For any domain' adds only mild reassurance about input generality 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 (looks up) and resource (WHOIS registration details, domain age, creation date, expiration, registrar, nameservers). The scope is unambiguous, though it never explicitly distinguishes itself from siblings like check_dns_and_headers or check_web_hosting.

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 signal is the 'FREE:' prefix, which tells the agent there is no cost concern. There is no statement of when to choose this over the sibling DNS/hosting/noindex tools, and no prerequisites or exclusions.

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 cost ($12 USD / 120 credits deducted from agent balance) and the crawl cap, but omits whether the operation is read-only, authentication requirements, expected duration, and failure/refund 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 that packs the core action, audit dimensions, page limit, and cost. There is no filler, and the most important operational constraint (cost) is included without disrupting clarity.

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 description covers purpose, scope, and cost, but with no output schema and no annotations, it does not explain what the audit returns, how results are structured, or whether the operation is long-running. An agent can call it, but key operational expectations remain implicit.

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 domain, format, and max_pages. The description reinforces the 250-page maximum but adds no further syntax or guidance beyond the schema, which is the baseline expectation at full 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?

States a specific verb and resource: executes a multi-page forensic crawl auditing SEO pillars, duplicate metadata, broken links, and redirect chains. The scope (up to 250 pages) is clear, but it does not explicitly differentiate itself from siblings such as run_full_seo_audit or run_quick_seo_checkup.

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 phrase 'multi-page forensic crawl' and the 250-page limit, suggesting a deep/comprehensive audit. However, there is no explicit guidance on when to choose this over run_full_seo_audit, run_quick_seo_checkup, or run_spider_view_scan, and no when-not conditions are stated.

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 does disclose useful behavior: the specific record types captured and the 1-credit cost. However, it says nothing about permissions, whether a baseline snapshot must already exist for a diff to be meaningful, or what happens on first run.

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 scope, and the credit cost is appended efficiently. 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?

For a simple one-parameter tool this is adequate, but with no output schema and no annotations the description should say more about the returned diff, baseline requirements, or first-run behavior. The stated scope is enough to call it, but not enough to predict results.

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% for the single domain parameter and its example is already documented in the schema. The description adds no syntax or format detail for the domain argument, 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 ('captures') and resource ('DNS zone records') plus the record types and the diff-against-history behavior, which cleanly separates it from check_dns_and_headers. It stops short of naming a sibling, so it is clear but not explicitly 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?

No when-to-use guidance, no prerequisites, and no mention of alternatives among the many sibling check_* tools. Usage context (DNS change monitoring) is only implied by the mention of historical diffs.

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 it does disclose a genuinely important trait not derivable from schema: a $39 USD fee deducted from the agent balance, plus multi-page crawling scope. However, it omits runtime/duration, whether the fee is charged on failure, and any rate or permission constraints.

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 compact sentence with no filler, and the scope plus cost are front-loaded where an agent will see them. The parenthetical fee clause is dense but 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 paid, no-output-schema tool with no annotations, the description says what triggers the run and what it costs but not what the 'audit report' returns, how it is delivered, or how long it takes. That leaves meaningful gaps for an agent deciding whether to invoke 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?

There is a single 'domain' parameter with 100% schema description coverage, so the schema already documents it fully. The description adds nothing about accepted formats or URL-vs-domain handling, matching the baseline 3 for high-coverage schemas.

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

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

States a specific verb and resource ('Executes a deep, multi-page 30+ check technical SEO audit') with clear scope (multi-page, 30+ checks). The 'deep' framing implicitly separates it from the sibling run_quick_seo_checkup, but it never names that alternative, so differentiation is left to inference.

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: 'deep, multi-page 30+ check' suggests this is the heavyweight option versus run_quick_seo_checkup, but there is no explicit when-to-use, when-not-to-use, or prerequisite statement. An agent must guess at the tradeoff.

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 does disclose the material behavioral fact that this is a paid operation ($7.00 USD / 70 credits), which is genuinely useful for an agent deciding whether to invoke it. However, it says nothing about credit consumption on failure, expected runtime (report generation is typically slow/async), or whether the caller must hold sufficient credits.

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 that opens with the verb and headline deliverable, with the pricing appended as a parenthetical. The clause list is dense but each item is informative; nothing is redundant. Slightly long for one sentence, but there is no wasted 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 and no annotations, so the description's enumeration of report contents usefully stands in for a return-value spec. What remains missing is operational context an agent needs before committing credits: expected turnaround, whether the response is delivered as a link or inline, and how the format parameter affects delivery. 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 parameters (domain, format) are already documented with examples and a default. The description adds nothing about parameter semantics — it only describes report contents, which are outputs rather than inputs. Baseline 3 is appropriate when the schema does all 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?

States a specific verb (Generates) and a well-defined resource (Website Keyword & Autocomplete Intelligence Report), then enumerates the report's contents (search volumes, rankings, intent mapping, striking distance keywords, report link). It is unmistakably distinct from generic siblings like check_url_status, but it offers no explicit differentiation against the closest siblings, run_full_seo_audit and run_quick_seo_checkup.

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 choose this tool over run_full_seo_audit or run_quick_seo_checkup, nor does it state prerequisites (e.g. domain must be live/indexed) or exclusions. The price is mentioned, which hints at a cost trade-off, but that is an implicit signal rather than 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?

No annotations are provided, so the description carries the full burden. It usefully discloses the 1-credit cost and the return shape (scores, categorized issues, pass lists), but says nothing about read-only vs mutating behavior, permissions, rate limits, or failure handling.

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 action and cost front-loaded and the return shape trailing. No filler, no redundancy.

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 does cover cost and rough return contents, which covers the essentials for a simple 2-parameter tool. It still omits how this differs from run_full_seo_audit and any runtime expectations, leaving 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 domain and format are already documented in the schema. The description adds no parameter-level detail (e.g., accepted URL forms or format trade-offs), 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 ('Runs a fast technical SEO checkup on any website domain') and implies a lightweight counterpart to run_full_seo_audit via 'quick'. However, it never names the sibling it contrasts with, so the differentiation from run_full_seo_audit is left to inference.

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 word 'fast' suggests a lightweight pre-check rather than the exhaustive 'full' audit, but there is no explicit when-to-use, when-not-to-use, or named alternative. An agent must guess between this and run_full_seo_audit.

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 usefully discloses the credit cost and the analysis dimensions, but says nothing about permissions, rate limits, or whether the spider simulation has side effects. Adequate but clearly incomplete for an unannotated 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?

One dense sentence that front-loads the core action and ends with the cost signal. No filler words or redundant restatement 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 read-only analysis tool with no output schema and no annotations, the description covers what is examined but not the shape of the result (report? pass/fail? HTML diff?) or any preconditions. An agent knows what the tool analyzes but not what it gets back.

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?

Single parameter with 100% schema description coverage ('Target domain or URL'), so the schema already documents the input fully. The description adds no format or normalization guidance beyond the schema's example, making the baseline 3 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 gives a specific verb ('Simulates Googlebot & AI spiders') and enumerates the concrete analysis targets (pre-rendered HTML vs CSR text, discovered links, meta robots), so the resource is unambiguous. It does not, however, differentiate itself from adjacent siblings like check_noindex_status or run_full_seo_audit, which could plausibly overlap on crawl/index topics.

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 named alternative among the many sibling checks. The only decision aid is the '(1 credit)' cost note, which implies a paid operation but does not tell the agent when this scan is preferable to a cheaper noindex or SEO check.

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