Desvela ARD Registry — free preflight(domain)

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

With no annotations, the description carries the full burden and does so: it discloses that this is a live probe making ~6 requests against the target, that it is free, that results depend on a browser control request, and that it can be skipped when the site opted out (optedOut, no requests sent). The full verdict taxonomy (ok/blocked/throttled/degraded/error) and the throttle-vs-block distinction are exactly the kind of behavioral context annotations would otherwise supply.

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 core distinction (observed CDN behavior vs robots.txt), followed by the verdict taxonomy, edge cases, cost, and sibling routing — all load-bearing. Slightly redundant in restating the robots.txt-can't-tell-you point and the parenthetical glosses, but nothing is 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?

No output schema and no annotations, so the description must define the result shape; it does so via the verdict vocabulary and the measurable=false case. It stops short of describing the actual response structure (per-crawler mapping, whether bytes/status codes are returned), which is the remaining gap for a tool whose whole value is its output.

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?

One required parameter at 0% schema description coverage; only the JSON Schema pattern hints at the accepted format. The description implies the argument is a bare domain (it probes 'the homepage', not an arbitrary URL), which is useful, but it never states format, scheme handling, or subdomain behavior explicitly.

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 action (probe the homepage with each AI crawler's real user-agent and compare against a browser) on a specific resource (a domain's CDN behavior). It explicitly contrasts with the declared policy in robots.txt, which makes it impossible to confuse with the sibling preflight 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?

Ends with an explicit routing rule: 'Use preflight for the declared policy; use this for the observed one.' It also implicitly scopes usage to live probing of a single domain, and the measurable=false explanation tells the agent when the tool yields no verdict rather than a false negative.

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 does substantial work: it discloses the data sources checked, the output receipt contents (surface-by-surface state, search words, missing items), and the serving behavior (index when fresh <7 days, live-check otherwise). It also notes the tool is free. It stops short of stating rate limits, auth requirements, or error behavior, so it is strong but not fully exhaustive.

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

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

The description is compact and front-loads the surfaces it checks before moving to the output and serving behavior. Every clause serves a purpose, though the long single paragraph structure could be slightly easier to scan.

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, no-output-schema tool, the description sufficiently explains what is inspected, what the receipt includes, and how data freshness works. The main gap is the lack of domain syntax guidance, but the schema pattern partially covers that concern.

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 0% for the single required domain parameter. The description refers to 'a domain' but adds no format guidance, examples, or syntax details beyond what the name and schema pattern already imply. It does not compensate for the lack of schema documentation.

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 the specific resources it inspects (ai-catalog.json, llms.txt, agents.md, robots.txt AI directives) and the resulting visibility receipt, so the tool's job is clear. It does not explicitly distinguish itself from siblings like crawler_block_test, but the breadth of surfaces checked implies a broader preflight inspection than a single block test.

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

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

The phrase 'before you touch it' gives a clear temporal context for using the tool prior to interacting with a domain. It does not name alternatives or exclusions, but the trigger condition is stated well enough for an agent to know when to invoke it.

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 discloses key behavioral traits: returns catalog entries per ARD spec, and when no match, returns referrals and listing instructions instead of an empty answer. This is useful, though it does not mention auth, rate limits, or side effects, which are likely not relevant for a read-only search 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?

Three sentences, each adding distinct value: purpose, output format, and fallback behavior. The most important scoping information is front-loaded. No redundant phrasing, though it could be slightly more compact without losing 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?

For a single-parameter search tool with no output schema, the description adequately covers purpose, output format, and fallback behavior. It also references the POST /search endpoint for context. Minor gaps like pagination or limits are not critical for such a simple tool.

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

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

Schema coverage is 100%, so the schema already documents the 'text' parameter. The description adds a concrete example ('find an MCP server for weather data') and clarifies it is a natural-language query, which helps the agent formulate effective inputs beyond the schema's minimal description.

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 ('search') and resource ('what Desvela has indexed'), and explicitly differentiates from siblings by mentioning it uses the same index as POST /search. Also clarifies the output is catalog entries per the ARD spec, distinguishing it from crawler_block_test, preflight, and watch.

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

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

The description implies usage through the natural-language query example and the 'same index' reference, but does not explicitly state when to use it versus alternatives or provide exclusion conditions. Siblings have clearly different purposes, so the context is inferable, but there is no explicit 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 burden and does well: it discloses the signed webhook (HMAC-SHA256), specific change triggers, weekly check frequency, and return values (manage_token, secret, and endpoints). Missing details on rate limits, authentication requirements, or what happens if domain is invalid, but still transparent for a subscription tool.

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

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

The description is a single sentence that packs essential information: action, webhook signature, trigger events, frequency, and return values. It is concise but could be broken into shorter sentences for readability. No fluff, but 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?

Given no output schema, the description covers return values (manage_token, secret) and management endpoints (GET/DELETE URL). It explains the webhook signature and detection scope. Missing details on webhook payload format or how to use the manage token, but sufficient for core functionality.

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 50% (only webhook_url has a description). The tool description adds context about the domain (the domain to watch) but doesn't explain the pattern or provide examples. For webhook_url, the schema already says 'HTTPS endpoint', and the description reinforces it. Overall, adds some value but incomplete for the domain 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?

The description clearly states the tool subscribes to a domain for changes, enumerates what changes are detected (ai-catalog.json, llms.txt, agents.md, robots.txt), and mentions the signed webhook mechanism. It distinguishes from the sibling 'preflight' by being a subscription tool rather than a test or validation 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?

The description implies use when wanting to be notified of domain changes for AI agents, but lacks explicit when-to-use or when-not-to-use guidance. No mention of prerequisites or comparison with the sibling tool 'preflight' (e.g., suggesting preflight for testing before subscribing).

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