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by io.github.123Ergo

check_urls

Read-onlyIdempotent

Check multiple URLs in a single batch. Returns results for all URLs, handling async processing automatically.

Each URL is analysed across seven dimensions: redirect behaviour, brand impersonation, domain intelligence (age, registrar, expiration, status codes, nameservers via RDAP), SSL/TLS validity, parked domain detection, URL structural analysis, and DNS enrichment. Known and cached URLs return results immediately. Unknown URLs are queued for pipeline processing. This tool automatically polls for results until all URLs are complete or the 5-minute timeout is reached. You don't need to manage polling or job tracking.

If the timeout is reached before all results are complete, returns whatever is available with a clear message indicating which URLs are still processing. The user can check results later via check_history.

Maximum 500 URLs per call. For larger datasets, call this tool multiple times with chunks of up to 500 URLs.

Billing: Same as check_url. Known and cached domains are free. Only unknown domains running through the full pipeline cost 1 credit each. The summary shows pipeline_checks_charged (the actual number of credits consumed). If you don't have enough credits for the unknowns in the batch, the entire batch is rejected with a 402 error telling you exactly how many credits are needed.

Duplicate URLs in the list are automatically deduplicated (processed once, charged once). Invalid URLs get individual error status without rejecting the batch.

Use the "profile" parameter to score all results with custom weights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to check (maximum 500 per call)
profileNoName of a custom scoring profile to use for all URLs (optional)

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description goes well beyond this by disclosing async processing, automatic polling with a 5-minute timeout, partial result behavior, deduplication, invalid URL handling, billing/credit charges, and 402 error conditions. This adds substantial contextual value.

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

Conciseness5/5

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

The description is long but well-structured into logical paragraphs covering purpose, processing dimensions, timeout behavior, billing, deduplication, and profile usage. Every sentence carries necessary information for using this complex batch tool effectively. It is front-loaded with the core purpose and adds details without redundancy.

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

Completeness5/5

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

Given the tool's complexity—async processing, billing, limits, error handling, and partial results—the description covers all critical facets. It explains what happens on timeout, how duplicates and invalid URLs are treated, credit requirements, and the return error message. The absence of an output schema is compensated by the detailed behavioral description. The coverage is comprehensive.

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

Parameters4/5

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

Schema documentation covers 100% of parameters with descriptions, including max 500 items for `urls` and a description for `profile`. The description adds extra meaning by explaining the `profile` parameter's purpose ('score all results with custom weights') and describing deduplication behavior that affects `urls`. This goes beyond the schema but does not need to compensate for missing schema info.

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

Purpose5/5

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

The description clearly states the tool's function: 'Check multiple URLs in a single batch.' The verb 'check' and resource 'URLs' are specific, and the plural form distinguishes it from the sibling `check_url`. It also adds unique handling details like async processing and auto-polling, fully differentiating it from siblings.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool, such as batch checks, and gives explicit guidance for large datasets ('call this tool multiple times'). It references `check_history` for retrieving results later and mentions billing affecting batching. However, it does not explicitly state when to prefer the sibling `check_url` (singular) over this tool, though the name and content imply it.

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

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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: check_url vs check_urls distinguish single vs batch, allowlist CRUD tools are separated, and profile management is distinct from account billing. Minor overlap exists between get_balance and get_stats (both report balance) and between list_profiles and show_defaults (both relate to scoring configuration), but descriptions clarify the differences.

Naming Consistency4/5

The vast majority of tools follow a verb_noun snake_case pattern (check_url, create_profile, list_allowlist, get_balance). A few outliers like purchase and signup are single verbs, but they are standard and do not break the overall predictability.

Tool Count4/5

18 tools is above the ideal 3-15 range but appropriate for the server's broad scope: URL analysis, custom scoring profiles, allowlist management, account billing, and reporting. Each tool serves a distinct function and none feel redundant or superfluous.

Completeness4/5

The tool surface covers the core domain thoroughly: single and batch URL checks, credit estimation, profile CRUD (create, list, delete, show defaults), allowlist CRUD, history, and account management (signup, balance, pricing, purchase). Minor gaps exist, such as no delete history or direct retrieval of a single past check by ID, but these are not critical.

Resources