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squirrelscan

by com.squirrelscan

Delete websites in bulk

delete_websites
Destructive

Delete up to 50 websites in one call, for cleaning up a dashboard that has filled with one-off or prospect audits. Same soft delete as delete_website (past audits, reports, and issues are preserved, published report links keep working, slots are freed) and the same two-step confirm: call once without confirm to see the domain behind every id, then again with confirm: true. EVERY result echoes the domain, so read them back to the user before and after: an id is not a name, and this is the tool most likely to be pointed at the wrong list. The preview also shows each site's kind and an owned_count: unclassified sites read as owned, so an 'owned' entry in a list you built from prospects is the clearest sign the wrong ids were assembled. Ids that do not resolve are reported per-id, never as a whole-call failure. To pick the ids, list_websites with kind: "prospect" returns only sites explicitly marked disposable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNoApprove the deletions. Omit on the first call to see which domain each id resolves to; set true to delete after the user approves.
website_idsYesWebsite ids from list_websites (1 to 50). Duplicates are collapsed.

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, the description richly discloses behavior: soft-delete semantics, two-step confirm, per-ID error handling, the preview showing owned_count, and the caveat about unclassified sites. This adds significant value and context not available from annotations alone. No contradictions with annotations.

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

Conciseness4/5

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

The description is a single dense paragraph, but every sentence carries important operational or safety information. It is front-loaded with the core action, and while long, the complexity of the tool justifies the length. No fluff.

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?

For a destructive bulk tool with no output schema, the description covers all critical aspects: what happens on delete, how preview works, how to verify IDs, what errors occur, and how to correctly source IDs. It is fully complete for an agent to safely invoke the tool.

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 coverage is 100% for both parameters, but the description adds practical semantics: the two-step confirm workflow, that website_ids should come from list_websites, and that duplicates are collapsed. It also warns that every result echoes the domain, reinforcing the importance of confirm. This goes beyond the schema descriptions.

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 'Delete up to 50 websites in one call', which is a specific verb, resource, and scope that distinguishes it from the sibling delete_website. It also provides the use case ('cleaning up a dashboard') and the bulk nature, making the purpose unambiguous.

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 gives clear context on when to use it ('for cleaning up a dashboard filled with one-off or prospect audits') and explicitly points to list_websites as the way to select IDs. It does not explicitly state when to use delete_website instead, but the bulk vs. single distinction is implied through the max 50 limit and the reference to 'same soft delete as delete_website'.

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

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct resource-action pair: websites, audits, issues, rules, credits, notifications, and account info are cleanly separated. Even the close pairs (delete_website vs delete_websites, get_rule vs list_rules) are clear singular/bulk or fetch-all vs fetch-one distinctions.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: add_, delete_, get_, list_, run_, comment_, send_, create_. The only outlier, whoami, is a conventional standalone command and does not break the overall predictability.

Tool Count4/5

At 20 tools, the surface is slightly heavy, but the count is justified by the wide domain coverage: audit lifecycle, issue tracking, rule catalog, billing/credits, notifications, and account management. Each tool appears to earn its place, and none feel redundant.

Completeness4/5

The core workflow is well covered: run an audit, poll it, fetch a report, compare audits, list and comment on issues, browse rules, and manage websites. Minor gaps exist—no cancel-audit tool, no update_website, and issues cannot be status-changed—but agents can work around these using the existing tools.

Resources