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bulk_delete_calls

Bulk delete up to 100 call IDs from your account to clean test data. Use dry run to preview count, then delete with approval.

Instructions

Bulk-delete the given call ids (max 100), scoped to your account (POST /v1/calls/bulk-delete). Useful for cleaning up garbage calls accumulated by dogfooding / dev tests. dryRun=true returns the matched count before deleting. The delete is one atomic SQL statement; a bulk_deleted event is recorded in the audit log. Per FK constraints, related traces / annotations / scores are cascade-deleted via ON DELETE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNotrue returns only the matched count without deleting (confirmation UX)
callIdsYesArray of call ids to delete (1-100 entries, each 1-128 chars)
approvalIdNoApproval id granted via request_approval (apr_ + 32 hex; create with action 'bulk_delete_calls'). Server-side verification + atomic consumption on actual deletion (1 approval = 1 execution). dryRun only verifies
Behavior5/5

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

No annotations provided, so description fully covers behavioral traits: atomic SQL statement, audit logging (bulk_deleted event), cascade delete of related entities via FK constraints, dryRun behavior, and approval flow. Comprehensive.

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?

Front-loaded with main action, every sentence adds unique information. No repetition or fluff. Efficiently covers purpose, usage, behavior, and side effects.

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 no annotations and no output schema, the description is remarkably complete: it explains what the tool does, when to use it, how it works internally, side effects, and parameter nuances. Leaves no ambiguity.

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%, so baseline is 3. Description adds value by explaining dryRun's confirmation purpose and approvalId's server-side verification and atomic consumption, 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?

Description clearly states bulk-delete of call ids, scoped to account, with a max of 100. Distinguishes itself via 'garbage calls' context and no sibling tool offers bulk deletion of calls.

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?

Gives a clear use case ('cleaning up garbage calls from dogfooding/dev tests') and mentions dryRun for safe verification. Does not explicitly state when not to use, but the context is sufficient.

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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