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delete_library_item

DestructiveIdempotent

Use this only when the user explicitly asks to remove one specific saved Prompt or Skill, and only after they confirm. It removes that one item from the library and the dashboard. It cannot delete facts, sessions, brands or the user's account, so never use it for requests to delete an account or all data.

Input Schema

NameRequiredDescriptionDefault
slugYesThe slug of the item to remove
brandNoWhich of the user's brands this is for, by name. Leave it out to use this connection's default brand. Set it when the conversation is about a different brand of theirs. If you can't tell which brand is meant, ask the user first.
confirmYesMust be true. Forces the agent to confirm intent before calling.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, idempotentHint=true, and readOnlyHint=false, so the hazard profile is known. The description adds real value beyond that: it specifies the blast radius (only the one item, in both library and dashboard), the confirmation gate, and the entity types explicitly out of reach. It stops short of stating that the deletion is permanent/irreversible, which is the main residual gap.

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?

Three sentences, each doing distinct work: eligibility/confirmation gate first, effect second, negative scoping third. No repetition of the name or title and no filler.

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 tool with full schema coverage, strong annotations, and no output schema, the description covers scope, confirmation, effect, and out-of-scope entities. An agent has everything needed to decide whether to call it and what to expect, with irreversibility being the only minor omission.

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

Parameters3/5

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

Schema coverage is 100%, so slug, brand, and confirm are all documented in the schema itself, which sets the baseline at 3. The description only implicitly reinforces the confirm parameter ('only after they confirm') and says nothing about slug formatting or the brand-defaulting behavior, so it adds little parameter-level meaning over the schema.

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 names a specific verb (remove/delete) and a tightly scoped resource: one specific saved Prompt or Skill. It also states where the removal takes effect (library and dashboard), so an agent can distinguish it from update_library_item or list_library without inspecting the schema.

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

Usage Guidelines5/5

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

It gives an explicit precondition ('only when the user explicitly asks... and only after they confirm') plus explicit exclusions ('cannot delete facts, sessions, brands or the user's account... never use it for requests to delete an account or all data'). Both the when and the when-not are stated outright, leaving nothing to inference.

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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