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Fino-wind

Vaultbeat MCP Server

Delete state of mind (erases the entry)

delete_state_of_mind
Destructive

Erase an AI-recorded state of mind entry created by mistake—such as a duplicate, wrong reading, or wrong person—and remove it from synced app, cloud, and Apple Health data.

Instructions

Erase one state of mind an AI recorded by mistake (agent write).

Only for an entry that should never have existed — a duplicate, the wrong reading of what they said, the wrong person. To record that a feeling changed, log a new one; feelings change and both are true.

It disappears from get_state_of_mind at once. The person's iPhone, on its next sync, drops it from the app, overwrites its content in the cloud for every reader it was shared with, and removes the sample it wrote into Apple Health, if it wrote one. The result carries deleted_entry — the full entry as it was — so a mistaken delete can be logged again. Records with source: "apple_health" cannot be deleted here; they are edited in Apple Health.

Input Schema

NameRequiredDescriptionDefault
entry_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.3

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the destructiveHint=true annotation by disclosing the full cascade: immediate removal from get_state_of_mind, next-sync removal from the iPhone app, cloud content overwrite for all shared readers, and Apple Health sample deletion. It also notes the deleted_entry payload enabling re-logging and the apple_health source restriction — rich context annotations cannot carry.

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?

Front-loaded with the core intent and the when-to-use condition, then layered with consequences. Slightly long, but nearly every sentence adds distinct operational value (cascade effects, return payload, source restriction).

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?

An output schema exists so return values need not be enumerated, yet the description still flags the deleted_entry payload. Combined with the usage exclusions, cascade effects, and source restriction, an agent has everything needed to invoke this destructive tool correctly.

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 description coverage is 0% and the description never explains the entry_id parameter or where to obtain it. It references related structures (get_state_of_mind, source values) but does not add semantics for the single required parameter, so the schema underspecification is only partially compensated.

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?

States a specific verb and resource ('Erase one state of mind'), scopes it as an agent write, and immediately distinguishes the intent from the sibling log_state_of_mind. An agent can identify the operation without opening 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?

Explicitly states the only valid use case (an entry that should never have existed — duplicate, wrong reading, wrong person) and names the alternative behavior ('To record that a feeling changed, log a new one'). It also gives an exclusion: apple_health-sourced records cannot be deleted here.

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