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ostermeyer

jmd-mcp-sql

by ostermeyer

delete

Delete SQLite records by filter or primary key list, or drop schema objects like tables, indexes, triggers, and views with confirmation keys.

Instructions

Delete records or drop a DDL object (https://github.com/ostermeyer/jmd-spec).

Delete (#- Label): filter-based delete (≥1 field required).

#- Order
id: 42

Bulk delete (#- Label[]): primary-key list (or objects for composite keys).

#- Order[]
- 42
- 43

Schema (#! Label): drop a DDL object. Each kind needs its own confirm-key:

Tables / views (legacy): confirm: drop-table

#! Order

Indexes: confirm: drop-index

#! Index
name: idx_order_status

Triggers: confirm: drop-trigger

#! Trigger
name: trg_log_orders

Views (preferred over the legacy drop-table path): confirm: drop-view

#! View
name: PendingOrders

Frontmatter policy: strict refusal — unknown keys cause an error. Accepted keys: confirm, debug. Debug: 'debug: sql, timing, table'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses confirm-key requirements, strict refusal on unknown keys, accepted keys (confirm, debug), and the debug option. The destructive nature is implied by 'delete'/'drop' and reinforced by confirm keys; return values are covered by the output schema.

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 long, but the length is earned: purpose is front-loaded and each block adds a distinct mode or policy. The code examples are compact and scannable, and the URL provides a reference without bloating the text.

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

Completeness4/5

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

For a tool with three modes, one opaque parameter, and no annotations, the description covers the necessary syntax, confirm keys, accepted frontmatter, and debug behavior. It falls just short of fully complete because it never explicitly ties the examples to the 'document' parameter or states the output shape, though an output schema exists.

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 0% and there is only a 'document' string parameter. The description effectively documents the document format through labeled examples and frontmatter policy, which adds substantial meaning beyond the bare schema, though it never explicitly names the 'document' parameter.

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 opens with a specific verb and resource: 'Delete records or drop a DDL object'. It then distinguishes three concrete modes (filter-based delete, bulk delete, schema drop), which makes the tool's scope unmistakable and separates it from siblings like open/read/write.

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?

It gives clear usage context for each mode, e.g. 'filter-based delete (≥1 field required)' versus 'primary-key list', and notes that schema drops require per-kind confirm keys. It does not explicitly mention when to prefer delete over write, so it misses the top-level alternative guidance.

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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