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write_record

Create, update, or delete records in a mock resource. Writes persist (unlike JSONPlaceholder/FakeStoreAPI). POST creates (auto-id), PUT replaces, PATCH merges, DELETE removes. id required for PUT/PATCH/DELETE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoRecord id (PUT/PATCH/DELETE).
bodyNoRecord fields (POST/PUT/PATCH).
methodYes
projectYes
resourceYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses important side effects—persistence and per-method behavior (auto-id, replace, merge, delete)—which is substantial. It does not cover return values or error behavior, but the core mutation semantics are transparent.

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 dense sentences convey scope, persistence, and method-specific rules with no filler. The most important behavioral contrast—writes persist—is front-loaded, and every sentence earns its place.

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

Completeness3/5

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

For a 5-parameter mutation tool with no output schema, the description covers method semantics well but omits guidance on valid project/resource identifiers and expected response format. These gaps prevent full standalone usability, though the core CRUD workflow is understandable.

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?

The description adds real meaning to method by explaining what POST, PUT, PATCH, and DELETE do, and it clarifies when id is required. However, project and resource, two required parameters, are left completely undocumented in both the schema and the description, so parameter coverage 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?

The description opens with 'Create, update, or delete records,' a specific verb-resource statement, and then specifies exact HTTP semantics. This clearly differentiates write_record from read-oriented siblings like query_records.

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

Usage Guidelines3/5

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

The description gives clear write-tool context and notes that writes persist, which helps an agent decide to use it. However, it never names sibling tools or states when to prefer query_records or add_resource instead, so usage guidance is implied rather than explicit.

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

A4.2/5.0
Disambiguation5/5

Every tool targets a distinct resource or action: project creation, data seeding, record CRUD, traffic inspection, snapshots, and monitoring are all clearly separated. The four monitoring-related tools are carefully differentiated with cross-references, so an agent is unlikely to misselect.

Naming Consistency3/5

Most data and lifecycle tools follow a clear verb_noun pattern (add_resource, create_project, query_records, write_record), but several tools use noun phrases instead (heartbeat, snapshots, project_info, uptime_monitor, custom_route). The split is readable but not a consistent convention.

Tool Count5/5

14 tools is a reasonable, well-scoped size for a combined mock-API platform and monitoring utility. Each tool has a distinct job, and the monitoring tools complement the mock-API lifecycle tools without feeling redundant.

Completeness4/5

The toolset covers project creation/deletion, resource seeding, record CRUD, request inspection, snapshots, and external API monitoring. Minor gaps exist: resources can be added but not individually removed/updated, and custom routes have no delete or update path.

Resources