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gemmeinhq

Gemmein MCP Server

Official

validate_collection_name

Read-only

Validate planned Gemmein collection names against required syntax before writing g.collection() calls, catching illegal strings and providing corrective suggestions.

Instructions

Run at PLANNING time on every collection name you intend to use, before any g.collection(name) call is written. The naming law: lowercase letters, numbers, underscores; starts with a letter; 2-63 characters. A bad name throws from g.collection(name) before any network call — at module load that blanks the whole app with no console error. An invalid name comes back with a suggested fix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond readOnlyHint=true by disclosing the consequence of skipping it: a bad name throws from g.collection(name) *before* any network call, and at module load that blanks the whole app with no console error. It also notes that invalid input returns a suggested fix, which is real behavioral context about the failure path.

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?

Four short sentences: the when, the rule, the failure consequence, and the return behavior — each earns its place, and the strongest constraint (run before writing g.collection) is front-loaded.

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 single-param validator with no output schema and only a readOnlyHint annotation, the description covers timing, the validity rules, the error consequence, and the shape of the failure response. It leaves the exact success return (boolean? echo of the name?) unstated, a minor gap given no 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 the single 'name' parameter is undocumented in the schema, so the description carries the burden — and it does, spelling out the naming law (lowercase letters, numbers, underscores, starts with a letter, 2-63 chars). That fully compensates for the gap, though it never restates the parameter by name or its type.

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 ('validate collection name') and immediately frames it as a pre-flight check for g.collection(name) calls, which no sibling tool covers. An agent can distinguish this from guide/reference/check_integration without opening any 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?

Explicit trigger: 'Run at PLANNING time on every collection name you intend to use, before any g.collection(name) call is written.' This names both the timing (planning, not runtime) and the exact point of use, 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.