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pablixnieto2

ETL-D MCP Server

by pablixnieto2

enrich_date_v1_enrich_date_post

Parse human-readable date strings into structured ISO 8601 formats, resolving relative dates and timezones for database normalization.

Instructions

Transforms human-readable or messy date strings into structured ISO 8601 formats. Features relative date resolution (e.g., 'next Tuesday') and Timezone awareness.

Cost: 1 credit per request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNo
date_orderNoThe expected order of day, month, and year for ambiguous dates (e.g., 01/02/03).DMY
date_stringYesThe human-readable or messy date string to parse. Supports relative dates (e.g., 'next Friday'), absolute dates, and mixed formats. USE THIS TOOL whenever you need to normalize a date for database entry. NEGATIVE CONSTRAINT: DO NOT use this tool for plain time strings (e.g., '14:00') without any date context. If the input is just a number, it might be a year; specify source_format if known.
output_formatNoThe desired strftime format for the output string.%Y-%m-%d %H:%M:%S
source_formatNoExpected format of the input date. Use 'auto' for heuristic detection.auto
target_timezoneNoDEPRECATED: Use context.timezone instead.
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses core behaviors (relative date resolution, timezone awareness) and mentions the cost of 1 credit per request. However, it does not describe failure modes, edge-case behavior (e.g., ambiguous dates), or the exact output structure beyond the ISO 8601 format statement, leaving some transparency gaps.

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?

The description is two sentences plus a cost line, delivering the purpose and key features upfront without fluff. It is appropriately concise and structured, with no redundant information.

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?

The tool has 6 parameters but only 1 required, and the schema is detailed. The description covers the core transformation, relative dates, and timezone, plus cost. It lacks explicit notes on output format customization (though output_format is in schema) and does not state whether the output is a string or other type, but given the schema and the simplicity of the operation, it is reasonably complete. The deprecated target_timezone is noted in schema, not description, but that's acceptable.

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 high (83%), with most parameters having explanatory descriptions (e.g., locale, timezone, output_format). The main description does not add parameter-specific semantics beyond mentioning timezone awareness, which is already covered. Since the schema already documents the parameters, the description does not need to repeat, giving a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the core function: transforming date strings into structured ISO 8601 formats. It highlights key features (relative date resolution, timezone awareness) and is unambiguous about the resource being dates. However, it does not explicitly differentiate from sibling enrichment tools (e.g., enrich_amount, enrich_name), relying on the shared verb 'enrich' pattern for inference.

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?

The main description does not provide usage guidance, but the date_string parameter description explicitly states when to use ('USE THIS TOOL whenever you need to normalize a date for database entry') and includes a negative constraint (DO NOT use for plain time strings). It also advises specifying source_format for numeric years. However, it does not name alternative tools or compare with siblings, so guidance is present but not comprehensive.

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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