due_date_calculatorEstimated due date by Naegele's rule (+280 days from last period, adjusted for cycle length). Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Language for the source_url link (default en) | |
| last_period | Yes | First day of last menstrual period, YYYY-MM-DD | |
| cycle_length | No | Average cycle length in days (default 28) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses the core calculation logic (Naegele's rule and cycle length adjustment) but does not mention return format, edge cases, or locale behavior. This is a partial disclosure that adds some value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence is concise and informative. However, the second sentence 'Runs on smart-tools.xyz' adds no value for tool selection or invocation and could be removed. The overall length is short, but not every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should specify what the tool returns (e.g., a date string or estimated due date with link). It does not, and it also omits guidance on invalid inputs or locale usage. The core formula is covered, but significant gaps remain for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds context about cycle length adjustment but does not provide additional semantic meaning for parameters like locale or error handling. Baseline 3 is appropriate because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates due date using Naegele's rule (+280 days from last period, adjusted for cycle length). This specific algorithm and the mention of 'last period' and 'cycle length' distinguish it from sibling calculators like date_difference_calculator or age_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for calculating a due date from the last menstrual period, but it provides no explicit guidance on when to use it versus alternatives, nor any exclusions. No sibling tools are named, leaving the agent to infer context from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.
Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.
With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.
The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.