utm_builderAppend encoded UTM campaign parameters to a URL, preserving any existing query and fragment. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Base URL, e.g. https://example.com/landing | |
| term | No | utm_term (optional) | |
| locale | No | Language for the source_url link (default en) | |
| medium | Yes | utm_medium, e.g. cpc | |
| source | Yes | utm_source, e.g. google | |
| content | No | utm_content (optional) | |
| campaign | Yes | utm_campaign, e.g. spring_sale |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose that parameters are encoded and that existing query/fragment are preserved, but it does not explain behavior for duplicate UTM params, invalid URLs, or the exact return format. This is partial but not comprehensive.
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 clear and efficient. However, 'Runs on smart-tools.xyz' is unnecessary and does not aid tool selection or invocation, slightly reducing conciseness.
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?
For a simple append-parameters tool, the description covers the key behavior (encoding, preserving query/fragment). No output schema or annotations exist, but the tool's low complexity means the description is mostly adequate, though edge cases like existing UTM parameters are not addressed.
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 all parameters are already documented in the schema. The description adds minimal value beyond noting preservation of query/fragment, which relates to the 'url' parameter. Baseline 3 is appropriate.
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 uses a specific verb ('append') and resource ('URL'), clearly stating it adds UTM campaign parameters. It also mentions preserving existing query and fragment, which distinguishes it from any sibling tools (all other tools are converters/calculators).
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?
Usage is implied by the action of appending UTM parameters to a URL, but there is no explicit guidance on when to use this tool vs. alternatives or when not to use it. No exclusions or alternative tool mentions are provided.
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.