x402-bom-check
BOM Check: Check for a UTF-8 BOM in text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | No | Input to process |
BOM Check: Check for a UTF-8 BOM in text.
| Name | Required | Description | Default |
|---|---|---|---|
| input | No | Input to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state what the tool returns (boolean, BOM position, or a report), whether the BOM is checked only at the start or anywhere in the string, or how edge cases like empty input behave. For a check-type tool with no output schema, these are material gaps.
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 description is short and easily scannable, and the core clause 'Check for a UTF-8 BOM in text' is efficient. However, the 'BOM Check:' prefix largely duplicates the tool name and contributes no information, keeping it from earning top marks for structure.
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?
This is a 1-parameter tool with no output schema and no annotations, so the description must carry substantial weight. It conveys the operation but omits the return contract entirely and offers no differentiation from related text/encoding siblings. For a tool this simple, the gap between the description and what an agent needs to invoke and interpret it correctly is moderate.
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% (input documented as 'Input to process'), so the baseline is 3. The description's phrase 'in text' confirms the input is the string being examined but adds no format, encoding, or constraint details beyond the schema. This is adequate but not additive.
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 'Check for a UTF-8 BOM in text' names a specific verb and resource, making the tool's function clear and distinguishing it from the large sibling set, none of which target BOM detection. It is not a tautology, since it adds what is operated on and what is detected. It falls short of 5 because 'check for' leaves ambiguity about return type (boolean vs. details) and whether detection applies only at the start of the text.
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?
No guidance is given on when to use this tool versus alternatives. With hundreds of siblings including related text/encoding tools like utf8-validate and charset-detect, the description provides no selection criteria, exclusions, or context. An agent must infer usage entirely from the tool name and one-line purpose.
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.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.