x402-sig-figs
Sig Figs: Round a number to a specified number of significant figures. Provide value and optional sigFigs (default 3).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | Value to process | |
| sigFigs | No | SigFigs to process |
Sig Figs: Round a number to a specified number of significant figures. Provide value and optional sigFigs (default 3).
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | Value to process | |
| sigFigs | No | SigFigs to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden of behavioral disclosure. It honestly states the core behavior — rounding to a chosen number of significant figures — and the default of 3. It does not disclose the rounding convention (half-up vs half-even), how string-form inputs are parsed, or what the return value looks like.
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?
Two short sentences with the operation front-loaded and zero filler. The 'Sig Figs:' prefix is mildly redundant with the tool name, but everything else 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?
For a simple two-parameter pure function, the definition is close to sufficient: the operation and the default are stated. Remaining gaps are the lack of disambiguation from near-duplicate siblings, no return/output information despite there being no output schema, and no rounding-convention detail. An agent can probably invoke it correctly but may select it incorrectly.
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 coverage is 100% so the baseline is 3, but the schema descriptions ('Value to process', 'SigFigs to process') are tautological and add no meaning. The description partially compensates by stating that sigFigs is optional with a default of 3, which the schema alone does not convey. It never clarifies the expected string format for value or valid ranges/constraints for sigFigs.
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 names a specific verb and resource — 'Round a number' — and defines the exact scope: 'to a specified number of significant figures.' This is clear and concrete. It does not, however, distinguish itself from near-duplicate siblings such as x402-significant-digits and x402-format-significant, which plausibly perform the same operation.
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?
There is no when-to-use guidance and no comparison with alternatives. The 'Provide value and optional sigFigs (default 3)' line is calling instruction, not routing guidance. Given the enormous sibling list full of rounding and formatting tools (x402-round-to, x402-format-significant, x402-significant-digits), an agent gets zero help choosing this tool over them.
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.