json_formatterValidate and pretty-print or minify JSON, reporting the line and column on a parse error. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | JSON text to format | |
| action | No | pretty = indented (default); minify = single line | |
| indent | No | Spaces per level for pretty (default 2), or "tab" for tabs | |
| locale | No | Language for the source_url link (default en) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool reports the line and column on a parse error, which is valuable behavioral information beyond the schema. However, with no annotations provided, the description carries the full burden but does not specify the success output format or edge-case handling, leaving some 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 first sentence is concise and informative. The second sentence, 'Runs on smart-tools.xyz,' is irrelevant for selecting or invoking the tool and does not earn its place, slightly detracting from 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 tool with a fully documented schema, the description is adequate. It covers the validation and error-reporting behavior, though it lacks an explicit statement about the success return value. Given the tool's simplicity and absence of an output schema, the description is mostly complete.
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%, with parameter descriptions already explaining 'action' and 'indent' in detail. The tool's description adds no additional parameter semantics, so the baseline of 3 applies.
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 specific verbs 'Validate' and 'pretty-print or minify' with the resource 'JSON', precisely stating the tool's function. It also distinguishes itself from sibling tools like csv_to_json by focusing on formatting/validation rather than conversion.
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 clearly implies when to use the tool: whenever you need to validate or format JSON. It provides clear context but does not explicitly mention alternatives or when-not-to-use, so it lacks the highest level of explicit exclusion guidance.
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.