hash_generatorHash text with SHA-1, SHA-256, SHA-384 or SHA-512 (hex, over UTF-8 bytes). MD5 is not supported. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to hash | |
| locale | No | Language for the source_url link (default en) | |
| algorithm | No | Hash algorithm (default SHA-256) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals that output is hex-encoded, input is UTF-8 bytes, and MD5 is unsupported—key behavioral details. It also notes the tool runs on smart-tools.xyz. While it doesn't cover error behavior or limits, it does provide substantial context 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 description is two sentences long, front-loaded with the primary action ('Hash text'), and every word adds value—algorithm list, output format, encoding, a negative constraint, and hosting context. No fluff or repetition.
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 hashing tool with a fully documented schema, the description is complete: it explains the return format (hex), encoding, algorithm choices, and a key exclusion (MD5). The only missing piece is an explicit contrast with sibling tools like file_hash, but that is not critical given the clear focus on text.
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?
The input schema already describes all 3 parameters with 100% coverage, so the baseline is 3. The description adds extra semantic context by specifying the output is hex and that hashing operates over UTF-8 bytes, which enriches the meaning of the 'text' and 'algorithm' parameters beyond their schema descriptions.
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 starts with 'Hash text' and explicitly lists supported algorithms (SHA-1, SHA-256, SHA-384, SHA-512), clearly distinguishing this from sibling tools like file_hash (for files) and base64 (encoding). It also states the output format (hex) and encoding (UTF-8), fully clarifying what the tool does.
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 use for hashing text with specific algorithms, and notes that MD5 is not supported, which is a useful exclusion. However, it does not explicitly mention alternatives or when not to use it (e.g., for file hashing), so it stops short of a 5.
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.