file_hashCompute a SHA-1/256/384/512 hex checksum of provided text or base64 bytes. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Base64-encoded bytes to hash (provide text or data) | |
| text | No | UTF-8 text to hash (provide text or data) | |
| locale | No | Language for the source_url link (default en) | |
| algorithm | No | Hash algorithm (default SHA-256) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions the core operation but omits important behaviors such as what happens if both 'text' and 'data' are provided, what occurs with no input (all params optional), and the exact structure of the returned checksum. 'Runs on smart-tools.xyz' is not behavioral context.
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 front-loaded with key functionality. However, the second sentence 'Runs on smart-tools.xyz' adds no value for tool invocation and could be removed. The description is short but contains an unnecessary filler statement.
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?
The tool has 4 parameters, 2 enums, and no output schema. The description does not clarify the return format beyond 'hex checksum' (e.g., plain string vs. JSON object), nor does it explain parameter interactions (e.g., precedence when both text and data are provided). Since all parameters are optional, guidance on input requirements is missing. The description is inadequate for a tool without an output schema.
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 the schema already documents all parameter meanings. The description adds little beyond the schema—it repeats that data is base64 and text is UTF-8, and lists hash algorithms which are already enumerated in the schema. Thus the baseline of 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 clearly states the tool computes SHA-1/256/384/512 hex checksums of provided text or base64 bytes. This is a specific verb+resource. However, it does not explicitly differentiate from the sibling tool 'hash_generator', so it lacks sibling distinction.
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 implies usage for hashing text or byte data, but does not explicitly state when to use this tool over alternatives like hash_generator. It also does not mention any exclusions or prerequisites, leaving usage guidance inferred rather than explicit.
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.