Compute the SHA-256 hash of a text string. Returns the digest as a 64-character lowercase hex string. UTF-8 encoded.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to hash. UTF-8 encoded before hashing. |
| Name | Required | Description | Default |
|---|---|---|---|
| hex | Yes | 64-character lowercase hex digest. | |
| algorithm | Yes | Hash algorithm name (always 'SHA-256'). | |
| bytes_hashed | Yes | Number of bytes that were hashed. |
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?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description goes beyond them by specifying that the output is a 64-character lowercase hex string and that input is UTF-8 encoded. This adds useful technical context about the hash behavior, though it doesn't discuss edge cases like empty input or maximum length (which is in 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 concise sentences, front-loaded with the primary action. Every word adds value: the compute verb, the algorithm, the input type, the output format, and the encoding. 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 stateless tool with one well-documented parameter, an output schema, and annotations covering safety, the description is fully complete. It even states the return format, which is a nice bonus. No gaps remain for the agent to guess.
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%: the only parameter 'text' has a description stating it is UTF-8 encoded before hashing. The description's mention of UTF-8 encoding merely echoes the schema, adding no new semantic meaning. Baseline of 3 is appropriate because the schema already documents the parameter thoroughly.
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 states a specific action ('Compute') and a specific resource ('SHA-256 hash'), making the tool's purpose immediately clear. It distinguishes itself from siblings like base64 or uuid-generator by explicitly naming the algorithm and the text input.
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 provides clear context for when to use the tool: computing a SHA-256 hash of a text string. It doesn't explicitly mention when not to use it or name alternatives, but the function is so specialized that the intended usage is obvious. No misleading exclusions are present.
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 have distinct purposes. However, 'hex-to-rgb' is redundant with 'color-converter', which already handles hex-to-RGB conversion, causing potential confusion.
Names follow a consistent lowercase-with-hyphens style, but vary in pattern (e.g., 'angle-converter', 'average-calculator', 'dedup-lines'). One tool ('internal-do-not-call') deviates from the descriptive norm.
With 46 tools, the server is heavily populated. Many converters could be merged into a generic unit converter, and there is redundancy, making the surface unnecessarily large for a single server.
The server covers a broad range of utility domains: converters, text processing, math, cryptography, etc. Minor redundancies exist (e.g., hex-to-rgb vs color-converter), but the set is otherwise comprehensive.
