Compute a commitment string for (input, salt): sha256(JCS(input) ++ salt_bytes), prefixed 'sha256:'. Convenience only — the rule is public and you can compute it yourself.
| Name | Required | Description | Default |
|---|---|---|---|
| salt | Yes | Your hex salt (even length, e.g. 32+ random bytes hex-encoded). Keep it secret until reveal. | |
| input | Yes | Your algorithm input (any JSON value). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and excels: it discloses the exact algorithm, output format ('prefixed 'sha256:''), and states the rule is public. It also notes it's a pure convenience wrapper with no hidden side effects, making behavior fully transparent for a deterministic function.
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 sentences with no waste. The formula is front-loaded, and the 'Convenience only' note adds essential context without repetition. Every word 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 pure function with two parameters, the description is complete. It provides the algorithm, input types, output format, and context on when to use it. No output schema exists, but the formula fully specifies the return value. Sibling tools don't create ambiguity that requires more detail.
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 provides descriptions for both parameters (100% coverage). The description adds meaning by explaining how each parameter is used in the formula: input is canonicalized via JCS and salt is converted to bytes. This goes beyond the schema's simple definitions and clarifies processing semantics.
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 a commitment string via a concrete formula ('sha256(JCS(input) ++ salt_bytes), prefixed 'sha256:''). This specific verb+resource definition distinguishes it from siblings like commit_input, which likely performs a different action, and the phrase 'Convenience only' further clarifies its scoped role.
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 explicitly says 'Convenience only — the rule is public and you can compute it yourself,' which tells the agent this tool is optional and a manual alternative exists. However, it does not explicitly name any alternative tools (e.g., commit_input) or contrast with them, so the guidance is clear but not fully 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.
Each tool has a clear, distinct role in the deal lifecycle: key creation, deal creation, algorithm listing, input validation, commitment computation, committing, revealing, entropy retrieval, certificate fetching, and certificate verification. No two tools appear to do the same thing.
All tool names follow a consistent verb_noun snake_case pattern (e.g., create_deal, get_certificate, verify_certificate). The verbs and nouns are descriptive and match the tool's function. There is no mixing of conventions.
With 11 tools, the set is well-scoped for the fairness deal domain. Each tool earns its place, covering onboarding, deal creation, input handling, execution, and verification without unnecessary redundancy.
The core lifecycle is covered: create key, create deal, inspect algorithms, validate inputs, compute commitments, commit, reveal, fetch entropy for random deals, retrieve certificates, and verify them. The main gap is a tool for counterparties to accept/join a deal using the invite token, but this may be handled outside the MCP server.