Exports a Decision Proof Unit as a JSON-LD v2.0 proof document conforming to Cronozen Evidence Ontology. Includes compliance status, 6W extraction (Who/What/Where/When/How/Why), hash chain info, and policy snapshot.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The DPU ID to export as JSON-LD |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions the output includes compliance status, 6W extraction, hash chain info, and policy snapshot, giving some transparency about the result. However, it does not disclose side effects, error conditions, or whether the operation is read-only or mutating.
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 concise, containing a single sentence that packs essential information without fluff. It is front-loaded with the main purpose and immediately followed by relevant output details, maintaining good structure and clarity.
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?
While the description covers the core function and output contents, it lacks contextual completeness for a tool with siblings. It does not explain when to use this export tool compared to other proof-related operations, and it omits any prerequisites or preconditions. This is a gap given the existence of sibling tools.
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 schema already describes the single parameter 'id' as 'The DPU ID to export as JSON-LD', which is clear. The description adds no extra meaning about the parameter, such as format, constraints, or examples. With 100% schema coverage, the baseline is met but not exceeded.
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's function: exporting a Decision Proof Unit as a JSON-LD v2.0 proof document conforming to the Cronozen Evidence Ontology. It distinguishes this from siblings by specifying the export action and format.
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 does not provide any guidance on when to use this tool versus the sibling tools (e.g., proof_get, proof_verify). It lacks context about typical scenarios or conditions that would make this the appropriate choice.
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 (record, get, export, report, chain verify), but proof_verify and proof_public_verify both verify cryptographic integrity with overlapping semantics. The descriptions clarify the auth and chain-link differences, but an agent could still confuse them.
All tools follow a strict 'proof_' prefix with a verb action (get, record, verify, export, report, chain_verify, public_verify). The pattern is consistent, snake_case throughout, and predictable.
With 7 tools covering proof recording, retrieval, verification, export, and reporting, the server is well-scoped for its purpose. No redundancy or bloat, and each tool serves a clear function.
The tool surface covers the full lifecycle of proof management: record (create), get (read), verify (check integrity), export (format), and report (human-readable output). A list operation is missing, but it's not critical for the domain's core workflows.
