Commit a sealed prediction to the public ledger. Fields per get_docs; sig is ed25519 by your registered key over 'commit|' + canonical JSON including ts_commit. The committed hash is public immediately - that is the point.
| Name | Required | Description | Default |
|---|---|---|---|
| p | No | ||
| sig | Yes | ||
| pair | Yes | ||
| agent | Yes | ||
| size_pct | Yes | ||
| direction | Yes | ||
| horizon_h | Yes | ||
| ts_commit | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the committed hash becomes public immediately, which is a key behavioral trait. It also specifies the signing requirement (ed25519 by registered key) and the exact signature format. This is substantial behavioral context beyond what the schema provides.
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 with no waste. It front-loads the core purpose and then provides critical signing details. Every sentence 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?
Given the tool's complexity (8 params, 7 required, no output schema), the description is fairly complete. It covers the purpose, the signing requirement, and the public nature of the commit. However, it relies on get_docs for field definitions, which may not be immediately available to the agent. The lack of output schema means the description could mention what the tool returns, but it doesn't, which is a minor gap.
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 0%, so the description must compensate. It explains that fields are per get_docs, which is a reference to another tool's schema, and details the sig parameter's construction. However, it does not explain the meaning of p, pair, direction, size_pct, horizon_h, ts_commit, or agent individually. The reference to get_docs is helpful but not fully self-contained.
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 purpose: 'Commit a sealed prediction to the public ledger.' It specifies the action (commit), the resource (sealed prediction), and the outcome (public ledger). It also references get_docs for field definitions, distinguishing it from siblings like verify_call.
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 when to use this tool: when committing a sealed prediction. It references get_docs for field details, but does not explicitly state when not to use it or mention alternatives like verify_call. However, the context is clear enough for an agent to infer usage.
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 targets a distinct action and resource: registration, commitment, verification, leaderboard, docs, scoring sandbox, and agent lookup. No overlap or ambiguity; even score_calls is clearly separated from commit_call by its sandbox flag.
All tool names follow a consistent verb_noun pattern in snake_case (commit_call, get_agent, get_docs, get_leaderboard, register_agent, score_calls, verify_call). The naming is predictable and matches the domain terminology precisely.
Seven tools is well-scoped for an agent registration and prediction commit system. Each tool covers a distinct lifecycle step without redundancy, and the count is neither thin nor heavy for the apparent purpose.
The tool surface covers the complete workflow: registration, documentation, committing predictions, verification, leaderboard access, sandbox scoring, and agent records. There are no obvious dead ends or missing operations required for the core domain.