Full detail on one 8004 NONCE token: its seed (which IS the winning work hash), difficulty in leading-zero bits, band, rarity score, current owner, and links. Every value is read live from the chain.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | token id (0-based; 0-20 are DAEMON's mined genesis) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral burden. It does disclose that every value is read live from the chain, which is useful and signals a real-time read rather than cached data. However, it does not mention failure behavior, finality, auth, or side effects; the absence of annotations leaves those gaps.
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, no filler; the scope is front-loaded and each listed field earns its place. Very efficient for an AI agent to parse.
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?
With one simple parameter and no output schema, the description does enough by listing the return fields (seed, difficulty, band, rarity, owner, links) and stating the live-chain read. It does not discuss errors or edge cases (e.g., nonexistent token id), but for a get-by-id read the core context is present.
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%, and the id property is already described as a 0-based token id with DAEMON genesis range. The description adds no parameter-level meaning; it focuses on response fields. Baseline 3 applies because the schema carries the documentation burden.
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 opens with 'Full detail on one 8004 NONCE token' and enumerates the exact fields returned, so an agent immediately knows the verb (get one token) and resource. It is distinguishable from a census/list tool by 'one token', though it does not explicitly name any sibling alternative, so not a 5.
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?
No when-to-use or when-not-to-use guidance is given, and no sibling alternatives are mentioned even though nonce_census and nonce_info exist. The only usage signal is the word 'one', which weakly implies this is for single-token lookups; there are no exclusions or routing conditions.
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.
The koine_ and nonce_ prefixes cleanly separate two distinct collection workflows, and within each prefix every tool addresses a unique action or resource. Even the two verify tools are easily distinguished by collection prefix and their exact verification behavior.
Tool names share a clear collection-prefix snake_case scheme, making grouping and selection predictable. However, not every name follows the same verb_noun form—info, census, spec, listings, and provenance are noun-style while mine, get, list, and verify are verb-style—so the pattern is consistent but not perfectly uniform.
13 tools is well-scoped for a server covering two distinct on-chain art collections with read, discovery, verification, and minting workflows. Each tool maps to a real operation, with no obvious filler or redundant entries.
The NONCE half covers the full lifecycle well: spec, mine, mint_packet, verify, info, census, and get_piece. The KOINE half covers discovery, provenance, listings, and verification, but the only acquisition route is external Seaport fulfillment, with no KOINE purchase or fulfillment packet equivalent to nonce_mint_packet—a minor but real gap.