How mining-pool attribution was established over a window: share proven by view key, claimed by pool API, inferred from coinbase, or unattributed. window in 1h,6h,24h,48h,7d.
| Name | Required | Description | Default |
|---|---|---|---|
| window | No | 24h |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the four attribution categories and the valid window options, which adds useful behavioral context. However, it does not mention output format, data freshness, or any limitations, leaving some behavioral aspects undocumented.
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 a single sentence that is front-loaded with the core purpose and wastes no words. It packs the attribution methods and window options efficiently without redundancy.
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 one-parameter tool with no output schema, the description provides the key conceptual information: what attribution provenance means and the available windows. It is nearly complete, though it could add a note about the return type or data structure to be fully self-contained.
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 only defines 'window' as a string with a default, but the description enriches it by listing the exact valid values (1h,6h,24h,48h,7d). Since schema coverage is 0%, this description effectively compensates and gives the agent the necessary enumeration.
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 explains that the tool shows how mining-pool attribution was established, listing the four attribution methods. It distinguishes itself from sibling tools like pool_distribution or pool_sources by focusing on provenance methodology, though it lacks an explicit verb like 'returns' or 'shows'.
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 guidance is given on when to use this tool versus alternatives such as pool_distribution or pool_sources. The description implies that it is used to understand attribution provenance, but does not state explicit use cases, prerequisites, or alternative comparisons.
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 grouped by prefix (network_, pool_, haveno_, reorg), but there is overlap: get_block vs search_block both return block details, price vs haveno_book both expose the current Haveno order book, and chain_fork_window, recent_orphans, and reorgs all touch chain-fork/orphan phenomena. The descriptions help separate them, but an agent could easily pick the wrong one.
The dominant convention is a domain_noun pattern (network_hashrate, pool_distribution, haveno_premium, chain_provenance), which is predictable and readable. Minor deviations like get_block, search_block, price, and reorgs break the pattern slightly, but not enough to cause confusion.
18 tools is on the heavier side but reasonable for a metrics/analytics server covering network health, mining pools, reorgs, blocks, and Haveno market data. A few endpoints could potentially be consolidated, but each tool generally earns its place.
The surface covers current network state, historical time series, block lookup, orphan/reorg analysis, pool attribution, and Haveno market data, which is solid for a Monero metrics server. Minor gaps like transaction-level lookup or a direct chain-range endpoint are absent, but agents can work around them using the provided block and fork-window tools.