seneschal_stats_overviewAggregate snapshot powering the public stats dashboard at stats.seneschal.space: total positions tracked, debt under watch, HF distribution histogram, top-10 at-risk borrowers, 30-day liquidations-per-day series, builder market share for 24h/7d/30d windows, and 10 most recent on-chain liquidations. One call returns everything needed to render the dashboard.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that this is an 'Aggregate snapshot' and that a single call returns all dashboard data, which implies a read-only, comprehensive behavior. It does not detail potential caveats like data freshness, but the description still communicates the essential behavioral trait of being a one-call bulk retrieval.
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, information-dense sentence that front-loads the core purpose ('Aggregate snapshot powering the public stats dashboard') and then enumerates the specific data points without unnecessary fluff. Every phrase adds value and it is not overly long.
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 no output schema, the description fully explains what is returned, listing all seven categories of data. It also states the single-call behavior. For a zero-parameter tool with no annotations, this is sufficient contextual completeness for an agent to select and invoke it correctly.
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 tool has zero parameters, and the baseline for a 0-param tool is 4. The description adds no parameter information (none needed), but it does clarify the scope of the data returned, which is the only relevant semantic for this stateless snapshot tool.
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 identifies a concrete aggregate snapshot tool with a specific name and scope, listing the exact contents (e.g., 'total positions tracked', 'top-10 at-risk borrowers'). It differentiates from siblings by presenting itself as the all-in-one dashboard data source, unlike granular tools like seneschal_recent_liquidations.
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 usage context ('powering the public stats dashboard', 'One call returns everything needed to render the dashboard') but does not explicitly name alternatives or state when NOT to use it compared to granular sibling tools. Thus it provides implied usage guidance rather than explicit exclusions.
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.
Tools are grouped by domain (board, private_watch, zecmon) with clear lifecycle separation, but seneschal_list_at_risk_borrowers and seneschal_list_borrowers overlap heavily, and the USDC vs crypto variants of private_watch_create/topup could be confused without careful reading.
Most tools follow a seneschal_<domain>_<action> pattern, but verb/noun order varies (get_borrower vs list_borrowers vs board_list) and outliers like seneschal_health and seneschal_q break the pattern.
At 35 tools, the server is definitely heavy, but it covers multiple distinct domains (DeFi data, privacy-chain monitoring, notice boards, payments), so the count is at the high end of reasonable rather than absurdly bloated.
Core workflows are well covered: borrower discovery/analysis, liquidations, private watch lifecycle, Zcash scanning lifecycle, board operations, and checkout invoices. Minor gaps like board deletion or watch cancellation exist but are workaround-able.