Rolling aggregate money-flavor statistics (default 1 hour window): asset class, chain class, flow class distributions, plus arb/refused/non-USDC ratios. Drives the CLEAN-MONEY gate.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the rolling 1-hour window and the specific aggregates, but does not state whether the tool is read-only, potential side effects, or return format. The phrase 'default 1 hour window' hints at configurability contradicted by the empty schema, creating slight confusion.
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. It front-loads the main purpose, lists specific content, and includes the gate context with no unnecessary words.
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?
The description covers the key output dimensions and ties the tool to a specific business process (CLEAN-MONEY gate). Given the lack of an output schema, it is reasonably complete, though it could clarify the return format and the distinction from morph_money_flavor_probe.
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?
There are zero parameters, so the schema is fully covered. The description's mention of a 'default' window implies a parameter that does not exist, which could mislead agents, but per the rubric for 0 parameters, baseline is 4.
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 computes rolling aggregate money-flavor statistics with specific dimensions (asset class, chain class, flow class distributions, ratios). The phrase 'Drives the CLEAN-MONEY gate' adds purpose context. However, it does not explicitly differentiate from the sibling tool morph_money_flavor_probe, only implying distinction through the word 'aggregate'.
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 for the CLEAN-MONEY gate but gives no explicit guidance on when to use this tool vs. alternatives, nor any exclusions. It does not mention sibling tools like morph_money_flavor_probe, leaving the choice to the agent without clear criteria.
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 target distinct resources (broods, supermodels, money flavor, audit, carousel). The pair morph_money_flavor_probe and morph_money_flavor_stats are close but distinguished by scope (latest window vs rolling stats). Similarly, morph_brood_conversion and morph_brood_conversion_leaderboard are related but serve different purposes. Overall, minimal overlap.
All tools share the 'morph_' prefix, but the structure after is inconsistent: some use verb+noun (morph_get_identity, morph_list_supermodels), others use noun+descriptor (morph_brood_conversion, morph_money_flavor_probe), and some are just nouns (morph_carousel). This mixed convention makes the naming pattern less predictable.
With 14 tools, the count is appropriate for the server's broad scope covering supermodels, broods, money flavor, audit, and scans. Each tool has a distinct purpose, and the number is within the ideal range.
The server provides comprehensive read-only coverage for analytics: listing/fetching supermodels, brood conversion metrics, audit logs, money flavor stats, and dry-run scans. However, it lacks write operations or a way to act on pending approvals, which may be intentional but leaves a gap for full lifecycle management.