Run the spawn-monitor scan: detect supermodels eligible for new brood spawns based on conversion gaps, opportunity surface, and saturation. READ-ONLY — does not actually spawn.
| 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 the full behavioral burden. It explicitly states 'READ-ONLY — does not actually spawn,' which is a key safety disclosure. It also explains the detection logic (conversion gaps, opportunity surface, saturation). However, it does not describe the return format or any other side effects, though the read-only nature is the most critical behavior.
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 concise sentences. The first states the main purpose, and the second adds the crucial read-only note. No wasted words, and the structure is front-loaded with the verb.
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 0-parameter, read-only scan with no output schema, the description is fairly complete. It explains what the tool detects and that it is safe. The lack of return-value guidance is a minor gap, but the tool's name and the 'detect' wording imply the output is the eligible supermodels.
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 schema is empty. Per the rubric, the baseline is 4. The description does not need to explain any parameters, and it adds no param-related detail, which is appropriate.
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 function: 'Run the spawn-monitor scan: detect supermodels eligible for new brood spawns based on conversion gaps, opportunity surface, and saturation.' It uses a specific verb ('detect'), names the resource ('supermodels'), and distinguishes this scan from siblings like culling or approval tools.
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 the tool should be used to check supermodel eligibility for spawns, but it does not explicitly state when to use it versus alternatives or provide exclusions. Sibling tools like morph_auto_cull_scan exist but are not referenced.
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.