Feed of $200k–$1m (core) or just-graduated $20k–$200k (early) tokens scored for $10m. Early is the 1% hunt: 99% of grads die before $200k. Uses volume/cap, FOMO cluster, whale hits, stock-route pairing, live LP. Research candidates, not orders.
| Name | Required | Description | Default |
|---|---|---|---|
| band | No | core | |
| minP | No | ||
| limit | No |
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?
With no annotations, the description carries the burden and does well: it discloses the scoring methodology (volume/cap, FOMO cluster, whale hits, stock-route pairing, live LP), explains the core/early graduation distinction, and warns that early candidates have a 99% failure rate. It also frames output as research rather than actionable orders.
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 compact and front-loaded with the core purpose. Each sentence adds relevant context, though the dense jargon (FOMO cluster, stock-route pairing, live LP) makes it less immediately scannable than it could be.
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?
There is no output schema, so the description should clarify what the returned feed looks like, but it does not. It also leaves 'minP' undefined and does not explain the 'all' band option. An agent could call the tool with defaults, but full correct invocation with non-default parameters is under-specified.
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 description coverage is 0%, so the description must explain the parameters. It does explain 'band' by defining core ($200k–$1m) and early ($20k–$200k), but it never explains 'minP' or 'limit'. 'limit' is self-evident, but 'minP' is cryptic and undocumented in both schema and description.
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 token feed: tokens in two market-cap bands scored for a $10m potential, which is more specific than a generic 'breakout' name. It distinguishes internal modes (core vs early) but does not explicitly differentiate this from the many talon_* siblings.
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 a research use with 'Research candidates, not orders' and explains the early band's risk profile, but it gives no explicit guidance about when to choose this tool over alternatives such as talon_alpha, talon_radar, or talon_scan. There are no when-not conditions beyond not treating output as orders.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.