Machine-readable, append-only signal track record summary (6100+ timestamped signals archived; ~1600 have measured 24h outcomes, the rest still pending or unmeasured — see the actual counts in the response).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral context. It discloses that the store is append-only, provides scale (6100+ signals archived), and explains that only ~1600 have measured outcomes while the rest are pending or unmeasured. It does not describe the response format, but it does direct the agent to the response for exact counts.
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 entire description is one compact sentence with no wasted words. Key qualifiers are front-loaded, and the parenthetical data about signal counts and outcome statuses is dense but relevant.
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 parameterless summary tool, the description provides strong context: it states the nature of the data, scale, measurement status, and where to find exact counts. It could be slightly more explicit about the response shape, but it is sufficient for an agent to understand what the tool does.
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, so the description correctly does not need to document parameter behavior. The baseline for a parameterless tool applies, and the description adds relevant context about what the response contains.
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 identifies a specific resource: a signal track record summary, with useful qualifiers like 'machine-readable' and 'append-only'. It is clear what the tool covers, though it lacks an explicit verb such as 'returns' or 'fetches', and does not distinguish itself from sibling tools by name.
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?
There is no explicit guidance on when to use this tool versus the sibling tools, such as recent_events or verify_claim. The usage is only implied by naming the resource area, not by stating conditions or alternatives.
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 actions (build a swap, check a mint, verify a claim, fetch pricing), and the descriptions make boundaries clear. The main risk is mild confusion between check_mint/score_mint and copy_signals/recent_events, as both pairs sit in adjacent signal/safety territory, but they are not interchangeable.
Most names follow a verb_noun pattern (build_swap, check_mint, score_mint, verify_claim, track_record). guard_pricing and recent_events break that pattern slightly, but the naming remains predictable and readable overall.
Nine tools is well within the ideal range and each tool earns a place in the safety/signal/trading workflow. It is neither bloated with near-duplicates nor too thin to define a useful server.
The server covers a coherent lifecycle: discovery (recent_events/copy_signals), safety and validation (check_mint/score_mint/verify_claim), execution (build_swap), and outcome auditing (track_record). Minor gaps exist, such as an EVM swap builder to complete the Robinhood check path, but the core workflow is usable.