Recent closed trading signals with verified outcomes

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint annotation, the description discloses important behavioral traits: results are net of fees, slippage and funding; every signal has a SHA-256 receipt; and only live signals are included. It also states it includes a 24h summary (wins, losses, net bps), which adds return-context beyond the annotation.

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 sentences, front-loaded with the trigger condition, followed by key output details and caveats. Every sentence earns its place with no redundancy or filler.

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 parameters and no output schema, the description is remarkably complete. It covers what the tool does, what data it returns (outcomes, net bps, 24h summary), and critical distinctions (live only, never backtests). No additional context seems missing for an agent to select and invoke this tool appropriately.

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 schema coverage is effectively 100%. The description does not need to explain parameters and instead adds context about the returned data. This matches the baseline of 4 for a 0-parameter 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 explicitly states the tool returns recent closed LONG/SHORT signals from the ByKaranteli signal engine with verified outcomes (TP1, SL, TIMEOUT) and net basis-point results. It distinguishes from sibling tools by naming the specific engine and emphasizing 'live signals only, never backtests.'

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 gives direct trigger conditions: 'Call this when the user asks how the ByKaranteli signal engine is doing today, or wants recent closed LONG/SHORT signals.' It also provides a clear when-not: 'live signals only, never backtests.' However, it does not name alternative tools for backtest or historical queries, so it lacks that explicit alternative mention.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.