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fahali_get_realtime_alerts

Retrieve real-time detection alerts clustered by symbol and thesis to reduce context consumption. Each cluster includes an evidence array and raw detection confidence.

Instructions

Get realtime detection feed clustered by (symbol, thesis). Each cluster represents one active thesis on one symbol with an evidence array of confirmations — reduces context consumption ~3-5x vs ungrouped rows. Each cluster's detectionConfidence is the engine's RAW detection confidence (0-1), NOT a calibrated hit probability or actionability — it is null when the alert carries none (never a fabricated 0.5). For judged reliability use fahali_get_track_record_scorecard; for the arbitrated read use fahali_get_market_verdict. Public data — no tier required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Discloses important behavioral details: detectionConfidence is RAW (not calibrated), can be null, and is never fabricated. No annotations are provided, so the description carries full burden and addresses it thoroughly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed and well-structured, beginning with purpose and benefit, then clarifying key fields and alternatives. Every sentence adds value, though slightly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters, no annotations, and no output schema, the description fully explains the tool's behavior, output structure, and related tools, making it complete for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist in the schema (0 params), so baseline is 4. The description does not need to add parameter info but explains the output structure, which adds value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get realtime detection feed clustered by (symbol, thesis)', which is a specific verb and resource. It distinguishes from sibling tools by explaining the clustering benefit and pointing to alternatives for reliability and arbitrated reads.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides when-to-use and when-not-to-use: 'For judged reliability use fahali_get_track_record_scorecard; for the arbitrated read use fahali_get_market_verdict.' Also notes 'Public data — no tier required', giving clear usage context.

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

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