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temporal_event_stream_deduplicator

Eliminate duplicate messages in high-throughput streaming agent logs using a sliding-window Bloom filter, with zero disk I/O.

Instructions

Sliding-window Bloom filter and event deduplicator for high-throughput streaming agent logs, eliminating duplicate messages with zero disk I/O. (0.030 USDC on Base L2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesInput parameters or JSON string payload for the tool execution
paymentSignatureNoBase L2 USDC micropayment signature or transaction hash for x402 settlement

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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 disclosure. It mentions 'zero disk I/O' (implying memory-only operation) and a cost figure, but it does not disclose whether the tool is stateful, whether it mutates input, what side effects occur, or that a payment signature is required. The payment aspect is ambiguous—it states a cost but doesn't confirm the paymentSignature parameter is mandatory or how it is used.

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

Conciseness5/5

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

The description is a single sentence that packs the core purpose, method, use case, and a notable property (zero disk I/O) efficiently. It also includes the cost, which is relevant for an agent deciding on invocation. There is no filler or redundancy.

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

Completeness2/5

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

The tool is moderately complex (a Bloom filter deduplicator) with no output schema. The description does not explain what the tool returns, how to construct the payload, or how the payment mechanism works. Without annotations to cover safety or side effects, the description leaves critical gaps that an agent would need to know to invoke it correctly and interpret results.

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

Parameters3/5

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

The schema covers 100% of the parameters, so the baseline is 3. However, the description adds no meaning beyond the schema. The payload description in the schema is generic ('Input parameters or JSON string payload'), and the tool description does not clarify what format or fields the payload should contain for this deduplicator, nor what the paymentSignature represents beyond the schema's generic phrasing.

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 states a specific verb (deduplicates) and resource (event stream for agent logs), and even specifies the method (sliding-window Bloom filter). It distinguishes itself from siblings like 'deduplicate_embeddings_cosine' by targeting streaming logs rather than embeddings. The purpose is unmistakable.

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

Usage Guidelines3/5

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

The description implies the intended use case ('high-throughput streaming agent logs') but does not explicitly state when to use it vs. alternatives, nor any prerequisites or exclusions. It offers no guidance on when not to use it, leaving the agent to infer applicability from the 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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