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annotate_hook_trace

Decodes and annotates hex traces from Xahau hook execution, identifying XFL floats, int64, UInt32, dates, account IDs, and hashes while preserving raw data.

Instructions

Annotate the trace[] array from an execute_hook result. Each entry is "label: HEXVALUE" (the hook's trace() memory dump). Decodes each blob by byte-width: 8-byte → canonical XFL float (definite) else int64 (both endians) + native-drops reading; 4-byte → UInt32 (both endians) + Ripple-epoch ISO date if in range; 20-byte → candidate account-id → r-address (possible, since arbitrary bytes can coincidentally encode); 32-byte → possible tx/hook hash (heuristic); other widths → raw blob. The raw hex is ALWAYS preserved as the primary field; nothing is suppressed; confidence is 'definite' only for canonical XFL. Fully offline, no network.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
traceYestrace[] from an execute_hook result; each element "label: HEXVALUE"
Behavior5/5

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

The description thoroughly discloses behavioral traits: decoding rules by byte-width, confidence levels ('definite' only for canonical XFL), that raw hex is always preserved, and that it is fully offline with no network calls. This is exceptionally transparent, especially since no annotations are provided.

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 but well-structured, starting with the overall purpose and then detailing decoding rules. While slightly lengthy, each sentence adds value and the information is logically organized. It could be slightly tightened without losing clarity.

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 the tool has a single parameter and no output schema, the description fully explains what the tool does, how it processes the input, and what the output will contain (e.g., decoded values with confidence). It covers all necessary behavioral aspects for an agent to correctly invoke it.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds crucial semantic detail beyond the schema: it explains that each trace element is 'label: HEXVALUE', how each byte-width is interpreted (XFL float, int64, UInt32, Ripple-epoch date, account-id to r-address, tx/hook hash, raw blob), and that confidence varies. This is far more informative than the schema alone.

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 that the tool annotates the trace[] array from an execute_hook result, specifying its purpose of decoding hex blobs into human-readable formats. It uses a specific verb (annotate) and resource (hook trace), and is distinct from sibling tools which are about different aspects of Xahau.

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 that this tool should be used after execute_hook to decode trace output, but it does not explicitly state when to use it versus alternatives or when not to use it. No exclusions or alternative tools are mentioned, leaving usage guidance implicit.

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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