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XDaLa Workflow Builder

by io.github.xgr-network

Trace native XGR value provenance

trace_xgr_value_flow
Read-onlyIdempotent

Read-only native-XGR value-flow analysis starting from one transaction. Use model="possible" for conservative attribution ranges or model="proportional" for haircut attribution. Native XGR has no per-coin identity, so results are provenance models rather than proof that a specific coin moved. maxTransfers and maxHops accept a number or "all"; "all" is still bounded by Explorer server safety caps and reports truncation explicitly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNopossible returns attribution ranges; proportional applies a haircut/share model.
txHashYes0x-prefixed transaction hash to inspect or resolve.
maxHopsNoMaximum propagation hops from the seed recipient, or "all" subject to server safety caps.
amountWeiNoOptional amount of the seed transaction value to trace in wei. Defaults to the full native XGR value of the seed transaction.
maxTransfersNoMaximum propagated transfers to return, or "all" to continue until exhaustion subject to server safety caps.
minAttributedWeiNoIgnore branches whose possible/attributed amount falls below this wei threshold.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesStructured result data returned by the XGR MCP gateway.

TDQS

A4.7/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations: it warns that native XGR lacks per-coin identity, making results provenance models rather than proof, and clarifies that 'all' is bounded by server safety caps with explicit truncation reporting. This goes well beyond the readOnly/idempotent hints.

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 compact, front-loaded with the core purpose, and each sentence earns its place. It covers purpose, model selection, a critical limitation, and truncation behavior in four sentences without unnecessary fluff or repetition.

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?

For a complex tool with six parameters and an output schema, the description is thorough. It defines the tool's scope, explains model choices, discloses result limitations, and addresses edge-case behavior for 'all' in maxHops/maxTransfers. Since an output schema exists, return-value details are not required, and nothing important is missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds interpretive value by explaining the meaning of 'possible' vs 'proportional', emphasizing the provenance-model caveat, and noting that truncation is explicitly reported for 'all'. While some details repeat schema text, the caveats and model-choice semantics are not fully captured in schema descriptions, justifying a 4.

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 a specific action ('read-only native-XGR value-flow analysis') and the resource ('starting from one transaction'). It distinguishes the tool's provenance focus from the sibling tool 'trace_xgr_transaction', which likely handles transaction-level details, by emphasizing 'value provenance' and 'provenance models'.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use the two models ('possible' for conservative attribution ranges, 'proportional' for haircut attribution) and notes limitations of the results. However, it does not explicitly compare with sibling tools or state when not to use this tool, so it falls short of full when/when-not guidance.

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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TDQS

B3.2/5.0
Disambiguation2/5

There are many overlapping session-listing tools (list_xdala_sessions, get_recent_xdala_sessions, find_latest_xdala_session, list_xdala_session_ids, get_latest_session_payload) and duplicate validation tools (validate_xdala_bundle is an alias for validate_xgr_multibundle). Descriptions help but boundaries are still unclear.

Naming Consistency4/5

The verb_noun snake_case pattern is consistent across nearly all tools (get_, list_, create_, cancel_, validate_). Minor inconsistencies include the alias validate_xdala_bundle and interchangeable verbs like get_ vs read_ vs resolve_ for similar read operations.

Tool Count1/5

With 95 tools, this is far beyond the 25+ threshold for 'too many'. While the domain is broad, the sheer number makes the tool surface unwieldy and difficult for an agent to navigate.

Completeness4/5

The tool set covers a wide range of operations: handoffs, session queries, transaction exploration, contract reads, validation, gas requests, and purchases. Minor gaps exist (e.g., no direct workflow editing tools), but overall the surface is remarkably complete.

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