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Mobai-read

SciTrace MCP Server

by Mobai-read

build_trace

Record a reasoning step from agent execution, including type, parent ID, and artifacts, to build a structured DAG trace for persistent analysis.

Instructions

Record a reasoning step from the agent's execution. Each step has a type (hypothesis/experiment/analysis/conclusion/verification/backtrack), an optional parent_id to build a reasoning DAG, and optional artifact file paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesReasoning step type
step_idYesUnique identifier for this step
summaryYesOne-line summary of what this step did
trace_idYesIdentifier for the overall trace/experiment
artifactsNoOptional list of associated file paths
parent_idNoOptional parent step ID for DAG construction
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that the tool 'records' a step but does not disclose side effects such as whether the step is appended, overwritten, persisted immediately, or whether an existing trace is required. It also omits any mention of return values or failure modes, providing minimal insight beyond the input schema.

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 two concise sentences with no filler content. It front-loads the core action ('Record a reasoning step') and then efficiently summarizes the optional fields, making it appropriately sized and well-structured.

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

Completeness3/5

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

The description adequately covers the tool's write behavior and input structure for basic use, but it leaves gaps regarding the lifecycle of a trace (e.g., whether the trace must already exist) and the relationship to the sibling query_trace. No output schema exists, so the description should provide more context about what happens after recording, which it does not.

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 input schema provides descriptions for all six parameters, achieving 100% coverage. The description adds some context by mentioning that parent_id builds a reasoning DAG and artifacts are file paths, but these largely mirror the schema descriptions. Since the schema handles the parameter semantics well, the baseline score of 3 is appropriate.

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 uses the specific verb 'Record' with the resource 'a reasoning step from the agent's execution', and explicitly enumerates the step types and structural elements (parent_id, artifacts). This clearly differentiates it from the sibling query_trace, which is a read-oriented tool.

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 gives context ('from the agent's execution') implying when the tool should be used, but it lacks explicit 'when not to use' guidance or any mention of the sibling query_trace as an alternative. No exclusions or prerequisites are stated, so the usage guidance is only 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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