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memorydetective

Analyze allocations from a .trace bundle

analyzeAllocations

Parse Allocations .trace files to obtain per-category memory aggregates, top allocators by size and count, and a one-liner diagnosis of the dominant allocator.

Instructions

[mg.trace] Parse the allocations schema from a .trace recorded with the Allocations Instruments template. Returns per-category aggregates (cumulative bytes, allocation count, lifecycle = transient/persistent/mixed), top allocators by size and by count, and a one-liner diagnosis identifying the dominant allocator.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tracePathYesAbsolute path to a `.trace` bundle recorded with the Allocations template (`xcrun xctrace record --template Allocations --attach <app|pid>`).
topNNoReturn the top N allocators by aggregated size (default 15).
minBytesNoFilter out individual allocations smaller than this size in bytes (default 0). Use 1024 to focus on >1KB allocations.
outputFormatNoResponse format. Omitted or `json` (default, preserves v1.8 behavior) returns JSON.stringify of the result. `markdown` renders a human-readable view of the same data. `both` returns both content items in one response, so a client can display markdown to the user and parse JSON for the agent loop without a second call. `verify-fix-table` (v1.10, applies to `analyzeAbandonedMemory` and `diffMemgraphs`) emits a focused 4-column markdown comparison table (Class | Before | After | Delta) of the actionable rows; other tools fall back to `markdown` for this value.
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It states it 'parses' and 'returns' data, implying a non-destructive read operation, but does not mention side effects, permissions, or performance characteristics. The description lacks detail on what happens if the trace is malformed or incompatible.

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 a single sentence that efficiently captures the tool's purpose and return values. However, it is dense and could benefit from a more structured format (e.g., bullet points) for better readability.

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 lists returned data (aggregates, top allocators, diagnosis) but does not explain the output structure in detail. With no output schema, the description should cover error conditions, prerequisites (e.g., trace must be from Allocations template), and how the diagnosis is formed. The tool is part of a large sibling set, but its niche is clear.

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?

Schema description coverage is 100%, so the schema already documents all parameters well. The description adds minor value by providing the xcrun command example for tracePath and clarifying outputFormat values, but does not significantly enhance understanding beyond the schema.

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?

Description clearly states it parses the 'allocations' schema from a .trace bundle recorded with the Allocations Instruments template. It distinguishes itself from siblings like analyzeMemgraph (which analyzes general heap) and analyzeMemoryFootprint (which focuses on footprint breakdown) by specifying the exact schema and template used.

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 usage for analyzing allocation data from a specific trace template, but does not explicitly state when to use this tool versus siblings like analyzeMemgraph, analyzeMemoryFootprint, or compareTracesByPattern. No when-not-to-use guidance is provided.

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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