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carloshpdoc

memorydetective

Classify ROOT CYCLEs against known patterns

classifyCycle

Matches each root cycle in a .memgraph file against 8 known antipatterns, returning pattern ID, confidence, and a fix hint for iOS memory leak investigation.

Instructions

[mg.memory] Match each ROOT CYCLE against a built-in catalog of 8 known antipatterns (TagIndexProjection cycle, ForEachState retention, Combine sink-store-self, Task-without-weak-self, NotificationCenter observer, viewmodel-wrapped-strong closure, UINavigationController host, _DictionaryStorage internal). Returns patternId, confidence, and a fixHint per cycle.

Pipeline: this is the killer tool — after the result, follow suggestedNextCalls which pre-translates each match to a Swift regex (swiftSearchPattern) + the captured class name (swiftGetSymbolDefinition). Discovery is data, not inference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to a `.memgraph` file.
maxResultsNoCap on classifications returned (default 20).
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states what the tool returns and its pipeline role, but does not mention whether it is read-only, destructive, or requires specific permissions. For a mutation-like analysis tool, this is a gap.

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 two paragraphs: first defines functionality, second guides pipeline usage. It is efficient but contains jargon; a slightly more structured format could improve clarity.

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

Completeness4/5

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

The description lists return fields and pipeline connections, compensating for the lack of output schema. However, it does not detail the structure of the return values beyond names, which may be sufficient given the context.

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 covers 100% of parameters with descriptions. The description adds no extra parameter information beyond listing return fields, so it meets the baseline but does not exceed it.

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 the tool matches each ROOT CYCLE against a catalog of 8 known antipatterns, using specific verbs like 'Match' and 'Returns'. It distinguishes itself from sibling tools like findCycles by focusing on classification against patterns, not just cycle detection.

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 instructions on what to do after using the tool ('follow suggestedNextCalls') and hints at a pipeline context. However, it does not specify when not to use this tool or directly compare to alternatives among the many siblings.

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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