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vola-trebla

playwright-trace-decoder-mcp

by vola-trebla

analyze_race_conditions

Identify potential race conditions in Playwright traces by flagging network requests still in-flight when user actions fire.

Instructions

Detects potential race conditions by finding network requests that were still in-flight when a user interaction action fired. Returns flagged actions with pending requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trace_pathYesAbsolute path to trace.zip, or a URL (https://) to download it from
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. It explains the detection methodology and gives a basic idea of the return value ('flagged actions with pending requests'), but it does not disclose side effects, input constraints beyond the schema, potential failure modes, or performance considerations. For a read-only analysis tool, more behavioral context is expected.

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 concise and well-structured: two sentences front-load the core purpose and then provide the key output detail. No redundant information or filler.

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?

With no output schema, the description partially explains the return value ('flagged actions with pending requests') but lacks detail about the structure or format of that output. Given the tool has only one parameter and is specialized, the description is minimally complete but leaves gaps about the exact nature of flagged actions.

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 schema describes the sole parameter 'trace_path' completely (100% coverage), including both file and URL options. The description adds no additional parameter semantics, so the baseline of 3 applies per the rubric.

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's purpose with a specific verb ('Detects') and resource ('potential race conditions'), and explains the mechanism (network requests in-flight when user interaction fired). This distinguishes it from sibling tools like get_filtered_network_logs or correlate_dom_and_network.

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 when investigating race conditions but does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. It provides contextual hints but no explicit guidance on tool selection.

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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