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funkyfunc

browser-dvr-mcp

by funkyfunc

get_session_summary

Get a token-efficient JSON summary of browser session telemetry with auto-generated alerts for errors and issues. Start here to identify problems before drilling down.

Instructions

THE PRIMARY OBSERVABILITY ENTRY POINT. Returns a token-efficient JSON summary of all telemetry captured since the session started.

INCLUDES: • Network stats: total requests, successes, failures, pending, slow requests • Console stats: log/warning/error counts • DOM mutation counts (structural vs attribute changes) • Interaction counts (clicks, typing, key presses, scrolls) • Cumulative Layout Shift (CLS) score • Auto-generated alerts for: server errors (5xx), client errors (4xx), failed requests, uncaught JS exceptions, slow requests

PROGRESSIVE DISCLOSURE WORKFLOW:

  1. Call get_session_summary — scan alerts for problems.

  2. If alerts flag issues, call query_session_telemetry to drill down into the specific category.

  3. Never dump all logs/network at once. Always start with the summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite no annotations, the description fully discloses the tool's behavior by enumerating all included telemetry categories (network, console, DOM, interactions, CLS, alerts). Notes that output is token-efficient, implying low overhead.

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?

Well-structured with bolded lead sentence, bullet list of contents, and a numbered workflow. Slightly verbose but all content is relevant and aids quick comprehension.

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?

Comprehensively covers what the tool returns and how to use it within a larger workflow. No output schema exists, but the description detail compensates fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist; schema coverage is 100% by default. Description correctly implies no input needed, adding no conflicting or redundant info.

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?

Clearly states the primary observability entry point and returns a token-efficient JSON summary of all telemetry. Distinguishes from sibling tool query_session_telemetry by positioning get_session_summary as the initial scan step.

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

Usage Guidelines5/5

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

Explicitly provides a progressive disclosure workflow: call get_session_summary first, then drill down with query_session_telemetry if alerts are triggered. Includes directive to never dump all logs/network at once.

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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