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get_diagnostics

Retrieve recorded console messages, runtime errors, and unhandled promise rejections with stack traces to diagnose UI issues. Filter by log level or time range for targeted debugging.

Instructions

Query recorded console messages, runtime errors, and unhandled promise rejections with stack traces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoLog level filter
sessionIdYesSession ID
toTimestampNoEnd timestamp
fromTimestampNoStart timestamp

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

A3.8/5.0
Behavior3/5

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

In the absence of annotations, the phrase 'Query recorded ...' communicates a read-only operation over historical data, which is meaningful behavioral context, and 'with stack traces' describes what is included. It does not, however, state side-effect-free behavior explicitly or describe boundaries such as lack of live capture, result limits, or missing-session behavior.

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?

A single front-loaded sentence with no filler; every phrase ('recorded', 'console messages', 'runtime errors', 'unhandled promise rejections', 'with stack traces') adds distinguishing meaning. It is appropriately concise for a diagnostic query tool.

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?

For a four-parameter query with full schema documentation, the description is nearly complete: it names the resource, indicates historical/recorded data, and notes stack traces. Since there is no output schema, it could be stronger by mentioning ordering, pagination, or return shape, but the core invocation context is covered.

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 four parameters; the description adds no new parameter-level meaning. It gives useful output context (console messages/errors/rejections) but does not explain timestamp formats or how the level filter interacts with the result set, leaving the baseline at 3.

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 uses a specific verb ('Query') and names an exact resource set: recorded console messages, runtime errors, and unhandled promise rejections, with stack traces. This distinguishes it from sibling tools like get_network_events and get_live_dom_snapshot, so an agent can tell what it does without inferring.

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 resource type implies when to use it (needing console/runtime diagnostic records), but there are no explicit when-to-use, when-not-to-use, or alternative routing statements. With many sibling tools present, this guidance is only implicit rather than stated.

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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