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ykovenskiy-hub

Purl MCP Server

get_debug_logs

Retrieve recent debug log entries from a live play session to verify engine actions like inputs, errors, or audio. Enable domains first, then filter by type, domain, or timestamp.

Instructions

Read recent debug log entries from the running play session. Useful for verifying what the engine saw after a test action (input received? error fired? audio playing?). Only entries for currently-enabled domains exist in the buffer — call set_debug_domains first to enable categories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional: max entries to return (default 200, returns most recent).
sinceNoOptional: only return entries with timestamp >= this (ms since epoch). Use Date.now() before a test action, then read entries with since=<that timestamp>.
typesNoOptional: filter by entry type (summary, log, error, domain). Empty/omitted = all types.
domainsNoOptional: filter to entries from these domains (collision, movement, follow, dodge, physics, zone, camera, mask, input, audio, errors, log). Empty/omitted = all domains.
Behavior4/5

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

With no annotations, the description carries the transparency burden. It reveals that only entries for currently-enabled domains exist in the buffer and that set_debug_domains must be called beforehand, adding useful behavioral context. It doesn't discuss return format or buffer limits, but the 'Read' verb and parameter schema cover basic expectations.

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 three sentences, front-loaded with the action, then a usage example, then a crucial prerequisite. No wasted words.

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 tool is a read-only log fetcher with no required parameters; the description covers the main scenario and prerequisite. The absence of an output schema means return values aren't explained, but the name and filters imply entry contents. Minor gap.

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?

All 4 parameters are fully described in the schema, so the description adds no additional semantic detail beyond the schema. Baseline of 3 applies per the high schema coverage.

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 uses the specific verb 'Read' with resource 'recent debug log entries from the running play session,' clearly distinguishing it from sibling tools like clear_debug_logs and set_debug_domains by stating its read-only nature and domain prerequisite.

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?

Provides a concrete use case ('verifying what the engine saw after a test action') and an explicit prerequisite ('call set_debug_domains first to enable categories'). However, it doesn't explicitly compare with alternatives or state when not to use it, though the read operation is self-evident.

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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