Skip to main content
Glama

get_console_since

Read-only

Retrieve Unity console entries logged after a specific mark. Supports filtering by severity level and keyword, with count-only option.

Instructions

Console entries after the watermark created by console_mark(). mark_id: string from console_mark() or bare float timestamp. level: optional filter ('error,exception,assert'). keyword: case-insensitive substring filter. count_only: return match count as string. count: max entries to return (default 500).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
levelNo
keywordNo
mark_idYes
count_onlyNo
Behavior4/5

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

The readOnlyHint annotation already declares safety, and the description adds meaningful behavioral details: mark_id can be a bare float timestamp, count_only returns a match count as a string, level filter accepts specific values, and keyword is case-insensitive. However, it does not describe the return format for normal results, leaving a minor gap beyond the annotation coverage.

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: the first line states the core purpose, followed by a compact list of parameters with explanations. Every sentence adds value, and there is no redundancy or fluff.

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 covers the main behavior and all parameters adequately, and the absence of an output schema means it should explain return values; it partially does with count_only but not for the default return of console entries. Minor gap, but overall sufficient for a straightforward read tool.

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?

With 0% schema description coverage, the description fully compensates by explaining every parameter's purpose and valid values (e.g., level filter options, keyword substring behavior, count_only return type, count default). This goes far beyond the schema's type/default information and is essential for correct invocation.

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 retrieves console entries after a watermark created by console_mark(), and it distinguishes itself from sibling tools like get_console and console_mark by referencing the mark mechanism. The noun phrase 'Console entries after the watermark' combined with the tool name leaves no ambiguity about the action and resource.

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 implies usage: first call console_mark() to get a mark_id, then use get_console_since to retrieve entries after that mark. It does not explicitly name alternatives like get_console for all entries, but the context is clear and sufficient for an agent to infer when to use this tool. A 5 would require explicit 'use X instead of Y' guidance, which is not present.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/german-krasnikov/unity-biome-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server