Skip to main content
Glama

get_context_at

Retrieve the exact screen state, OCR text, active window, and clipboard snapshot from a specified point in the recent past. Solves recalling what was on screen when referencing earlier events.

Instructions

Return screen + activity context from a specific point in the recent past.

Returns the captured screen state, OCR text, active window, and clipboard snapshot from the buffer entry closest to the requested timestamp.

USE WHEN: the user references something from earlier ("the error I saw 10 minutes ago", "what was on screen when I started this session") and you need to recall that exact state. NOT FOR: live state (use get_screenshot) or text-search across history (use search_history). ALTERNATIVES: get_recent for a chronological list.

BEHAVIOR: pure read. Returns the closest buffer entry within +/- 30 seconds of the requested point; raises if no entry exists.

PARAMETERS: minutes_ago: how many minutes back to look. Range 0-1440 (24h). Required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
minutes_agoYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, description fully discloses behavior: 'pure read', returns closest buffer entry within +/-30 seconds, raises if no entry exists. This covers safety and error conditions adequately.

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 labeled sections (USE WHEN, NOT FOR, etc.) and no redundant sentences. Slightly verbose but each sentence adds value. Could be tightened slightly without losing clarity.

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?

Given one parameter, no annotations, and an output schema (implied), description covers all essential: return content (screen state, OCR, active window, clipboard), timing constraint, error case. Sufficient for agent to invoke correctly.

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?

Single parameter minutes_ago with schema coverage 0% is fully described: 'how many minutes back to look. Range 0-1440 (24h). Required.' Adds meaning beyond schema type and required status.

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 clearly states 'Return screen + activity context from a specific point in the recent past' with specific verb and resource. Distinguishes from siblings like get_recent and search_history by emphasizing temporal point retrieval versus chronological list or text-search.

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 'USE WHEN' scenarios (user references something from earlier), 'NOT FOR' cases (live state, text-search), and 'ALTERNATIVES' (get_recent, search_history) with clear conditions.

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/ContextPulse/contextpulse'

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