This record as markdown: /tools/100xprompt-chitta/context-timeline.md
What context_timeline does on Chitta
AI agents call context_timeline to retrieve information from Chitta without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why context_timeline is rated Low
This tool retrieves or reasons over time-based information from the memory system without modifying, deleting, or executing external operations. It is a read-only operation that queries existing memory data organized temporally.
From the tool's definition Tool name 'context_timeline' and description 'Reason over TIME using the memory' indicate a query/retrieval operation that accesses stored temporal data within the knowledge-graph and vector memory system.
Attacks that exploit this kind of access
The rule that runs context_timeline safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Chitta, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For context_timeline, this is the rule to start with:
context_timeline is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Chitta, apply this rule, and every context_timeline call is checked against it from then on.
Questions about context_timeline
Reason over TIME using the memory. It is categorised as a Read tool in the Chitta MCP Server, which means it retrieves data without modifying state.
Register the Chitta MCP server in PolicyLayer and add a rule for context_timeline: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Chitta. Nothing to install.
context_timeline is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the context_timeline rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for context_timeline. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
context_timeline is provided by the Chitta MCP server (@100xprompt/chitta). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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