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mcp-server-questdb

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get_recent_user_actions

Detect notebook edits the user made since your last fetch. Returns a coalesced digest of changed cells so the agent can react to user modifications.

Instructions

If notebook tools fail with BRIDGE_NOT_PAIRED, call get_pairing_credentials to begin pairing (the response includes a one-click URL to show the user; authentication runs in the browser, the bridge never sees credentials). Once paired, call get_workspace_state at the start of every notebook turn; the digest of edits since your last fetch is in get_recent_user_actions.

Return the digest of user edits to the notebook since your last fetch (or session start). Use this to detect that the user changed something the agent might want to react to. Coalesced — multiple typing events on the same cell collapse to a single 'edited' entry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose real behavioral traits: the digest window is 'since your last fetch (or session start)' and events are 'coalesced' so multiple typing events collapse to one 'edited' entry. It does not describe the empty/no-edit case or the digest's full shape, which is the main gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The actual purpose is buried in the second paragraph while the lead is a cross-tool pairing/workspace-state instruction that belongs to get_pairing_credentials and get_workspace_state rather than this tool. The relevant sentences are tight, but the front-loading is poor and the preamble doesn't fully earn its place here.

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 zero-parameter, read-only digest tool with no output schema, the description explains what it returns, when to call it, and its coalescing semantics, which is close to complete. Only the empty-result behavior and digest entry shape are left implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters and the schema is empty, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter confusion is possible.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The second paragraph states a specific verb and resource: 'Return the digest of user edits to the notebook since your last fetch.' It distinguishes itself from get_workspace_state (start-of-turn full state) and get_notebook_state, so an agent can tell them apart. The leading paragraph about pairing is off-purpose but the core function is unambiguous.

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?

It gives clear usage context: 'Use this to detect that the user changed something the agent might want to react to,' and situates itself relative to get_workspace_state at the start of every notebook turn. It lacks explicit when-not guidance, but the selection condition is reasonably clear.

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