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questdb

mcp-server-questdb

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get_recent_user_actions

Retrieve a digest of recent user edits to the QuestDB notebook to detect changes that may require agent reaction. Coalesces multiple typing events per cell into a single edited entry.

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 each 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

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses stateful behavior ('since your last fetch'), coalescing of typing events, and the session-start fallback. This is meaningful behavioral context beyond a simple read, though it does not mention output format or potential side effects.

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

Conciseness2/5

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

The description is unnecessarily long and not front-loaded. It starts with instructions about pairing and workspace state, which are not about this tool's own functionality. The core purpose appears in a later paragraph. The first two sentences do not earn their place for this tool's description.

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 simple tool with no parameters and no output schema, the description covers the essential aspects: what it returns, when to use it, and the coalescing behavior. It is reasonably complete, though the unrelated pairing instructions add noise rather than missing information.

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 has zero parameters and schema coverage is 100%. Per the rubric, baseline is 4 for 0-param tools. The description adds no parameter information, which is fine since there are none to explain.

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 description clearly states 'Return the digest of user edits to the notebook since your last fetch (or session start)' and explains the purpose as detecting changes. It distinguishes from siblings like get_workspace_state by focusing specifically on user edit digest. However, the purpose is not front-loaded; it is buried after unrelated pairing instructions.

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 gives explicit usage context: 'call get_workspace_state at the start of each notebook turn; the digest of edits since your last fetch is in get_recent_user_actions' and 'Use this to detect that the user changed something the agent might want to react to.' This provides clear when-to-use guidance, though it does not explicitly mention alternatives or when not to use.

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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