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context_pack

Read-only

Assemble all relevant context for answering a question in a single call by bundling ranked excerpts, linked notes, and source paths within a byte budget.

Instructions

Assemble everything needed to ANSWER a natural-language question in one call, under a strict byte budget (default 2048): ranked excerpts, linked neighbor notes (backlinks/outlinks) with one-line summaries, and follow-up source paths. Use search to locate notes and query_notes for metadata filters; use context_pack when you want answer-ready context without multiple round-trips. Empty excerpts with confidence "none" or "low" means the vault lacks coverage — do not infer content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language question or topic.
budgetBytesNoHard cap on response JSON bytes (256–16384, default 2048).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.17

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description adds critical behavioral disclosure: the byte-budget mechanism, the three output components, and especially the empty-result semantics ("Empty excerpts with confidence 'none' or 'low' means the vault lacks coverage — do not infer content"), which prevents an agent from hallucinating answers. No contradiction with annotations.

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?

Three dense sentences, each with a distinct job: what it returns, when to use it, and how to interpret empty results. Purpose is front-loaded and there's no fluff, though the middle sentence could arguably be split for skimmability. Minor polish would push this to 5.

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?

With no output schema, the description carries full responsibility for explaining return values and edge cases, which it does thoroughly: outputs (ranked excerpts, summaries, source paths), budget behavior, and the empty-coverage case are all disclosed. An agent has everything needed to call this tool correctly, so nothing critical is missing.

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

Parameters3/5

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

Schema description coverage is 100%, and the description's parameter-related details (byte budget default, natural-language query) are already present in the input schema's field descriptions. The description reinforces but does not extend the schema, so it sits at the baseline of 3 for high coverage.

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 opens with a specific verb and resource: "Assemble everything needed to ANSWER a natural-language question in one call," then enumerates exact outputs (ranked excerpts, linked neighbor notes with one-line summaries, follow-up source paths). This differentiates it from siblings by promising answer-ready context "without multiple round-trips," which no sibling claims.

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 routes to alternatives: "Use search to locate notes and query_notes for metadata filters; use context_pack when you want answer-ready context without multiple round-trips." Names two siblings and the precise condition that selects this tool, making the when-versus-when-not distinction unambiguous.

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