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Pack vault context for an AI question (token-budgeted)

obsidian_context_pack
Read-onlyIdempotent

Retrieve top relevant notes from your Obsidian vault based on a question, combine with backlink summaries and recent daily notes, then pack into a token-budgeted markdown bundle ready for AI chat.

Instructions

Given a question, retrieve the top relevant notes (via hybrid search), gather backlinks summaries + optionally recent dailies, deduplicate, pack to a token budget, return a single ready-to-paste markdown bundle. Saves the agent ~5 separate tool calls; produces a coherent context blob you can paste into any AI chat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesTopic or question to gather context for
budget_tokensNoApproximate token budget (default 4000, ~4 chars/token)
folderNoRestrict retrieval to this folder (vault-relative)
include_backlinksNoInclude 1-line backlink summaries for top-3 notes (default true)
recent_dailiesNoInclude the last N daily-format notes (YYYY-MM-DD basenames). Default 0 (off).
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the tool is safe and idempotent. The description adds behavioral details: uses hybrid search, gathers backlinks, optionally dailies, deduplicates, and packs to a token budget. It does not contradict annotations and provides useful process transparency beyond safety.

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

Conciseness5/5

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

Description is two sentences: first lists the step-by-step process, second explains the benefit. It is front-loaded, no filler, every sentence earns its place. Minimally viable length.

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?

Tool has 5 parameters, no output schema, but annotations are present. Description explains the overall flow and output (Markdown bundle). It does not detail exact composition of the output or mention default values for include_backlinks and recent_dailies, but given high schema coverage and no output schema, it is reasonably complete for an agent to understand usage.

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% (all parameters have descriptions). The tool description does not add new semantic meaning beyond the schema; for example, 'budget_tokens' schema already says 'Approximate token budget (default 4000, ~4 chars/token)' and the description only mentions 'token-budgeted' in the title. With high coverage, baseline is 3.

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?

Title 'Pack vault context for an AI question (token-budgeted)' and description clearly state the tool's purpose: given a question, retrieve top notes, gather backlinks and dailies, deduplicate, pack to a token budget, and return a Markdown bundle. It distinguishes from siblings like obsidian_search, obsidian_get_backlinks, and obsidian_read_note by combining multiple operations into one.

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?

Description says 'Saves the agent ~5 separate tool calls; produces a coherent context blob you can paste into any AI chat.' This implies use when you need compact context for an AI question, and that it replaces multiple separate calls. However, it does not explicitly state when not to use it or list alternatives.

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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