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Session context pack

lore_context_pack

Orient at session start with vault stats, top entities, recent notes, valid facts, and optional topic search hits; then drill down using lore_search or lore_read_note.

Instructions

Progressive-disclosure primer: vault stats, top entities, recently modified notes, currently-valid facts, and (if topic given) top search hits. Call once at session start to orient; then drill down with lore_search / lore_read_note. Every list here is a sample: when one is cut, a truncated field names it with { shown, of, rest } and the tool to call for the remainder — so treat a missing item as "not in this sample", never as "not in the vault".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNooptional focus topic

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.38.0

TDQS

A4.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose an important behavioral trait — every list is a sample and truncated lists expose a { shown, of, rest } field pointing at the remainder tool — which is genuinely useful context about partial results. However, it says nothing about cost, latency, permissions, or whether the primer is a pure read, so the behavioral picture is incomplete rather than wrong.

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?

Front-loaded with the payload list, then usage, then the truncation caveat. Dense but every sentence carries distinct information; nothing restates the name or title.

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 and no annotations, the description must cover return contents and semantics — and it does, enumerating the sections and the truncation contract. An agent has everything needed to call it and interpret a partial result correctly.

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?

Schema coverage is 100% and only one optional parameter exists, so the baseline would be 3. The description earns one extra point by explaining the parameter's effect on output ('if topic given, top search hits'), which tells the agent what changes when topic is supplied — meaning beyond the schema's 'optional focus topic'.

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?

States a concrete verb and enumerates the exact payload: vault stats, top entities, recently modified notes, valid facts, and optional search hits. This is clearly distinguishable from siblings like lore_search (targeted hits) and lore_query_facts (fact lookup), which the description itself reinforces.

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 says when to use it ('call once at session start to orient') and names the follow-on alternatives ('then drill down with lore_search / lore_read_note'). No inference required about sequencing.

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