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omega_preload_context

Loads episodic context for a new task by combining RAG store, vault history, and sealed handoff data. Returns JSON with rag_matches, vault_history, handoff, and continuity type.

Instructions

Loads episodic context for a new task by querying the RAG store, vault history, and any sealed handoff. Call this once at the start of every new task before doing any work. Returns JSON with fields: rag_matches, vault_history, handoff, continuity_type (CONTINUATION | CONTEXT_SWITCH | FRESH_START).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesNatural-language description of the task to load context for, e.g. 'Fix authentication bug in login module'.
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 discloses the return format (fields like rag_matches, vault_history, handoff, continuity_type) and the call timing, but does not discuss side effects, idempotency, or error conditions. It is adequate but not rich.

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?

Two sentences, no waste. First sentence states purpose, second gives usage and return format. Front-loaded and efficient.

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?

Given a single parameter, no output schema, and no nested objects, the description covers the tool's action, parameters, return fields, and recommended call site. It is complete for the tool's simplicity, though it omits prerequisites like session state.

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% (the task parameter has a description). The description adds an example and specifies the type. This adds modest value beyond the schema, but does not compensate for missing parameter details like constraints.

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?

The description clearly states it 'Loads episodic context for a new task by querying the RAG store, vault history, and any sealed handoff.' This specific verb+resource combination distinguishes it from sibling tools like omega_rag_query or omega_vault_search.

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 explicitly says 'Call this once at the start of every new task before doing any work,' providing clear context. It does not list conditions when not to use or alternatives, but the instruction is direct and sufficient for an AI agent.

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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