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kage_context

Validates memory health, recalls relevant packets, and queries code and knowledge graphs in a single call. Call at the start of every task to integrate memory and graph context.

Instructions

Primary kage entry point. Validates memory health, recalls relevant packets, and queries both the code graph and knowledge graph — all in one call. Call this at the start of every task; it answers caller/usage questions from the code graph too, so you rarely need a separate graph tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_dirYesAbsolute path to the project root
queryYesThe task or question — used for both memory recall and code graph search
limitNoMax memory packets to return (default 5)
session_idNoOptional active agent session id for memory reconciliation
targetsNoOptional files the agent may edit or explain; used for risk context
changed_filesNoOptional changed files for pre-edit or PR risk context
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses multi-faceted behavior (memory health, recall, graph queries) but omits error handling, failure modes, or any side effects. Adequate but not detailed.

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 concise sentences. First provides core purpose, second gives usage guidance and alternative avoidance. No redundant or superfluous language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite being a complex tool with 6 parameters and internal operations, there is no output schema and the description does not explain return format or behavior. For a primary entry point, more detail on what the agent receives would be beneficial.

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 coverage is 100% with parameter descriptions already present. The description adds no new information beyond restating that query serves both memory and code graph purposes. Baseline score appropriate.

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 is the primary entry point that validates memory, recalls packets, and queries both code and knowledge graphs. It distinguishes from siblings by noting it answers caller/usage questions from the code graph, reducing need for separate graph tools.

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?

Explicitly says 'Call this at the start of every task' and suggests rarely needing a separate graph tool. Provides clear context for when to use, though does not exhaustively list when not to use or compare to all siblings.

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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