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kage_context

Read-only

Validate memory health, recall relevant packets, and query the code and knowledge graphs to provide context for a coding task. Call at the start of every task.

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
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description correctly implies non-destructive behavior. It adds context about combined functionality and code graph answers, which is useful beyond the annotations.

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 with no redundancy, front-loaded with core purpose, then usage guidance. Every sentence adds value.

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 the tool's complexity (6 params, no output schema, many siblings), the description adequately covers purpose and usage. Lacks detail on return format but acceptable without output schema.

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%, so baseline is 3. The description does not add extra semantic context for individual parameters beyond what the schema already provides.

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 the tool is the primary entry point that validates memory health, recalls packets, and queries code/knowledge graphs. It distinguishes itself from sibling tools by aggregating multiple functions into one call.

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 advises to call at the start of every task and notes it reduces the need for a separate graph tool, providing clear when-to-use and implicit when-not-to-use guidance.

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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