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context_rules_set

Configure context injection rules in Kratos-MCP to optimize memory management for AI coding tools. Adjust parameters like memory age, importance thresholds, and deduplication to enhance codebase context retrieval and accuracy.

Instructions

Update context injection rules

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptImportanceThresholdNoConcept importance threshold
dedupeThresholdNoDeduplication threshold
maxMemoryAgeNoMax memory age in milliseconds
minImportanceNoMinimum importance threshold
pathBoostMultiplierNoPath matching boost multiplier
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update' implies a mutation, but the description doesn't specify if this requires special permissions, what the effects are (e.g., immediate application, persistence), or any side effects like rate limits or data changes. This is a significant gap for a mutation tool with zero annotation coverage.

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

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words, making it appropriately concise. However, it could be more front-loaded with critical details (e.g., specifying it's for configuring context injection behavior), but overall, it's well-structured for its brevity.

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

Completeness2/5

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

Given the complexity of a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what context injection rules are, how updates are applied, or what the expected outcome is, leaving significant gaps for an AI agent to understand and use the tool effectively.

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%, so the schema already documents all five parameters with clear descriptions. The description adds no additional meaning beyond what's in the schema, such as explaining how these parameters interact or affect context injection. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Update context injection rules' clearly states the action (update) and target (context injection rules), which is better than a tautology. However, it lacks specificity about what context injection rules are or what they control, and it doesn't differentiate from sibling tools like 'context_rules_get' or 'context_preview', leaving the purpose somewhat vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, dependencies, or when not to use it, and with siblings like 'context_rules_get' and 'context_preview', there's no indication of how this tool fits into the workflow or differs from them.

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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