list_rulesList stored rules, optionally filtered by domain and active status. Returns up to 100 rules, including each rule's id, condition, conclusion, domain and current confidence weight.
Args:
domain: Only rules in this domain. Empty = all domains.
is_active: 1 = only active rules, 0 = only inactive rules,
-1 (default) = both.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | ||
| is_active | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond annotations: a result cap ("Returns up to 100 rules") and the exact returned fields (id, condition, conclusion, domain, confidence weight). It could go further on pagination/ordering for results exceeding 100.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose sentence, then a returns sentence, then a scannable Args block. Structure is clean and each line earns its place, though the Args section is slightly verbose given only two simple params.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description responsibly summarizes return contents and the 100-rule cap, and both params are documented. For a read-only list tool this is nearly complete; only result ordering and behavior past the 100 cap are unstated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must carry the full burden, and it does: domain is documented with its empty-string default meaning ("Empty = all domains") and is_active with all three integer values (1/0/-1) and the -1 default. This fully compensates for the undocumented schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource ("List stored rules") and states the filtering scope. The resource "rules" is naturally distinct from sibling list_* tools like list_entities, list_goals, list_procedures, but no sibling is named explicitly for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied via the optional filters ("optionally filtered by domain and active status"), and the param docs clarify the semantics of each filter. However, there is no explicit guidance on when to use this over alternatives (e.g., query_world_model, cognitive_query) or any exclusions.
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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