list_validation_rulesLists all validation rules available to the IFC validator, including each rule's ID, category, severity, and default status, to help choose rules or explain checks.
List every rule validate_ifc can run: its id, category, severity and whether it is on by default. Use it to pick rules for validate_ifc or to explain what a rule checks.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint and openWorldHint=false already declared, the description adds value by disclosing the shape of the returned records (id, category, severity, default-enabled) and that the list covers the built-in rule catalog. It stops short of stating whether the list can change between calls or how large it is.
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?
Two sentences with no waste: the first states what is listed and what comes back, the second states why you would call it. The return-field list is front-loaded before the usage advice.
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?
There is no output schema, so the description carries the burden of describing return values — it does so by naming the four fields. Combined with read-only annotations and a zero-parameter schema, an agent has everything needed to call it correctly.
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?
The tool takes zero parameters, so the baseline is 4; there is nothing the schema could document and the description correctly implies a parameterless full dump. It adds no misleading filter semantics.
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 and resource ('List every rule validate_ifc can run') and immediately enumerates the fields returned (id, category, severity, default-on). It also names the sibling tool whose rule set is being listed, so the agent can distinguish it from validate_ifc or check_ids.
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?
It gives two concrete use cases: pick rules to pass to validate_ifc, or explain what a rule checks. That is clear positive guidance, though it does not state when not to call it (e.g. that it is unnecessary if you already know the rule ids).
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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