get_rules

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the data source (rules.json) and corpus size (107), which is useful, but says nothing about whether all rules are returned by default, pagination/limits on a 107-item result, or permissions. Adequate but incomplete for a 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.

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

Three short sentences, front-loaded with what the tool returns and immediately followed by the routing condition. No sentence is redundant and nothing is buried.

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 and no annotations, so the description should ideally describe the returned rule shape or the unfiltered default behavior. It covers the lookup purpose and filters adequately, but an agent still cannot predict what a call with no arguments yields.

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 coverage is 100% with two enum-constrained params and descriptive text for all three filters. The description merely restates that category/severity/detector filtering exists, adding no syntax, default, or combination semantics beyond the schema, so the baseline 3 applies.

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 names a specific verb (Get) and resource (melta-ui prohibition rules from rules.json), gives the corpus size (107 total), and explicitly distinguishes the tool from its closest sibling check_rule. An agent can tell it apart from check_rule, search, and get_token without opening any schema.

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?

"Use this to retrieve manual/contextual rules that check_rule cannot auto-detect" gives a clear selection condition and names the alternative tool. It stops short of stating when not to use it (e.g. when searching for arbitrary content, where `search` applies), so it is clear context without explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.