update_log_parsing_rule

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't indicate whether this is a read-only or destructive operation, what permissions are required, whether changes are reversible, what happens to unspecified fields, or what the output contains. For a mutation tool with 7 parameters, this lack of behavioral context is critically inadequate.

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?

The description is a single, direct sentence with zero wasted words. It's appropriately front-loaded and efficiently communicates the core action, though this brevity comes at the cost of completeness. Every word earns its place by stating the essential function without fluff.

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?

Given the tool's complexity (7 parameters, mutation operation, no annotations) and the presence of an output schema, the description is severely incomplete. While the output schema may cover return values, the description fails to address behavioral traits, parameter meanings, or usage guidelines. For a tool that modifies log parsing rules—a potentially impactful operation—this leaves too many gaps for reliable agent use.

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%, meaning all 7 parameters lack documentation in the schema. The description provides no information about any parameters—not even the required 'rule_id' or what fields like 'grok', 'nrql', or 'lucene' represent. This forces the agent to guess parameter meanings, which is unacceptable for a tool with this complexity.

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 'Update an existing log parsing rule' is a tautology that restates the tool name with minimal elaboration. It specifies the verb ('update') and resource ('log parsing rule') but lacks specificity about what aspects can be updated or how this differs from sibling tools like 'create_log_parsing_rule' or 'delete_log_parsing_rule'. This provides only basic purpose information without meaningful 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing rule ID), compare it to sibling tools like 'create_log_parsing_rule' or 'test_log_parsing_rule', or indicate appropriate contexts. The agent must infer usage from the tool name alone, which is insufficient for informed selection.

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