love_plot

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds only the 'before/after' contrast, which hints at the comparison dimension but does not disclose behaviors like automatic PS weight computation when weights=None, threshold lines, or as_handle caching—though these are partially in schema fields.

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 single-sentence description is extremely concise and front-loaded with the core concept. However, it is arguably under-specified rather than efficiently complete—though for a purportedly simple visualization, the brevity is appropriate and earns a good score.

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 14 parameters and two possible input workflows (raw data vs. result_id), a one-sentence description is inadequate. There is no orientation on when to supply data_path vs. result_id, how weights interact with ps_method, or what the output payload contains—matters an agent would need to call this tool 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?

Schema description coverage is 100%, so the schema fully documents all 14 parameters. The description itself adds no parameter-level meaning, which is acceptable under the baseline but does not compensate or enrich the semantic understanding of how parameters like data_path, result_id, treatment, and covariates relate to each other.

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 clearly identifies the tool's output: a 'dot plot of standardized mean differences before/after', which is the canonical love plot. The verb and resource are specific enough to distinguish it from many unrelated tools, though it does not explicitly differentiate from close siblings like balanceplot, ps_balance, or psplot.

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?

The description gives no guidance on when to use love_plot relative to the many sibling plotting/diagnostics tools, nor does it explain typical scenarios (e.g., after matching/weighting, with a fitted result). An agent must infer from the name and schema alone, which is insufficient for a large tool catalog.

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