ass_check_overlaps

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

With no annotations, the description carries the full behavioral burden and discloses important traits: default layer-strict comparison, treatment of comments, tolerate_ms threshold, and ordering by start time. It could be stronger by explicitly stating the operation is read-only and has no side effects.

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 with the core action, followed by compact notes and a structured Args/Returns section. Every sentence adds useful context without padding.

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 lack of annotations and low schema coverage, the description supplies the needed behavioral and parameter context. It also redundantly documents the return shape, which is harmless because an output schema exists.

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 0%, so the description must explain all four parameters. Its Args section defines selection, doc_id, layer_strict, and tolerate_ms meaningfully, though selection remains somewhat underspecified regarding expected format.

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?

States a specific verb and resource: list overlapping pairs of lines, ordered by start time. The overlap focus clearly distinguishes it from general validation or QC siblings.

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?

Explains the key usage condition: layer_strict defaults to comparing only within the same layer because cross-layer coincidences are intentional, and comment lines are excluded. It does not explicitly compare against alternatives like ass_qc or ass_validate, but the context is clear.

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