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

With no annotations, the description carries the full disclosure burden. It usefully scopes the operation (current-request lines only, structural validation plus counting, no verdict recomputation), which is real behavioral value, but it says nothing about what the tool returns (counts? per-line errors?), whether strict mode changes the response shape, or whether any state is written.

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, front-loaded with the core operation and followed by the key scope limitation. No filler, though the emphasis markup and the P3 reference add noise that an agent cannot act on.

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?

For a two-parameter tool with no annotations and no output schema, the description covers what it does and what it refuses to do, but leaves the response contract (counts, error reporting, strict-mode effect on output) unexplained. Adequate but with an obvious gap for an agent that needs to interpret results.

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 both json_lines and strict are already documented in the schema. The description adds only that json_lines must be passed within the current request, which is marginal beyond the schema's 'JSONL 行数组' wording.

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+resource: replay a trace from JSONL text, scoped to structural validation and counting. This distinguishes it from the sibling trace_export and from semantic/verdict tools, though the parenthetical '(结构校验 + 计数)' is the only thing separating it from a generic replay.

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 a clear exclusion: it only handles json_lines supplied in the current request and does not recompute verdicts (semantic replay is deferred to P3). However, it never names an alternative sibling (e.g. trace_export or get_behavior_evidence) or states the conditions under which an agent should pick this tool over them.

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