replay

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

With no annotations, the description carries the full burden and does so well: it defines survives=true/false outcomes, states that a withheld replay has no value to quote, explains that flipped/unchecked name the decision and the unchecked conversions, and warns that file-read tapes lose operands for counted conversions so most QuantLib replays are withheld. That is substantial non-obvious behavioral context; only error/permission behavior and side effects are absent.

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 purpose, and each sentence carries information, but the body is a dense semicolon-and-quote chain referencing other tools' output formats that is hard to parse on a first read. It could be restructured into short labelled lines (survives=true / survives=false / path_recorded) without losing content.

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 4-parameter tool with no output schema and no annotations, the description covers the outcome space (survives true/false, flipped, unchecked, path_recorded) and the meaning of the important inputs. Minor gaps: tape_id semantics and error behavior for malformed assignments are unaddressed.

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%, so the description must compensate and largely does: it gives a concrete assignments syntax with example ('#12=101,#15=0.21'), explains where leaf ids and the 'out' id come from, and defines path_recorded as returning the recorded path's value 'for comparison only'. Only tape_id is left undefined, and it is largely self-evident.

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?

Opens with a specific verb+resource: 'Re-evaluate the tape at new inputs without re-running the model', which distinguishes it from load_tape/inspect_tape by naming the key differentiator (no model re-run). It is jargon-dense but an agent can tell what the tool does and roughly how it differs from the tape-inspection 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?

Gives an explicit fallback ('say so and re-run the script at the new inputs for the price') when survives=false, which is real routing guidance. However it never states when to prefer replay over inspect_tape or trace_script, and no prerequisites (e.g., the tape must match the script that produced the inputs) are spelled out.

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