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Save and replay named step sequences across sessions. Automate testing by re-running saved workflows like login or checkout paths.

Instructions

Save and re-run named step sequences — define a workflow once (login, checkout, smoke path), replay it in any session. action='save' stores steps (interact_and_test's exact format, all 25 actions); action='run' executes a saved flow on a session via the same engine as interact_and_test; action='list' shows saved flows; action='delete' removes one. Deliberately minimal: verify outcomes by following a run with assert_all or visual_check. Flows persist in data/flows/ across sessions and server restarts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFlow name, e.g. 'login' (letters, digits, . _ -). Required except for list.
stepsNoFor save: steps in interact_and_test's format
actionNoWhat to do (default: list)
session_idNoFor run: session to execute on
descriptionNoFor save: optional human note about what the flow does
continue_on_errorNoFor run: keep executing after a failed step (default: false)
Behavior4/5

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

With no annotations provided, the description discloses key behaviors: flows persist across sessions and server restarts, the tool is 'deliberately minimal' regarding verification, and steps must use interact_and_test's exact format. It does not cover error handling or overwrite behavior, but the main traits are well stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with no redundant sentences. It opens with the core purpose, enumerates actions, provides guidance on verification, and mentions persistence. Every sentence contributes essential information without filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (6 params, no output schema, no annotations), the description covers the main functionality, persistence, and relation to siblings. It could mention overwrite behavior on save, but overall it provides sufficient context for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 6 parameters are described in the schema (100% coverage). The description adds value by explaining the action enum options, specifying that steps must be in interact_and_test's format for save, and noting the default for continue_on_error. This goes beyond the schema's basic descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: saving and replaying named step sequences. It explicitly lists the four actions (save, run, list, delete) and distinguishes itself from siblings by referencing interact_and_test as the underlying engine for execution, making its unique value clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use each action (e.g., 'action='save' stores steps', 'action='run' executes a saved flow') and provides guidance on verification: 'verify outcomes by following a run with assert_all or visual_check'. It lacks explicit exclusions or alternatives, 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.

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