jev_prepare_work

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

The description adds behavioral context beyond the annotations: it promises to 'preserve all originals, constraints and acceptance', states 'No model selection, spawning or edits', and explains that 'No labels/checks means zero inference'. These clarify side-effect boundaries. It does not cover auth, rate limits, or exact persistence semantics, so it is not a 5, but it adds genuine value.

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?

Four sentences, front-loaded with the core purpose, each sentence adding a distinct constraint (scope, task_id uniqueness, behavior, exclusions). No redundant or filler wording.

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?

The description covers the core workflow and important edge cases like zero inference, but it never describes the return value or what the prepared 'work packet' contains, and with no output schema an agent has to infer that. For a 9-parameter tool this is a noticeable gap, though the schema picks up a lot of slack.

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 descriptions already cover root, task, checks, labels, sources, and task_id (67% coverage). The description adds some extra semantics for labels/checks ('No labels/checks means zero inference') and mentions executor modes ('main-host execution or one subagent assignment') and preservation of constraints/acceptance. But it does not fully explain the semantics of executor, acceptance, and constraints, so it stays at the middle baseline.

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 states a specific verb ('Prepare') and a concrete resource ('task-specific source-linked work packet'), scoped to 'main-host execution or one subagent assignment'. It also distinguishes from siblings by noting each task needs its own task_id and explicitly excludes model selection, spawning, and edits, so an agent can tell this apart from tools like jev_prepare_evidence.

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 clear context for when to use the tool (preparing a work packet for main or subagent, per distinct task_id) and hints at when not to use it ('No model selection, spawning or edits. No labels/checks means zero inference'). However, it never names an alternative tool for those excluded cases, so the guidance is implicit rather than explicit.

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