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

Annotations declare readOnlyHint and openWorldHint, and the description goes well beyond that: it discloses the return shape (verdict/p/decision), the recipe mode, server-side ref expansion, and critically the degradation behavior (unavailable / rate_limited / budget_exceeded) with an instruction not to retry in a loop. That failure-mode guidance is exactly the kind of context structured fields cannot carry.

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 constraint and organized into Use for / Not for / refs / failure behavior / example – every sentence earns its place. The density and shorthand ("noul", "$diff:staged") make it slightly harder to parse on first read, but nothing is 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?

For a 9-parameter tool with nested objects and an output schema, the description covers the remaining gaps an agent would otherwise stumble on: which state to pass, how to reference files instead of pasting, which recipes exist, and what to do when the service degrades. Nothing needed to invoke it correctly is missing.

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 100%, so the baseline is 3; the description still adds value by naming the three question types (noul yes/no p, choice label, score level), the recipe form with the args convention, and a full worked example call. It stops short of explaining preset, detail, cache, long_context or images beyond what the schema already says.

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 precise verb+resource+cardinality constraint ("ONE state, N questions") and immediately states that answers come back with verdict, p and decision. It explicitly contrasts with the sibling jev_batch for the many-item case, so an agent can route without opening either schema.

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 positive triggers ("judging one failure log, one diff, one file, one command"), an explicit alternative for the many-item case ("For many items use jev_batch"), and a concrete not-for list excluding counting, dates, arithmetic, exit codes and patch-correctness judgments. This is the strongest form of routing guidance.

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

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

Beyond readOnlyHint/openWorldHint, it discloses execution traits an agent cannot infer: concurrent requests behind a shared rate gate, result ordering by p, summary plus every failure, and named failure modes (unavailable / rate_limited / budget_exceeded) with an explicit no-retry policy. Return rows are described even though an output schema exists.

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 contract and tightly packed, with a closing worked example that earns its space. Some phrasing is telegraphic to the point of obscurity ("narrow Nouls where true = bad"), which costs a point on clarity.

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 15 params, nested question objects, and an output schema, the description covers the calling contract, the distinguishing alternative, error handling, and an example. Residual gaps are minor: where preset thresholds come from and what concurrency/cache defaults imply in practice.

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?

With 15 params at 73% schema coverage, the description adds real meaning for the tricky ones: items_from forms, return top-k vs flagged semantics, rank_by sorting, and preset selection. It leaves several params (concurrency, cache, top_k, max_total_input_tokens) entirely to the schema, so it enriches rather than fully documents.

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 precise formula: "N items x ONE question set: one request per item", then names concrete item kinds (failing tests, diff hunks, files). It explicitly separates itself from jev_ask by scope (many items vs. several questions about one state), so an agent can route without opening either schema.

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 explicit when-not guidance ("Not for several questions about one state (jev_ask)") and a concrete workflow recipe ("Diff review: preset review_filter..."). It also prescribes fallback behavior for error responses: judge inline, do not retry in a loop.

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

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

Annotations already declare readOnlyHint and openWorldHint, so the description's main added value is the cost model: "Free except health/models refresh (one GET)" plus the note that validate is checked offline with "nothing sent." It does not spell out side effects of \"feedback\" or \"calibrate\" (they persist labels/thresholds, and \"reset\" clears counters), which sits in mild tension with readOnlyHint, though these are internal bookkeeping rather than changes to the user's resources.

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?

One dense opening sentence front-loads the action inventory, followed by the single most decision-relevant caveat about cost. It is compact with no filler, though the parenthetical chain is packed enough that a skim reader may lose the action-to-parameter mapping.

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?

All seven actions are named and briefly defined, the cost/refresh caveat is disclosed, and an output schema exists so return values need not be described. The remaining gap is routing guidance against jev_ask/jev_batch, which the description does not address.

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% and every parameter already carries an action-prefixed description, so the schema does the heavy lifting. The description echoes the same action-to-parameter pairings (feedback/label, health/models/refresh) but adds no syntax or format detail beyond what the schema states.

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 opens with a specific scope ("Jev health and housekeeping, no judgments") and then enumerates all seven actions with parenthetical definitions, so an agent can tell what each invocation does. It differentiates itself from jev_ask only obliquely via "validate (offline dry run of a jev_ask input)"; there is no explicit statement that it is the status/introspection counterpart to the query tools.

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 action list implies when each mode applies, and "validate (offline dry run of a jev_ask input)" links it to the ask workflow, but there is no explicit "use this when X, use jev_ask/jev_batch when Y" routing. An agent must infer the split from the sibling names alone.

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