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

With no annotations, the description carries the full burden and does well: it discloses the policy-gate-then-retrieval flow, the three possible verdicts, and the specific behavior of 'referred' (no passages returned) and 'no_source' (threshold not cleared). It omits auth requirements, rate limits, and error/timeout behavior, keeping it from a 5.

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?

Three tight sentences with the core purpose front-loaded and the verdict contract laid out efficiently. The parenthetical verdict explanations each earn their place, though the enumeration adds some density.

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?

With no output schema and no annotations, the description compensates by explaining the return contract via the three verdicts. It is nearly complete for an agent to call and interpret the tool, with the only gap being the undocumented max_passages parameter.

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 50%: 'question' is documented as 'verbatim' and the description reinforces acting on its result, but 'max_passages' (with default 4, min 1, max 10) is never mentioned in the description. The bounds and default in the schema make it largely self-explanatory, so this lands at the baseline rather than a gap.

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 names a specific verb+resource ('answers the user's question') and outlines the internal pipeline (policy gate then retrieval), which distinguishes it from lower-level siblings like search_corpus and get_passage. It also frames itself as the 'Primary tool,' implicitly positioning it as the entry point. It does not explicitly name a sibling it differs from, so it stops short of a 5.

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?

It gives clear context for use ('Primary tool') and a strong directive on how to act on the result ('respect the verdict and must not answer from your own knowledge'). What's missing is explicit when-not guidance or naming of alternatives (e.g., when to drop to search_corpus or list_gaps).

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?

With no annotations, the description carries the full burden. It does disclose the key trait that no content is retrieved (side-effect-free, dry-run semantics), which is valuable. However it says nothing about auth requirements, whether calls are logged, rate limits, or what a refusal/test result looks like.

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 short sentences, front-loaded with the action and then the rationale. No filler, redundancy, or repetition of the schema.

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 one-parameter tool with no annotations and no output schema, the description covers intent but omits what the caller gets back (presumably a policy/allowed decision) and any auth or logging behavior. It is adequate but leaves the return contract to guesswork.

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% and the single 'question' parameter is undocumented. The phrase 'Test a question against...' implies the string is a natural-language question, which is a small amount of added meaning, but no format, length, or example guidance is offered.

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 (test) and object (a question against the policy gate), and the phrase 'without retrieving anything' distinguishes it from the retrieval siblings (answer_question, search_corpus, get_passage). It stops short of naming a sibling explicitly, so an agent must infer the contrast.

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?

'Useful for reviewing where the refusal boundary currently sits' gives one implied use case (dry-run a question before asking answer_question), but there is no explicit when-to-use/when-not guidance or named alternative. The routing to answer_question is left to inference.

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?

With no annotations, the description carries the full burden. It does disclose the shape of the return (counts plus a full passage list) and its honesty/coverage intent, but says nothing about cost, size of the passage list, or read-only nature beyond implication. Adequate but not rich.

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 short sentences, front-loaded with the core purpose and followed by the intended use. No filler or repetition, though the phrasing is slightly colloquial.

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?

With no output schema and no parameters, the description must describe returns, and it does so reasonably: counts by source and grading, review status, and passage list. That is sufficient for a simple read-only inventory tool.

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?

The tool takes zero parameters, so the baseline is 4; there is no parameter semantics to explain and the description correctly spends no words on inputs.

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 names a specific resource (the corpus) and enumerates what it reports: counts by source and grading, review status, and the full passage list. This is clearly distinct from answer_question, search_corpus, and get_passage, though it never explicitly names those siblings to sharpen the boundary against list_gaps.

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?

"Use this to answer coverage questions honestly" gives one implied trigger, but there are no exclusions or stated alternatives — the agent must infer that search_corpus or list_gaps are not the right picks for coverage questions.

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?

No annotations are provided, so the description carries the full behavioral burden. It never states that this is a non-mutating read, what the response contains, or how a missing/malformed id is handled. Only the id format examples hint at behavior, which is not enough for a lookup tool with zero annotation coverage.

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?

A single front-loaded sentence that wastes no words and puts the essential constraint ('exact id') plus examples immediately after. Nothing extraneous.

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 tool is simple (one required param, no nesting), and with no output schema the description arguably should describe the returned passage shape or failure behavior. It covers the input well enough to call, but leaves the agent guessing about errors and return content.

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 0% — the schema declares only a bare string with no description. The description partially compensates by giving concrete id shapes ('Q 2:183', 'Bukhari 1'), which is genuinely useful format guidance. However, it does not explain id resolution rules, accepted prefixes, or case/whitespace tolerance, so the compensation is incomplete.

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 and resource: 'Fetch one passage by its exact id.' The word 'exact' implicitly contrasts with sibling search_corpus, so an agent can distinguish lookup-by-id from retrieval-by-query. It stops short of naming an alternative explicitly, so it is clear but not fully sibling-differentiated.

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?

Usage is implied by 'by its exact id' — use this when you already have an identifier rather than a query. But there is no explicit statement of when to prefer this over search_corpus, nor any exclusion for invalid or partial ids. Adequate but with clear gaps.

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?

No annotations are provided, so the description carries the full behavioral burden. It explains the conceptual meaning of a 'gap' and frames this as a corpus-improvement loop, but says nothing about read-only vs mutating behavior, ordering, pagination, or result volume. For a tool with zero annotation coverage this is thin disclosure.

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 short sentences with no padding, and the core idea (questions with no source) is front-loaded. The second sentence adds framing rather than repetition, though it leans slightly toward rationale over operational detail.

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 simple one-parameter read-only list tool, the description conveys what a gap is but not what a returned item looks like, how results are ordered, or how the limit interacts with the queue. With no output schema present, some of that burden remains unfilled.

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% for the single 'limit' parameter, and the description never mentions it, its default of 50, or its 1–500 range. With low coverage the description is expected to compensate, and it does not.

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 resource — 'questions that returned no source' surfaced in a scholar's review queue — which is more than a restatement of the name. However, it is phrased as a noun fragment without a verb and does not differentiate itself from siblings like search_corpus or answer_question. The purpose is clear but requires the agent to infer the 'list' action from the name.

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?

There is no explicit when-to-use guidance and no alternatives named, even though siblings such as search_corpus and answer_question are plausible substitutes an agent could confuse this with. 'For the scholar's review queue' implies a workflow context but does not tell the agent under what condition to call this versus another tool.

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?

With no annotations, the description carries the load and does disclose two non-obvious traits: results are threshold-filtered and policy gating is intentionally skipped. It does not cover safety profile, ordering, or pagination behavior, but the policy-gate disclosure is the highest-value piece an agent could not infer.

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?

Three short sentences, zero filler, with the core capability front-loaded and the routing caveat placed last where it is most actionable. Every sentence earns its place.

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?

No output schema and no annotations, so the description is the only specification available; it covers return content in outline and the policy-gate behavior, but leaves the two tuning parameters and any notion of result ordering or result-count control undocumented for a 3-param tool.

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 0% across three parameters, so the description must compensate and largely does not: max_passages and include_below_threshold are never explained, and the 'retrieval threshold' concept that makes include_below_threshold meaningful is only alluded to. Only the query concept is implicitly covered.

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?

Specific verb + resource ('Lexical search over the approved corpus') plus a scope statement ('Returns passages above the retrieval threshold with full citation metadata') that separates it from the semantic/QA siblings. An agent can distinguish it from answer_question and get_passage without opening any 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?

Explicitly states a negative condition ('Does NOT run the policy gate') and names the correct alternative with the selecting condition ('use answer_question for user-facing questions'). This is exactly the when/when-not/alternative structure that routing requires.

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