Quiz20

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful return-content context (number of papers per exam and a link to each exam page), which matters since there is no output schema. It does not disclose ordering, list size, or whether results are truncated, leaving real behavioral gaps.

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 sentence front-loads the resource ('All exams on Quiz20') and then the returned fields, with no filler or restatement of the title. Every clause carries information the agent can act on.

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 zero-parameter read-only list tool with no output schema, the description covers what is returned and at what granularity, which is the main thing an agent needs. The only omissions are ordering and result-set size, which are minor for this complexity level.

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 has zero parameters, so there is nothing for the description to disambiguate at the input level. Baseline 4 applies for a parameterless tool.

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 (exams with previous year question papers) and states the scope 'All exams on Quiz20', so an agent knows exactly what set is returned. It stops short of differentiating itself from siblings like list_papers or list_practice_sets, which cover adjacent resources.

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 mention of when to prefer list_papers, list_practice_sets, or search_topics instead. Because the tool takes no parameters, the implied usage is 'browse everything', but the agent must infer that from the absence of arguments rather than from the text.

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 a read-only, closed-world operation, so the safety profile is covered. The description adds genuinely useful return context — ordering (newest first) and what each paper includes (questions, time, paper page, PDF when available, online test link) — but says nothing about result volume limits, pagination, or empty-result behavior.

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 front-loaded sentence with no filler; the resource comes first and the return contents follow. The parenthetical example list is slightly heavy but each item is illustrative rather than redundant.

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 only two fully documented parameters and no output schema, the description carries the burden of describing returns, and it does so reasonably well. The remaining gap is operational detail such as how many papers are returned and whether large exam results are truncated.

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, and the description rightly does not re-explain the parameters. It does contribute the framing that exactly one exam is targeted and that the tool is exam-scoped, which reinforces the required parameter's role beyond the schema's own wording.

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 resource with scope: previous year question papers for exactly one exam, with concrete exam examples. It is distinguishable from list_exams and list_practice_sets by the resource named, though it never explicitly contrasts itself with those 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?

Usage is only implied: the agent can infer this is the tool for retrieving past papers for a named exam rather than practice sets or exam metadata. There is no explicit when-to-use/when-not guidance or reference to the sibling tools that cover adjacent needs.

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=true and openWorldHint=false, so the safety profile is covered. The description adds useful content details—free sets, 20 MCQs, specific categories, topics, and links—but does not describe pagination, ordering, or return structure.

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?

The description is a single efficient sentence with no wasted wording. It is appropriately sized for a simple list tool, though it could front-load the listing action more explicitly.

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 zero-parameter list tool with no output schema, the description explains what kinds of practice sets are returned and that topics and links are included. However, it omits whether all sets are returned, how results are structured, and any ordering or pagination behavior.

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 has zero parameters, so there is no parameter semantics to explain. The baseline for a parameterless schema is 4, and the description does not need to compensate for missing parameter documentation.

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 identifies the resource as free practice sets of 20 MCQs and enumerates the covered categories (General Knowledge, Computer, State special GK, Census 2011, latest data-based questions). It is clear what the tool returns, though it does not explicitly differentiate itself from siblings like list_exams, list_papers, or search_topics.

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 no when-to-use guidance and does not mention alternatives such as list_exams or search_topics. Usage is only implied by the content description, leaving the agent to infer when this tool is preferable.

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=true and openWorldHint=false, so the safety profile is covered; the description usefully adds that results are a mix of quiz, PDF and practice-set content delivered with links. It says nothing about matching behavior (substring vs prefix), result caps, ordering, or empty-result handling, which are the remaining behavioral questions for a search tool.

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 front-loaded sentence with the action first and the payload second; no filler. The inline example list is slightly long but it is doing real work in illustrating acceptable inputs.

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 single-parameter, read-only search with no output schema, the description covers what is searched and what kinds of results come back, which is the core need. The only gaps are result limits and matching semantics, minor for this level of complexity.

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% and the single query parameter is documented as "Topic words, at least 2 letters", so the schema carries the constraint. The description adds concrete example topic words, which helps an agent phrase input, but adds no syntax, escaping or multi-word rules beyond the schema. Baseline 3 applies.

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 (Search) plus the resource (Quiz20 by topic name) and enumerates what comes back: topic-wise quizzes, NCERT chapter PDFs, GK practice sets with links. That is far more informative than the title alone. It doesn't explicitly name the sibling list_* tools, so the search-vs-browse distinction is only implicit.

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 through example queries ("Mughal", "Budget", "Rivers"), which shows the intended input style, but there is no statement of when to prefer this over list_exams, list_papers or list_practice_sets, nor any exclusion or prerequisite. An agent can infer it is keyword lookup, but must guess about the browse alternative.

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