Scholarize — Study Plan & Thesis Tools

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

Annotations already declare this is not read-only and is open-world; the description adds meaningful context beyond that: the call runs against the connected student account, it consumes their plan quota, and it requires a Scholarize token obtained from Settings. That auth precondition and billing effect are exactly the kind of non-obvious behavior an agent needs, though latency/pagination-style traits are not applicable here.

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, front-loaded with the action and result, then usage triggers, then the prerequisite. Every sentence carries distinct information with no repetition of the schema or title.

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 two-parameter tool with no output schema, the description covers what the tool returns (a step-by-step explanation), when to use it, and the account/token prerequisite. The only gap is the absence of any explicit alternative-tool routing, which is minor here.

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%, with both 'question' and 'subject' documented in the schema, so the baseline is 3. The description adds no extra semantics (e.g., subject format, question length/scope) beyond what the schema already provides.

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 ('Ask ... a question') and resource ('the Scholarize Tutor') and states the output form ('step-by-step explanation'), so the tool's function is unambiguous. It does not explicitly contrast itself with the generate_* siblings, but the tutoring/Q&A framing is distinct enough from artifact generators and list_* tools that an agent can separate them.

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 concrete triggering phrases ('explain X', 'help me understand Y') and a category (homework/concept questions), which tells the agent when to reach for it. It stops short of naming alternatives or when NOT to use it (e.g., vs generate_flashcards for drill practice), so it is clear context without exclusions.

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 indicate readOnlyHint=false and destructiveHint=false, so the safety profile is already known. The description adds useful context beyond annotations: the email requirement and that it is free. It does not disclose the output format or precise behavior (e.g., whether it returns all five styles at once or requires external interaction), but the core generation behavior is predictable; no contradiction with annotations.

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 compact three sentences with the core action front-loaded. The 'Free' clause is mildly redundant but not harmful. Every sentence earns its place: purpose, requirement, and when-to-use.

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 tool with 11 parameters and no output schema, the description covers the main selection cues (what it does, when to use, email requirement) but omits what the returned citation looks like and whether all five styles are returned at once. The schema handles parameter meanings, but the description could be more complete about the output contract.

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 adds only 'from the source type and details,' which maps to the schema's `type` and other fields, but it does not explain individual parameters or their relationships beyond the schema. It lists 'book, journal article, website' in the usage note, slightly reinforcing the `type` enum values, but no substantial additional meaning.

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 verb and resource: 'Generate a formatted citation for a source in five styles...' It also names the supported styles and source types, and clearly distinguishes from sibling tools (generate_study_plan, generate_thesis_statement), which serve different purposes. The title and description align with no ambiguity.

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 when the tool should be used: 'Use it when a student needs to cite a book, journal article, website, or other source for an essay or paper.' It also gives a prerequisite (student email) and a condition (free). It does not explicitly contrast with alternatives, but the sibling tools are unrelated, so the use-case guidance is sufficient.

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 mark this as a non-read-only, open-world, non-destructive, non-idempotent write. The description adds genuinely useful context beyond them: that a connected Scholarize account is a prerequisite and that output is persisted to that account. It stops short of noting whether repeated calls duplicate existing cards, which matters for an idempotentHint=false 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?

Two short sentences, front-loaded with the action and inputs. There is mild redundancy between 'the connected student Scholarize account' and the trailing 'Requires a connected Scholarize account,' but it stays under control and costs little.

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 100% schema coverage, all-optional params, and no output schema, the essentials are covered: inputs, destination, and the account prerequisite. For a generation tool it would be slightly stronger if it said whether the result is returned inline or only saved to the account, but overall the agent has enough to invoke it correctly.

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%, so the schema already documents all three optional parameters. The description echoes the topic/notes inputs but adds no format, constraint, or default information (e.g., default card count) beyond what the schema provides. Baseline 3 is appropriate.

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 (generate) and resource (study flashcards), and names the two input modes: from a topic or from pasted notes. It also clarifies persistence ('saved to the connected student Scholarize account'), which distinguishes it from a pure read like list_my_flashcards. It does not, however, differentiate itself from the sibling generators (generate_quiz, generate_study_plan).

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 implies when the tool applies (you have a topic or notes to turn into cards), but never explicitly states when to choose it over generate_quiz or the other generate_* siblings, nor any exclusions. Usage is inferable rather than spelled out.

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 declare readOnlyHint=false, idempotentHint=false and openWorldHint=true but say nothing about persistence or prerequisites. The description adds genuinely new context: the generated quiz is written to the student's account, and an authenticated connection is required. It stops short of describing output or failure 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?

Two short sentences that lead with the action, which is the right front-loading. The second sentence restates the account requirement already implied by 'for the connected student', so there is minor redundancy.

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 three-parameter generator with no output schema, the description covers what is produced, where it is saved and the account prerequisite. It does not say what identifier or object comes back on success, but with no output schema that gap is modest.

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%, so topic, difficulty and numQuestions are already documented in the schema. The description only echoes 'on a topic' and adds no format, constraint or default information beyond what structured data provides, so the baseline of 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 and resource: 'Generate a practice quiz on a topic', plus the scope that it is for the connected student and persisted to their account. It does not explicitly distinguish itself from siblings like generate_flashcards or generate_study_plan, but the resource noun makes the intent unambiguous.

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 states a precondition ('Requires a connected Scholarize account'), which is useful usage context, but gives no when-to-use guidance or comparison against alternatives. An agent must infer that this is the tool for quiz requests rather than flashcard or study-plan requests.

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?

The description adds meaningful behavioral context beyond annotations: the plan is 'sent/saved' to the student's email, the tool returns 'the plan summary and a shareable link,' and it is free. This clarifies the side effects and outcome without contradicting the annotations.

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 concise, front-loaded sentences cover what the tool does, key requirements, outputs, cost, and when to use it. Every sentence adds value and none is redundant with 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 simple two-parameter tool with full schema coverage and no output schema, the description is complete: it explains inputs, required email side effect, return value, pricing, and the target use case. No essential information 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 description coverage is 100%, so the baseline is 3. The description reinforces that the email is required and the syllabus defines what to study, but it does not add significant new parameter meaning beyond what the schema already explains.

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 ('Create'), a clear resource ('personalized week-by-week study plan'), and the input sources ('syllabus, exam topics, or a description'). It is easily distinguishable from the sibling tool 'generate_thesis_statement' because it targets study plans rather than thesis statements.

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 explicitly says when to use it: 'Use it when a student asks for help planning their studying or exam prep.' It does not name the sibling or explicitly say when not to use it, but the use case is clear enough that an agent would pick it correctly.

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 provide readOnlyHint=false and destructiveHint=false. The description adds meaningful context by disclosing an auth-like requirement ('Requires the student’s email') and a cost constraint ('Free'). It also indicates that multiple output options are generated, which is useful beyond the structured annotations.

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 three short sentences with no filler. It front-loads the primary purpose, then lists constraints and the intended use case. Every sentence contributes useful information for tool selection and invocation.

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 the tool's moderate complexity and the absence of an output schema, the description gives enough context: what it generates, what inputs matter, a required identity element, and when to use it. It could be slightly more explicit about optional parameters and the exact return format, but it remains adequately complete for an agent.

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%, so the schema already documents all parameters well. The description adds only marginal clarity by grouping 'essay type' with its enum values and labeling 'stance' as optional, but it does not significantly expand on what the schema already provides.

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 clearly states a specific action ('Generate strong thesis statement options') and identifies the resource (thesis statement) plus the key inputs (topic, essay type, optional stance). It is immediately distinguishable from the sibling generate_study_plan because it targets essay thesis creation rather than study planning.

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 explicitly says 'Use it when a student needs a thesis or essay direction,' which gives clear when-to-use guidance. It does not explicitly name the sibling or state when not to use it, but the purpose is distinct enough that the use case is well understood.

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, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description usefully adds the account-connection prerequisite, but says nothing about result format, pagination, or empty-state 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?

Two short sentences, front-loaded with the action and resource, with the prerequisite second. Nothing is wasted or buried.

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 full annotation coverage and no output schema, the description supplies the one thing structured fields don't: the account-connection requirement. Adequate, though return-shape expectations are left unstated.

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 there is nothing for the description to disambiguate. Baseline 4 applies since the schema is trivially complete.

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 ('List') and resource ('connected student saved flashcard sets'), which is clear enough that an agent can distinguish it from generate_flashcards. It does not explicitly name or contrast any sibling, but the list-vs-generate distinction is readable from the wording.

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?

'Requires a connected Scholarize account' is an implicit precondition that tells the agent when this tool is unusable, but there is no guidance on when to prefer it or which sibling to use instead. Minimal viable usage 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?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is fully covered. The description adds value beyond them by disclosing the connectivity precondition, which an agent must verify before calling; it says nothing about volume limits or return shape, which keeps it short of 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?

Two short sentences, zero waste, with the action front-loaded and the precondition following immediately. Nothing is padded or 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?

For a zero-parameter, closed-world list tool with no output schema, the description covers what the agent needs to decide and invoke it. It could optionally note what is returned (quiz names/identifiers) and whether it is scoped to all saved quizzes or a subset, leaving a small gap.

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 and there is no schema semantics for the description to expand upon. Nothing is missing on this dimension.

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 (List) and resource (saved quizzes) scoped to the connected student's own account in Scholarize. The resource name naturally distinguishes it from its near-twin sibling list_my_flashcards, though no sibling is named explicitly.

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?

Provides one actionable prerequisite: a connected Scholarize account is required. However, it gives no when-to-use guidance relative to alternatives such as generate_quiz (create) or ask_ai_tutor, leaving that inference to the agent.

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