AI Certificates

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

The description adds meaningful behavioral context beyond the annotations: it returns explanations for every option, and it warns that multiple options are often defensible but only one is credited, which shapes the user's expectations. The annotations do not claim read-only behavior, so nothing here contradicts them.

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 sentences, no filler. The main function and distinctive behavior are front-loaded, and the second sentence adds valuable exam-specific context that helps the agent understand why the tool behaves as it does. 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?

With no output schema, the description reasonably explains what the tool returns (an explanation for every option) and signals the correctness-grading nature. It could specify the output format or whether the answer is recorded, but for its simplicity the description is sufficiently complete for correct invocation.

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 the input schema already documents each parameter clearly, including the expected format for 'selected'. The description does not add parameter-specific semantics, but the schema carries the burden adequately, so the 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 names a specific verb ('Grades') and resource ('the user's choice'), and explicitly states the distinctive behavior: returning an explanation for every option. This clearly differentiates it from sibling tools like get_practice_question, which fetches questions rather than evaluating answers.

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 the tool is used after the user has selected an answer on an exam question, and the exam-context sentence explains why the wrong-option explanations matter. However, it does not explicitly state when to use it versus alternatives, nor does it mention prerequisites such as first obtaining a question_id from get_practice_question.

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?

Adds important runtime context beyond the readOnlyHint annotation: the server is stateless and 'remembers nothing,' which explains why exclude_ids must be maintained by the caller. It also discloses that the question includes no answer key. 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?

Three short sentences, each earning its place: what is returned, how to sequence it with check_answer, and the critical exclude_ids obligation. Front-loaded and free of filler.

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?

Covers the essential behavioral contract for a stateless read-only tool: return value content, absence of answer key, and repeat-prevention guidance. Without an output schema, a bit more detail about the exact response shape would help, but the operation is simple enough that the description is adequate.

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 all three parameters at 100% coverage, so the baseline is 3. The description reinforces the purpose of exclude_ids by tying it to statelessness but does not add syntax-level detail beyond the schema.

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 exactly what it does: 'Returns one original practice question with its options and no answer key.' This clearly distinguishes it from check_answer, which validates the user's choice, and list_exams, which returns exam slugs.

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 clear workflow guidance: present the question, let the user choose, then call check_answer. It also instructs the agent to pass every already-served id in exclude_ids. It does not explicitly contrast with open_study or my_progress, but the sequencing is unambiguous.

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 readOnlyHint=true already declaring safety, the description adds value by enumerating the returned content: codes, item counts, fees, domain list, and weights. This is consistent with annotations and gives the agent useful expectations about result richness without contradicting anything.

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 two concise sentences, front-loading the specific content delivered and then providing a clear call-to-action. Every word earns its place; no redundancy or filler.

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 parameterless list tool with annotations covering the read-only nature and a closed world, the description fully explains the return payload and the intended invocation order. Nothing needed for correct selection or successful invocation 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?

With zero parameters, there is no parameter semantics to add. The baseline of 4 applies because the description has no need or opportunity to clarify parameters.

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 the tool lists Claude certifications with exam codes, item counts, fees, and domain lists/weights. It also explicitly frames the role as the entry point for obtaining valid exam slugs, which distinguishes it from siblings like check_answer or get_practice_question.

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 phrase 'Call this first to get valid exam slugs' gives explicit timing guidance and explains why this tool should precede others. It does not explicitly list alternative tools or when not to use it, but the sibling context and the clear sequencing instruction are 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 read-only, but the description adds valuable behavioral context beyond that: output is ordered weakest-first by domain, it is appropriate before and after study runs, and anonymous callers receive an explanatory message rather than fabricated zeros. This auth-related disclosure is especially useful and is not present in any structured field.

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 sentences that each earn their place: the first defines the output and ordering, the second gives concrete invocation contexts, the third handles an important edge case. It is front-loaded with the core meaning and contains no filler or repetition of schema details.

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 read-only, single-parameter progress tool, the description is complete: it conveys the grouping, ordering, expected timing, and auth behavior. The schema covers the only parameter, and annotations cover safety, so nothing needed for correct selection and invocation is missing. An output schema is not necessary to explain the return values at this level of detail.

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%: the single 'exam' parameter is fully documented with an enum and a reference to list_exams. The description does not need to add parameter details, so the baseline of 3 applies. It does reinforce that the tool covers 'one exam,' which aligns with the required parameter.

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 the resource: the person's recorded history for one exam, organized by blueprint domain with weakest first, making it easy to distinguish from list_exams, check_answer, and get_practice_question. The title also adds a clear verb-and-object framing: 'See what this person has answered so far.' This is highly specific about what the tool provides.

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 explicit usage timing: call at the start of a study session to decide what to drill, and after a question run to show progress changes. It does not explicitly name alternatives or say when not to use it, but the stated contexts are clear enough for an agent to know when this tool is appropriate.

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=true, and the description adds meaningful behavioral context beyond that: it opens/resumes a page, shows a visible question the user answers themselves, returns a URL, and instructs a browser agent to navigate there. No contradictions with annotations were found.

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 sentences, each earning its place: core action, usage context, and return/navigation behavior. The key purpose is front-loaded and there is no redundant filler.

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, the description appropriately states the return value (URL) and the expected agent action. It could elaborate on what 'resume' means when a session already exists, but overall the essential calling context is covered.

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 schema already documents exam, domain, and sub_objective. The description rephrases domain/sub_objective as optional focus but adds no format, validation, or cross-parameter semantics beyond what the schema 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?

Description names a specific verb ('open or resume'), a resource ('the study page for an exam'), and optional focus fields (domain/sub-objective). It also distinguishes itself from quiz-in-chat tools, so an agent can tell it apart from get_practice_question and check_answer.

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 says 'Use this when someone asks to study rather than to be quizzed in chat,' providing both a positive and negative usage condition. It also signals that subsequent reading/steering tools appear once the page is open, guiding the agent's next actions.

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