Connectry Architect Cert

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

No annotations are provided, and the description does not disclose behavioral traits beyond the return values. It does not mention whether it is read-only, requires an active project, or has side effects. However, the tool is inherently a read operation.

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, well-structured sentence that front-loads the core purpose and specific outputs. Every word adds value with no 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 parameterless tool with no annotations or output schema, the description adequately covers what the tool does and what it returns. Minor gap: does not specify prerequisites like having an active capstone build.

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?

There are no parameters in the schema, so the description does not need to explain them. With 100% schema coverage (no params), the description adds no param details, which is acceptable per guidelines.

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 checks 'guided capstone build progress' and lists specific return elements (current step, criteria coverage, quiz performance). It distinguishes itself from siblings like 'capstone_build_step' and 'start_capstone_build' by focusing on overall status.

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?

No explicit guidance on when to use this tool versus alternatives such as 'capstone_build_step' or 'get_progress'. The context implies it is for holistic status, but no when-not-to-use or alternative comparison is provided.

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?

Since no annotations are provided, the description fully discloses behavioral traits. It details progress tracking (creating/updating TodoWrite checklist), edge case handling (Other: re-present options; Skip: advance step), and presentation rules (use AskUserQuestion with headers, show results as chat text). This goes beyond basic annotations and prepares the agent for correct 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?

The description is moderately long but well-organized with clear sections (IMPORTANT, PROGRESS TRACKING, EDGE CASES). It front-loads the main purpose and provides necessary details without unnecessary verbosity. Each section adds value, though some repetition could be trimmed.

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 simplicity (one parameter, no output schema, no annotations), the description is very comprehensive. It covers all actions, progress tracking, presentation guidelines, and edge cases. Missing details like error handling or out-of-order calls are minor gaps, but the description is sufficient for most use cases.

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 input schema has 100% coverage for the single 'action' parameter. The description adds significant meaning beyond the schema by explaining the effect of each enum value (e.g., 'confirm' creates a checklist, 'next' updates progress). This contextual mapping helps the agent choose the correct action.

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's purpose: 'Drive your guided capstone build — quiz, build, and advance through 18 progressive steps.' It uses a specific verb ('drive') and identifies the resource ('guided capstone build'). This distinguishes it from sibling tools like 'capstone_build_status' (status check) and 'start_capstone_build' (initialization).

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 provides explicit guidance on when to use AskUserQuestion with specific headers ('Answer', 'Action'), how to display quiz results, and how to handle progress tracking via TodoWrite. It also covers edge cases for 'Other' and 'Skip'. However, it does not explicitly state when not to use this tool or mention alternatives among siblings, such as when to use 'capstone_build_status' instead.

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 exist, so description carries full burden. It indicates exploration of content but does not disclose side effects, state changes, or authentication needs. 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 sentences with no wasted words. Purpose is front-loaded, and the actions are concisely listed.

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 no output schema, the description covers when to use and what it does. It could optionally mention return type, but not necessary given context signals.

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% (baseline 3). Description adds value by mapping enum actions ('next', 'code_example', etc.) to real-world purposes (explore concepts, code examples, etc.), enhancing understanding 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?

The description clearly states it handles post-answer follow-up actions and lists specific content types (concepts, code examples, handouts, reference projects). This distinguishes it from siblings like submit_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 states 'Use after submit_answer', providing clear temporal context. However, it lacks explicit when-not-to-use or alternative tool 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?

The description indicates a read-only operation ('View') and specifies output content, but with no annotations provided, it doesn't disclose additional behavioral traits such as authentication requirements, rate limits, or error conditions. A simple view tool, but transparency is limited.

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, well-structured sentence that front-loads key information. No unnecessary words, earning its place efficiently.

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 no parameters and no output schema, the description adequately describes the return content (domains, task statements, mastery). However, it does not cover potential edge cases or response format, but for a simple retrieval tool, it is sufficiently complete.

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 input schema has no parameters (100% coverage), so the description doesn't need to add parameter semantics. Baseline score of 3 is appropriate as it adds no extra 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?

The description clearly states the verb 'View' and the resource 'full certification curriculum' with specific details (domains, task statements, mastery). It distinguishes itself from sibling tools like get_dashboard or get_progress by specifying what it retrieves.

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 use when you need curriculum info, but it lacks explicit guidance on when to use this tool versus alternatives or when not to use it. No exclusions or alternatives are mentioned.

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 does not explicitly state that this tool returns a URL; it only says 'Open...' followed by instructions to use 'preview_start' after getting the URL. While the implication is clear, the exact output behavior (returning a URL) is not spelled out. No annotations are provided, so the description carries the full burden, but it fails to fully disclose the return value.

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 remarkably concise: two sentences plus a crucial 'IMPORTANT' note. Every sentence serves a purpose: first explains what the tool does, second provides critical usage guidance. No redundant or irrelevant information.

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 description effectively covers purpose and usage, but misses explicitly stating the return type (a URL). Given that there is no output schema and no annotations, this omission slightly reduces completeness. However, the guidance to use 'preview_start' after 'getting the URL' implies the return value, so the gap is small.

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 0 parameters, so the input schema requires no additional explanation. The description adds value by detailing what the dashboard displays (mastery levels, exam history, etc.), going beyond the schema's void. This compensates fully for the absence of 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's action ('Open the study progress dashboard') and lists the specific content it shows (mastery levels, exam history, activity timeline, capstone progress), making the purpose unambiguous. It distinguishes from siblings like 'get_exam_history' and 'get_progress' by framing it as a combined dashboard view.

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 provides explicit usage guidance: after obtaining the URL, the AI should use 'preview_start' to open it. It also gives trigger phrases ('show dashboard', 'open dashboard') to help the agent decide when to call this tool, clearly differentiating when to use it versus alternatives.

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 implies a read-only operation ('view'), and no annotations are present. It does not disclose potential limitations like data volume or authentication requirements, but for a simple tool with no parameters, the description adequately covers the main 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 sentences, 20 words. Front-loaded with action and outputs, second sentence adds value. No redundancy or unnecessary text.

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 no output schema, the description explains return values (scores, pass/fail, per-domain breakdowns) and adds comparison feature. It lacks mention of any limits or prerequisites, but for a no-parameter tool, it is largely sufficient.

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?

Input schema has 0 parameters, and schema description coverage is 100%. Per guidelines, baseline is 4, which is appropriate as the description adds no param-specific details.

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 clearly states what the tool does: view completed practice exam attempts with specific details like scores, pass/fail, and per-domain breakdowns. It also adds a secondary feature of comparing progress. No competing sibling tool serves the same purpose.

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?

No explicit guidance on when to use this tool versus alternatives. While the purpose is clear, the description does not mention scenarios where other tools might be more appropriate, nor does it provide criteria for selection.

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 provided, the description bears full burden. It explains the prioritization logic and flow but does not disclose side effects (e.g., marking questions as seen, state changes) or permissions required. The emphasis is on usage rather than behavioral safety.

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 lengthy and mixes purpose, usage instructions, and edge cases into a single block. While front-loaded with the core purpose, it could be more concise by separating general functionality from detailed agent instructions.

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 complexity of the multi-step interaction and absence of an output schema, the description adequately explains the expected output (question details for AskUserQuestion) and edge cases. It assumes some agent knowledge of sibling tools but is largely comprehensive.

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 input schema has 100% description coverage for both parameters (domainId and difficulty). The description adds no extra meaning beyond what the schema already provides, so baseline of 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?

The description clearly states the tool retrieves the next practice question with explicit prioritization (review, weak areas, new material). This distinguishes it from siblings like submit_answer or follow_up, which serve different roles in the workflow.

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 provides detailed instructions on how to present the question and handle edge cases (Other, Skip). However, it does not explicitly mention when not to use this tool or compare to alternatives like get_exam_history or get_curriculum, missing some usage boundaries.

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 indicates a read operation ('Get') but does not disclose data freshness, authentication requirements, or whether the progress is real-time. The description is too minimal to fully inform the agent about behavioral traits.

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, front-loaded sentence with no extraneous information. Every word contributes to the purpose, making it efficient and easy to parse.

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 tool, the description covers the return themes but lacks output schema or details on structure. It does not mention whether results are aggregated or per-section, leaving some ambiguity. The description is adequate but not comprehensive.

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?

There are no parameters, so schema coverage is 100% (trivial). The description adds value by explaining what the tool returns, which is not evident from the empty schema. Baseline 4 for zero parameters 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?

The description clearly identifies the tool as retrieving a certification study progress overview with specifics on mastery levels, accuracy, and review status. It is clear, but does not explicitly distinguish itself from sibling tools like get_dashboard or get_study_plan, which may overlap.

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?

No guidance on when to use this tool versus alternatives is provided. It does not mention prerequisites, limitations, or exclusions, leaving the agent to infer context from the tool name alone.

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 provided. Description does not disclose behavioral traits like read-only nature, authorization needs, or side effects. Only states it gets information, which implies safety but lacks explicit 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?

Single sentence, no wasted words, efficiently conveys core purpose and included fields.

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 one required param, no output schema, and no annotations, the description adequately names the resource and some fields. However, it omits return structure, error conditions, or additional context. Adequate for a simple tool but not comprehensive.

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 parameter description ('Task statement ID, e.g. 1.1') is clear. The description adds no additional semantics beyond restating 'specific task statement'. 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?

Clearly states verb 'Get' and resource 'detailed information about a specific task statement' and lists included content (concept lesson, mastery, history). Distinguishes from siblings like get_curriculum by focusing on task statements, but could be more precise about scope.

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?

No guidance on when to use this tool versus alternatives such as get_curriculum or get_practice_question. No context for selection or 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?

No annotations are provided, so the description must carry the full burden. It only says the tool gets a plan but does not disclose behavioral traits such as side effects, required prior state (e.g., assessment completed), or whether it modifies data. The instructions about AskUserQuestion and TodoWrite are about the agent's actions, not the tool's 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?

The description is overly long and mixes the tool's purpose with multi-step agent instructions (AskUserQuestion and TodoWrite). The first sentence is concise, but the rest adds verbosity that could be separated. This reduces clarity for tool selection.

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 no parameters and no output schema, the description should at least describe what the study plan contains. It only says 'personalized' but does not detail the structure (e.g., list of topics, time estimates). The additional instructions compensate somewhat for missing output info, but the lack of output format is a 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 input schema has zero parameters, so parameter semantics are not needed. The baseline for 0 parameters is 4, and the description adds no parameter information beyond what is already implied (no input required). No deduction needed.

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 'Get a personalized study plan based on your assessment results, weak areas, and learning path.' This provides a specific verb ('Get'), resource ('study plan'), and context, distinguishing it from siblings like get_curriculum or get_dashboard.

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 tells the agent what to do after invoking the tool: show the plan, then use AskUserQuestion to let the user pick domains, then filter practice questions. It provides a clear usage flow, though it does not explicitly mention when NOT to use this tool or alternative tools.

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 burden. It specifies the accuracy threshold (70%) but does not disclose whether the tool is read-only, requires auth, or any side effects. More detail would improve transparency.

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 with no wasted words. The description is front-loaded with the key purpose and a direct actionable suggestion. 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?

The description gives the tool's purpose and a threshold, but lacks output details (e.g., format, data structure). With no output schema, the agent is left guessing the return value, reducing completeness.

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 input schema has zero parameters, so the description inherently adds no parameter info beyond the schema. Baseline 4 applies as per guidelines for 0-parameter tools.

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 identifies weakest task statements based on accuracy below 70%, providing a specific verb and resource. It is distinct from sibling tools like get_progress or get_dashboard, though it doesn't explicitly differentiate.

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 usage for study focus but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, leaving the agent to infer context.

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 fully discloses the destructive behavior: 'permanently deletes', 'cannot be undone', and lists what is deleted. This goes beyond the input schema, which only has a confirmation parameter.

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 one impactful sentence with a warning prefix. No extraneous words; front-loaded with critical information.

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 destructive action with one parameter, the description explains the consequence and confirmation requirement. No output schema exists, so return values are not needed. Minor improvement could mention what happens after reset, but it's 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?

The schema already documents the 'confirmed' parameter well (must be true to confirm). The tool description adds context about the consequence but does not add new parameter-specific meaning. With 100% schema coverage, baseline is 3.

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 deletes all study progress permanently. It uses strong verbs ('deletes') and specifies the resources (answers, mastery data, review schedules). This distinguishes it from sibling tools like get_progress or get_weak_areas.

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 does not provide explicit guidance on when to use this tool versus alternatives. It lacks conditions or examples of appropriate use cases. A warning is given but no when-not-to-use or alternative suggestions.

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 present, so the description carries full burden. It indicates a read-only operation ('Get instructions'), but does not disclose behavior for invalid projectId or any side effects. 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 single, front-loaded sentence with no wasted words. It conveys the tool's purpose and parameter usage efficiently.

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 description is adequate for a simple tool with one parameter. It lacks details about the return format or what 'instructions' entail, but given no output schema, the description provides sufficient context for an agent to understand its basic function.

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% for the single parameter 'projectId'. The description adds the instruction 'Omit to see available projects', which clarifies a special behavior not evident from the schema alone.

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 specifies the verb 'Get', resource 'instructions for a reference project', and purpose 'to practice certification concepts hands-on'. It clearly distinguishes from siblings like get_curriculum or get_dashboard.

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 use when needing hands-on practice but does not explicitly state when to use this tool versus alternatives like get_curriculum or get_practice_question. No exclusions or alternative tool names are provided.

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 provided; description carries full burden. It discloses that it returns one question, requires a flow with domain handouts, handles user interactions, and updates progress. No destructive actions implied, and no contradictions.

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?

Long but well-structured with sections for flow, edge cases, progress tracking. Front-loaded with core purpose. Could be more concise but every sentence adds necessary detail for correct usage.

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 interactive complexity and lack of output schema, description fully explains expected response format, step-by-step flow, edge cases, and progress tracking. Leaves no ambiguity 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?

Input schema has 0 parameters with 100% coverage, so description need not add param info. Baseline 4 is appropriate; description does not need to explain parameters but adds value through behavioral instructions.

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?

Clearly states 'Start the initial assessment' and specifies it returns one question at a time (15 total, 3 per domain). Distinguishes from sibling tools like start_practice_exam 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?

Provides detailed step-by-step instructions including when to call other tools (get_section_details, submit_answer), how to present questions, handle edge cases (Other, Skip), and progress tracking. Explicitly covers when to use and what to avoid.

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 full burden but fails to disclose side effects, idempotency, or resource creation. 'Start or refine' is vague and does not explain behavior on repeated calls or state changes.

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, front-loaded with purpose, no wasted words. Ideal conciseness.

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?

Lacks explanation of return values, subsequent steps, or how 'refine' differs from 'start'. No output schema and no annotations, so the description should provide more context for an interactive build 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 description adds meaning beyond the schema by noting that omitting 'theme' shows the 30 criteria first. This clarifies a key usage pattern. Schema coverage is 100%, so baseline is 3; the added context raises it to 4.

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 starts or refines a guided capstone build and connects it to learning 30 certification tasks. It is specific about the resource (capstone build) and action, but does not distinguish from siblings like scaffold_project or capstone_build_step.

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?

No guidance on when to use this tool versus alternatives like scaffold_project, capstone_build_step, or others. The description does not provide context for optimal usage or 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?

With no annotations, the description fully discloses behavioral traits: exam start, scoring, question presentation flow, progress tracking via TodoWrite, and edge case handling. Very transparent.

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?

Well-structured with sections (IMPORTANT, PROGRESS TRACKING, EDGE CASES) and front-loaded with key exam specs. Slightly verbose but necessary detail for a complex tool.

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 all aspects: exam specs, first question flow, progress tracking, edge cases. No output schema, but return behavior is implied. Complete for the tool's 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?

Input schema has no parameters (empty), so description adds no param info beyond schema. Baseline 4 applies for zero 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 it starts a full 60-question practice exam with domain breakdown and scoring details. It distinguishes itself from sibling tools like start_assessment and submit_exam_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?

Provides explicit instructions on how to present the first question via AskUserQuestion, details progress tracking, and covers edge cases (Other, Skip). However, lacks explicit guidance on when NOT to use this tool vs alternatives.

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 fully discloses key behavioral traits: deterministic results, finality, two-step presentation, and handling of 'Other' and 'Skip' edge cases, including the instruction not to dispute results.

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 well-structured with sections and bullet points, but it is somewhat lengthy. All content is relevant, though some details could be condensed.

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?

Despite lacking an output schema, the description adequately covers the output behavior (text then prompt). It provides enough context for correct tool usage, including edge cases.

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 baseline is 3. The description adds no additional meaning beyond the schema's property descriptions and enum values, hence no extra value.

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 'grades a certification exam answer', using a specific verb and resource. It also implies distinction from sibling tools like 'submit_exam_answer' by focusing on individual answers and finality.

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 provides explicit instructions on how to present results and handle edge cases, but it does not clarify when to use this tool over siblings like 'submit_exam_answer' or when not to use it.

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 discloses that grading is deterministic and specifies the presentation behavior. However, since no annotations are provided, it should cover more behavioral details such as error handling, side effects (e.g., recording the answer), and permissions.

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 front-loaded with the purpose and includes necessary instructions. It is slightly lengthy due to the detailed two-step guide, but every sentence serves a purpose. Could be trimmed slightly without losing 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?

The description explains the post-submission presentation flow and grading behavior, which is adequate given no output schema. However, it does not clarify whether the answer is saved permanently or any system limits (e.g., one submission per question).

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?

Input schema has 100% coverage with descriptions for all parameters, so the baseline is 3. The description adds context about the answer format (A, B, C, D) and the two-step flow, but does not provide additional semantic 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?

The description clearly states 'Submit an answer for a practice exam question' with a specific verb and resource, and distinguishes it from sibling tools like 'submit_answer' by specifying it's for practice exams and includes a two-step presentation flow.

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 provides detailed usage instructions, including the two-step presentation process and the requirement to show results as regular chat text. However, it does not explicitly state when not to use this tool or list alternative tools for other contexts.

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