Server Quality Checklist

Tool Scores

• get_blog_postsC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool retrieves 'recent analysis' but doesn't specify what 'recent' means (timeframe), whether results are paginated, if authentication is required, rate limits, or what format the return data takes. The description is insufficient for a tool with no annotation coverage.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is efficiently structured in a single sentence that front-loads the core purpose. It lists content types concisely without unnecessary elaboration. While it could be slightly more structured, it avoids redundancy and stays focused on the essential information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the return data looks like (structure, fields), doesn't mention error conditions, and provides minimal behavioral context. The description should do more to compensate for the lack of structured metadata about this read operation.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so the schema already fully documents both parameters (limit and post_type). The description adds no parameter-specific information beyond what's in the schema - it doesn't explain default behavior when parameters aren't provided or provide additional context about the post_type values. Baseline 3 is appropriate when schema does all the work.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Get recent analysis from AI Takeover Tracker's blog' with specific content types listed (occupation spotlights, news commentary, trend reports). It distinguishes from siblings like 'get_latest_news' by specifying blog content rather than general news, but doesn't explicitly contrast with all siblings.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives. It mentions content types but doesn't specify when to choose this over 'get_latest_news' or other sibling tools, nor does it mention any prerequisites or exclusions for usage.

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

• get_personal_factorsC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It describes what the tool does (gets questions that adjust risk scores) but lacks behavioral details such as whether it's read-only, if it requires authentication, rate limits, error handling, or what the output format looks like. It adds minimal context beyond the basic function.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately sized with two sentences. The first sentence clearly states the purpose and provides an example, while the second adds context about the broader experience. It's front-loaded with the main function, though the second sentence could be seen as slightly promotional rather than essential.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no annotations and no output schema, the description is incomplete for a tool that likely returns structured data (personalization questions). It doesn't explain what the output contains, how questions are formatted, or any behavioral traits. For a tool with one parameter but potentially complex output, more detail is needed to be fully helpful.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema has 100% description coverage, with one parameter 'identifier' documented as 'Occupation slug or SOC code'. The description doesn't add any meaning beyond this, as it doesn't explain parameter usage, formats, or examples. Baseline score of 3 is appropriate since the schema does the heavy lifting.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Get personalization questions for an occupation' with specific examples like 'What type of accounting do you specialize in?' and mentions they adjust risk scores. It distinguishes from siblings like get_occupation_risk or get_occupation_tasks by focusing on personalization questions rather than risk scores or tasks directly. However, it doesn't explicitly differentiate from get_specializations, which might overlap in concept.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives. It mentions the full personalized scoring experience is available elsewhere, but doesn't specify when to choose this tool over siblings like get_occupation_risk or get_specializations, nor does it outline prerequisites or exclusions for usage.

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

• get_occupation_tasksB
  3.2/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It describes what the tool returns (task-level breakdowns) but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, rate limits, error conditions, or what format the breakdown comes in. The reference to an external website adds some context but doesn't fully compensate for missing behavioral transparency.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately concise with two sentences that efficiently convey the core purpose and additional context. The first sentence clearly states the main function, and the second provides useful supplementary information about the full report. There's minimal waste, though the external website reference could be considered slightly extraneous.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a single-parameter tool with good schema coverage but no annotations or output schema, the description provides adequate basic context about what the tool does. However, it lacks details about return format, error handling, and behavioral characteristics that would be important for an AI agent to use this tool effectively. The reference to external content partially compensates but doesn't fully address completeness gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema has 100% description coverage for its single parameter ('identifier'), so the baseline is 3. The description doesn't add any parameter-specific information beyond what's in the schema (which documents it as an 'Occupation slug or SOC code'). No additional syntax, format, or usage details are provided about the parameter.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Get task-level AI capability breakdown' with specific details about analyzing job tasks for automability. It distinguishes itself from siblings like 'get_occupation_risk' by focusing on task-level analysis rather than overall risk scores. However, it doesn't explicitly contrast with all siblings like 'get_career_transitions' or 'get_specializations'.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage context by mentioning 'which specific job tasks are most/least automatable' and referencing a full report website, suggesting this tool provides detailed breakdowns. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_occupation_risk' (overall risk) or 'search_occupations' (search functionality), nor does it provide exclusion criteria or prerequisites.

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

• get_career_transitionsA
  3.5/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function but lacks details on behavioral traits such as whether it requires authentication, has rate limits, returns paginated results, or what format the recommendations are in (e.g., list of occupations with scores). For a tool with no annotations, this is a significant gap in transparency.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, well-structured sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with the core action ('Get recommended career transition paths') and adds qualifying details concisely. Every part of the sentence earns its place by specifying the input and output context.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (providing transition recommendations based on risk and skills), lack of annotations, and no output schema, the description is minimally complete. It states what the tool does but does not cover behavioral aspects or output details. For a tool with no structured support, it should do more to explain how results are structured or any limitations, making it adequate but with clear gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, with the parameter 'identifier' documented as 'Occupation slug or SOC code.' The description adds no additional parameter semantics beyond this, as it does not explain what 'identifier' entails (e.g., examples of slugs or SOC codes). With high schema coverage, the baseline score is 3, as the schema handles the parameter documentation adequately.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with a specific verb ('Get') and resource ('recommended career transition paths'), and distinguishes it from siblings by specifying 'from a given occupation to lower-risk alternatives that leverage similar skills.' This differentiates it from tools like get_occupation_risk or search_occupations by focusing on transition recommendations rather than risk assessment or general search.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage context by specifying 'from a given occupation to lower-risk alternatives,' suggesting it's for risk mitigation scenarios. However, it does not explicitly state when to use this tool versus alternatives like get_occupation_risk (which might provide risk data without transitions) or search_occupations (which might find occupations without transition paths). No explicit exclusions or prerequisites are mentioned.

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

• get_latest_newsA
  3.5/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the newsletter is 'curated daily', hinting at freshness and editorial selection, but lacks details on output format (e.g., structured data vs. raw text), error handling, or any rate limits. For a tool with zero annotation coverage, this leaves significant 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, well-structured sentence that efficiently conveys the tool's function and scope without redundancy. It is front-loaded with the core action ('Get the latest AI & jobs newsletter edition') and adds clarifying details ('curated daily briefing...') that earn their place by enriching understanding.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on output (e.g., format, structure) and behavioral context (e.g., update frequency, data source), which could help the agent use it more effectively. It meets the minimum viable threshold but has clear gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. A baseline of 4 is applied as it compensates adequately by not needing to explain parameters, though it doesn't enhance semantics beyond the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with specific verbs ('Get', 'curated') and resources ('latest AI & jobs newsletter edition', 'daily briefing on AI's impact on the workforce'). It distinguishes itself from siblings by focusing on a newsletter edition rather than blog posts, career transitions, or occupation data, making the purpose specific and differentiated.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage for retrieving a curated newsletter, but provides no explicit guidance on when to use this tool versus alternatives like 'get_blog_posts' or 'search_occupations'. There is no mention of prerequisites, frequency limitations, or contextual triggers, leaving the agent with minimal direction on optimal usage scenarios.

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

• get_occupation_riskA
  3.8/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what information is returned (score, risk tier, etc.) and mentions the existence of a more detailed external report, which adds useful context. However, it doesn't disclose rate limits, authentication requirements, data freshness, or error conditions that would be important for an agent to know.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately sized with two sentences. The first sentence efficiently states the purpose and outputs. The second sentence adds valuable context about the external report without being redundant. There's no wasted language, though it could be slightly more structured for optimal agent comprehension.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with no annotations and no output schema, the description provides good information about what data is returned. However, it doesn't specify the format or structure of the return values (e.g., whether it's a JSON object with specific fields), which would be important for an agent to process the results correctly. The mention of the external report adds context but doesn't fully compensate for the lack of output details.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  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 the 'identifier' parameter thoroughly. The description doesn't add any additional parameter information beyond what's in the schema, but since there's only one parameter and it's well-documented in the schema, the baseline of 3 is appropriate. The description's clarity about what the tool returns provides good context for parameter usage.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the specific action ('Get AI displacement risk for a specific occupation') and lists the exact outputs (score, risk tier, protective factors, labor data, displacement timeline). It distinguishes from siblings like 'get_occupation_tasks' or 'search_occupations' by focusing on risk assessment rather than task lists or search functionality.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage by mentioning it provides a 'summary' and that a 'full interactive report' exists elsewhere, suggesting this is for quick overviews. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_latest_score' or 'search_occupations', nor does it provide clear exclusions or prerequisites for usage.

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

• get_latest_scoreA
  4.2/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses that the score is 'daily composite' and 'updated daily,' which adds useful behavioral context about data freshness. However, it lacks details on potential errors, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, well-structured sentence that efficiently conveys the tool's purpose, what the score represents, and update frequency. Every part adds value without redundancy, making it appropriately sized and front-loaded.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is largely complete, covering purpose and behavior. However, without an output schema, it could benefit from mentioning the return format (e.g., numeric score or structured data), slightly reducing completeness.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for not adding unnecessary information beyond the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the specific action ('Get') and resource ('current AI Takeover Index'), including what it is ('a daily composite score (0-100%) tracking AI's progress toward automating white-collar work'). It distinguishes this tool from siblings by focusing on a specific index score rather than blog posts, news, occupations, etc.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use this tool ('Get the current AI Takeover Index'), including its purpose and update frequency ('Updated daily'). However, it does not explicitly state when not to use it or name alternatives among siblings, such as when other tools might be more appropriate for related data.

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

• get_specializationsA
  4.4/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses key behavioral traits: returns multiple variants with different risk scores, and highlights significance of score differences (e.g., Staff Accountant 45.6 vs Business Analyst 32.1). However, it doesn't mention response format, pagination, or error handling.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences with zero waste: first defines purpose with concrete example, second provides explicit usage guidelines with rationale. Front-loaded with core functionality, and every sentence adds essential value.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given 1 parameter with full schema coverage and no output schema, the description is largely complete: explains purpose, usage, and output implications (variants with risk scores). It could mention response structure or error cases, but covers core context well for a read-only lookup tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100% (parameter 'identifier' described as 'Occupation slug or SOC code'), so baseline is 3. The description adds no additional parameter semantics beyond what the schema provides, focusing instead on usage context and output implications.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Get specialization variants for an occupation' with specific examples (e.g., 'accountants' has variants like Tax Accountant). It distinguishes from siblings by focusing on occupation variants rather than general occupation data (get_occupation_risk), tasks (get_occupation_tasks), or searches (search_occupations).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Explicitly states when to use: 'ALWAYS use this when a user asks about a specific job title that might be a variant of a broader occupation.' It provides a clear alternative context (risk score differences matter) and distinguishes from other tools by emphasizing variant-specific data.

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

• search_occupationsA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's scope (59,000+ occupations), return format (matching jobs with risk scores), and important behavioral nuance about specialization variants. However, it doesn't mention potential limitations like search algorithm behavior or error conditions.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is perfectly structured with two sentences: the first states the core functionality, the second provides crucial usage guidance. Every word earns its place, and the 'IMPORTANT' flag appropriately highlights critical information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a search tool with no annotations and no output schema, the description provides excellent context about what the tool does and how to use it effectively. The only gap is the lack of information about return format details, but given the tool's relatively simple purpose, this is a minor omission.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  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 both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. The baseline score of 3 reflects adequate coverage through the schema alone.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with specific verbs ('search', 'returns') and resources ('59,000+ occupations', 'matching jobs with AI displacement risk scores'). It distinguishes from sibling tools like 'get_occupation_risk' by emphasizing search functionality rather than direct retrieval.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  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 this tool vs alternatives: it instructs to search for base occupations when specific titles aren't found, then use 'get_specializations' for variants. This clearly differentiates from sibling tools and addresses common usage scenarios.

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