Resolve a country name to the correct format accepted by Himalayas filters. Useful for fuzzy matching user input.
| Name | Required | Description | Default |
|---|---|---|---|
| country_string | Yes | The country name to get the correct name for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description has full responsibility. It mentions the output format ('correct format') but does not disclose what happens with invalid input, normalization behavior, or exact return value. The description is too thin to fully inform an agent about edge cases.
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 sentences with no wasted words. It front-loads the core purpose and then adds a practical usage hint. Each 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?
For a simple one-parameter tool with no output schema, the description covers the core function and usage context. However, it lacks explicit detail on the return format (beyond 'correct format') and failure behavior, which would be useful for an agent to fully predict the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, so the schema already documents its meaning. The description adds context about fuzzy matching but does not provide additional semantics beyond what the schema states. Baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Resolve a country name to the correct format accepted by Himalayas filters.' It distinguishes itself from other tools by referencing the specific 'Himalayas filters' context. However, it does not explicitly name or contrast with any sibling tool, so it doesn't fully earn a 5.
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 includes a usage hint: 'Useful for fuzzy matching user input.' This gives some context on when to use it, but it doesn't explicitly say when not to use it or mention alternatives. For a helper tool with no obvious siblings, this is adequate but not exceptional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct resource and action: job posting vs job browsing vs job management vs company management vs talent search vs profile editing vs messaging vs application tracking. Even similar tools like get_companies and search_companies are clearly differentiated by purpose and parameters. Overlapping concepts (e.g., post_job_public vs create_company_job) have explicit differences in authentication and cost.
All tools use snake_case and follow a verb-first pattern (add_, get_, create_, update_, delete_, search_, list_, send_, etc.). There are minor deviations like 'show_company_job' instead of 'get_company_job' and 'mark_message_read' which is a verb+noun+adjective, but the overall style is consistent and predictable across the 41 tools.
With 41 tools, this is well into the 'too many' range (25+). While the breadth reflects a comprehensive jobs platform, the number is excessive for an agent to efficiently navigate. Many tools could be consolidated (e.g., profile management could merge add_education/add_experience/update_profile, or company perks could be combined with profile updates). The tool count detracts from usability.
The tool set covers the full lifecycle: job posting (create, update, delete, list), job discovery (browse, search, related), company management (profile, perks, tech stack), talent search and messaging, application tracking (save, get, remove, update status), and data analytics (salary, statistics). Minor gaps exist—no delete/update for education or experience, no explicit 'close job' action—but these are edge cases and agents can work around them.