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create_company_job

Post a new job on Himalayas. Jobs are free to post and require admin approval before going live. Requires employer authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftNoSave as draft instead of submitting for approval
titleYesJob title (5-80 characters)
extrasNoPaid extras: 'sticky' ($299 pin to top for 30 days), 'newsletter' ($99 feature in weekly email for 30 days)
seniorityYesSeniority levels
max_salaryNoMaximum salary
skill_listNoComma-separated skills
base_salaryNoMinimum salary
descriptionYesJob description (350+ characters, can include HTML)
category_listNoComma-separated job categories
valid_throughNoExpiration date (ISO format, defaults to 30 days from now)
salary_countryNoSalary currency code (default: USD)
employment_typeYesEmployment type
app_link_or_emailYesApplication URL or email address — backend auto-detects via @ check
screening_questionsNoScreening questions for applicants

TDQS

A3.6/5.0
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 mentions that jobs are free, require admin approval before going live, and require employer authentication—key behavioral traits. However, it omits other behaviors like the option to save as a draft (though visible in schema) and any error/validation details. It provides essential context but not exhaustive transparency, hence a 3.

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, focused sentence that front-loads the primary action and immediately relays crucial behavioral notes (free, admin approval, auth). There is zero redundancy or filler, making it concise and effective. It delivers necessary information without wasting words.

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?

The description covers the core context needed for an agent to call the tool correctly: the purpose, the cost implication, the approval process, and authentication. Since the schema provides comprehensive parameter details, the description complements rather than duplicates that info. It could mention return behavior or draft handling, but these are covered in schema or are not essential. Overall, it is adequately complete for a creation tool with rich schema metadata.

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% parameter description coverage, so all 14 parameters are already documented in detail. The tool description adds no additional meaning beyond what the schema provides. Given the high coverage, a baseline of 3 is appropriate, as the description does not enhance parameter understanding.

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 action ('Post a new job on Himalayas') and provides context about free posting and admin approval. However, it does not explicitly differentiate itself from sibling tools like post_job_public or update_company_job, which would elevate it to a 5. Overall, the purpose is unambiguous and specific enough for an agent to select it.

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 gives context about when to use the tool (to post a new job) and includes prerequisites like employer authentication. However, it does not explicitly state when not to use it or mention alternatives (e.g., post_job_public). This implies usage rather than providing explicit routing guidance, so a 3 is appropriate.

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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TDQS

B3.3/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

Resources