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PJW2004

job-search-mcp

by PJW2004
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.0.6

  • Disambiguation4/5

    The two tools are clearly differentiated: one searches a single company, the other supports batch searching for multiple companies. While they share the same core purpose, the distinct execution mode (direct results vs. file output) makes them easy to tell apart.

    Naming Consistency5/5

    Both tools follow a consistent 'search_jobs' verb-noun pattern, with the bulk variant clearly suffixed as '_bulk'. This creates a predictable and readable naming scheme.

    Tool Count3/5

    With only 2 tools, the server feels thin for a general job search use case, but the single/bulk search split is a reasonable scope for a focused utility. It is borderline but not extreme.

    Completeness2/5

    The server only supports searching by company name, lacking keyword, location, or other filters. The bulk tool returns a file path, requiring external file access to retrieve results, which is an awkward dead end. Missing detail views or pagination leave significant gaps.

  • Average 4/5 across 2 of 2 tools scored. Lowest: 3.4/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It discloses that it searches JobKorea and Saramin and returns specific fields, and states any company name is searchable. But it doesn't discuss pagination, platform selection behavior, or potential limitations/side effects, which is a gap for a tool with no annotations.

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

    Conciseness2/5

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

    The description is overly verbose with redundant bilingual repetition, repeating the same information in English and Korean. It could be condensed to a single sentence, and the structure is not front-loaded with the most essential information.

    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?

    The description covers purpose, usage, and return fields, and the schema covers parameters. However, it lacks details about pagination behavior, the platform parameter's effect, and the exact response format (e.g., how results are structured), which is important given no output schema.

    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 coverage is 100%, so each parameter is already described. The description adds little beyond the schema, only reiterating that any company name can be searched, which is implied by the schema's description.

    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 searches Korean job postings by company name across JobKorea and Saramin, and lists the returned fields. It distinguishes from the sibling (search_jobs_bulk) by focusing on single-company search, though it doesn't explicitly name the sibling.

    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?

    It explicitly tells the agent to use this tool for questions related to job search, hiring, career, and recruitment. However, it doesn't specify when not to use it or mention alternative tools, so the guidance is clear but lacks exclusions.

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

  • Behavior4/5

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

    No annotations are provided, so the description carries the full burden. It discloses key behaviors: internal parallel search, results saved to a file, and response containing a summary and file path. It also instructs the user to read the file for details. Minor gaps remain, such as file persistence and error handling for invalid inputs, but overall transparency is strong.

    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 compact yet comprehensive. It front-loads the purpose, then explains the process, output, and usage guidance in a logical order. Every sentence adds value, with no fluff or redundancy.

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

    Completeness5/5

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

    Despite no output schema, the description explains the return format (summary and file path) and the side effect of file creation. The tool has only 2 parameters, and the description provides enough context for an agent to invoke it correctly, including use case and performance benefit.

    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 both company_names and platform having clear descriptions. The tool description adds minimal parameter-specific detail beyond what the schema already provides, so the baseline of 3 is appropriate per the rubric.

    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 'Search job postings for multiple companies at once' with a specific verb and resource. It distinguishes from the sibling tool search_jobs by emphasizing bulk search and speed advantage, making its unique purpose unambiguous.

    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: 'Use this when you want to look up many companies at once, such as a list of companies designated for military exemption.' It also directly compares to the alternative: 'much faster than calling search_jobs multiple times,' providing clear guidance on tool selection.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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