xing-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: search for jobs, get job details, search across pages, and get company jobs. The two search tools are differentiated by pagination and deduplication, with clear guidance to prefer the paginated one for multi-page queries.
Naming Consistency5/5All tools follow the verb_noun pattern with consistent snake_case: search_jobs, search_jobs_paginated, get_job_details, get_company_jobs. This makes the tool set easy to predict and navigate.
Tool Count5/5Four tools is well-scoped for a job search server, covering search, detail retrieval, pagination, and a company filter without redundancy or bloat.
Completeness4/5The domain of job searching is well covered: searching with filters, pagination, job details, and company-specific listings. Minor gaps like browsing by category or filtering by salary range exist, but the core workflow is complete.
Average 4.3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior2/5
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 states the action 'List' without disclosing additional behavior such as pagination, error handling, or response format. Since there is no readOnlyHint annotation, the agent must infer safety from the word 'List'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the purpose first and a clearly formatted Args section. Every word adds value; the example is concise and directly relevant to the parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single required parameter and an output schema, the description covers the essential input semantics well. However, it lacks any context about when to choose this tool over its siblings, making it slightly incomplete for an agent deciding between tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only specifies `company` as a string with no description. The description adds critical details: 'The company's XING page slug or full page URL — the part after /pages/, e.g. "exxetaag" for xing.com/pages/exxetaag.' This gives the exact format and an example, far exceeding the schema's empty description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List the open positions published on a company's XING page.' This uses a specific verb ('List') and a specific resource (jobs on a company's page), distinguishing it from siblings like `get_job_details` (specific job) and `search_jobs` (global search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving jobs from a specific company page via the `company` parameter, but it does not explicitly mention when to prefer alternatives like `search_jobs` for cross-company searches. This leaves usage context partially implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It does disclose that the description is converted to markdown and supports truncation. However, it doesn't mention error handling, rate limits, authentication, or what happens with invalid identifiers. For a read-only getter this is acceptable but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose. The Args section is clear and directly addresses parameters, though it could be slightly more compact. Every sentence contributes to understanding the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description needn't explain return values. The tool has only two parameters (one optional) and no nested objects, so the description covers the essential input semantics and behavior. Minor gaps like edge cases (e.g., what happens with very short descriptions) exist but are not critical for a simple getter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description coverage (0%), but the description thoroughly explains both parameters: identifier accepts a URL or slug with a concrete example, and description_max_chars controls truncation length. This adds meaning beyond the bare schema and compensates for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches the full details of a single XING job posting, which distinguishes it from the sibling search tools. It uses a specific verb 'Fetch' and identifies the resource as 'one XING job posting' with details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this tool is for retrieving a specific job given a URL or slug. While it doesn't explicitly say 'use search_jobs first to find jobs', the singular focus and presence of sibling search tools imply the appropriate use case. No exclusions are mentioned, but the purpose itself is a strong signal.
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?
With no annotations, the description carries the full burden and does well: it discloses salary estimate presence, page size limits, employment_type URL filter constraints, and return structure. It does not mention authentication or error behavior, but for a search tool these are not glaring omissions. Overall, strong 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with an intro, a notable behavior note, a clearly formatted Args section, and a Returns line. Every sentence adds relevant information—nothing is filler. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and all parameters are optional, the description is complete enough: it explains all params, return keys, and behavioral quirks. It does not need to duplicate the output schema. The only minor gap is not addressing sibling tool selection, but that is a usage guideline concern rather than contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions, but the description adds meaningful semantics for all five parameters: keywords with examples, location with cities, radius in kilometers, employment_type restricted to FULL_TIME/PART_TIME, and page with 1-based numbering and page size. This fully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search job postings on XING' with a specific verb and resource, plus DACH region context. However, it does not explicitly differentiate from the sibling tool 'search_jobs_paginated', even though it describes page-based search behavior. This is clear but lacks direct sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides useful parameter usage guidance such as German terms matching better and employment_type restrictions. However, it does not state when to use this tool versus alternatives like search_jobs_paginated or get_company_jobs. Usage context is implied by the purpose but not made explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
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 behaviors: pagination behind a rate limiter, deduplication, ~1 second request spacing, and time estimates, giving the agent realistic expectations about performance and side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: two sentences of purpose/usage followed by a clean argument list. Every sentence adds value, and the argument definitions are direct without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema (not shown) covers return format, the description covers all other essentials: parameters, pagination behavior, rate limiting, and deduplication. The sibling comparison and explicit cap complete the picture for a complex paginated tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description hand-documents all five parameters with meaningful details: radius is in kilometres, employment_type accepts FULL_TIME or PART_TIME, and max_results is capped at 200. This adds crucial semantics beyond the bare schema properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search XING jobs across multiple pages, deduplicated,' which clearly states the action, resource, and scope. It also distinguishes itself from the sibling tool `search_jobs` by noting it is the paginated alternative, avoiding repeated calls.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to use this tool 'instead of calling `search_jobs` repeatedly,' providing clear when-to-use guidance. It also explains the rate limiting and deduplication benefits, helping the agent choose correctly among siblings.
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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