AI Dev Jobs MCP workflow skill. Use this skill when the user needs Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
AI Dev Jobs MCP workflow skill. Use this skill when the user needs Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/ai-dev-jobs-mcp from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
AI Dev Jobs MCP
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: MCP Configuration, Available Tools, Limitations.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
Use when helping a user search for AI or ML engineering jobs
Use when an agent needs to look up which companies are hiring for specific AI roles
Use when building recruiting or talent-matching workflows
Use when analyzing the AI job market (open positions, top companies, role distribution)
Use when the request clearly matches the imported source intent: Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
Validate the result against the upstream expectations and the evidence you can point to in the copied files.
Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.
Imported Workflow Notes
Imported: Overview
AI Dev Jobs is a remote MCP server that gives AI agents access to a live index of AI and ML job listings. As of April 17, 2026, the live MCP stats report 8,405 active roles across 489 companies, a $213,500 median salary, and 600 new jobs this week. Agents can search jobs by role, location, or company, retrieve full job details, list hiring companies, match roles to a profile, and get salary or aggregate market statistics. It is designed for AI agents that assist with job searching, recruiting, or labor market analysis.
Imported: MCP Configuration
Add the AI Dev Jobs MCP server to your client configuration. The endpoint uses streamable HTTP and requires no authentication.
Use @ai-dev-jobs-mcp to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @ai-dev-jobs-mcp against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @ai-dev-jobs-mcp for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @ai-dev-jobs-mcp using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Imported Usage Notes
Imported: Examples
Example 1: Find Remote ML Jobs
Use @ai-dev-jobs-mcp to find remote machine learning engineer positions.
The agent will call search_jobs({ query: "machine learning engineer", location: "remote" }) and return matching listings.
Example 2: Check Which Companies Are Hiring
Use @ai-dev-jobs-mcp to list all companies currently hiring for AI roles.
The agent will call list_companies({}) and return companies sorted by number of open positions.
Example 3: Get Job Market Overview
Use @ai-dev-jobs-mcp to show current AI job market statistics.
The agent will call get_stats({}) and return aggregate data on listings, top employers, and role distribution.
Example 4: Get Full Job Details
Use @ai-dev-jobs-mcp to get the full details for job ID abc123.
The agent will call get_job({ id: "abc123" }) and return the complete listing with requirements and application link.
Example 5: Match Jobs to a Candidate Profile
Use @ai-dev-jobs-mcp to match remote LLM roles to a senior Python and PyTorch profile.
The agent will call match_jobs({ skills: ["python", "llm", "pytorch"], workplace: "remote" }) and return suitable listings.
Example 6: Compare Salary Data
Use @ai-dev-jobs-mcp to compare senior LLM salary data.
The agent will call get_salary_data({ tag: "llm", level: "senior" }) and summarize available compensation ranges.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Use search_jobs with specific keywords for targeted results rather than broad queries
Use listcompanies to discover companies, then searchjobs filtered by company name for focused searches
Use get_stats to provide users with market context before diving into specific listings
Use match_jobs when the user gives skills, seniority, location, or work arrangement preferences
Use getsalarydata only as market context; remind users that listings and compensation change quickly
Combine with resume or cover letter skills to create end-to-end job application workflows
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Imported Operating Notes
Imported: Best Practices
Use search_jobs with specific keywords for targeted results rather than broad queries
Use list_companies to discover companies, then search_jobs filtered by company name for focused searches
Use get_stats to provide users with market context before diving into specific listings
Use match_jobs when the user gives skills, seniority, location, or work arrangement preferences
Use get_salary_data only as market context; remind users that listings and compensation change quickly
Combine with resume or cover letter skills to create end-to-end job application workflows
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/ai-dev-jobs-mcp, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: Available Tools
search_jobs
Search the job index by keyword, location, company, or work arrangement. Returns matching listings with title, company, location, and salary information.
