From career-navigator
Generates a market intelligence brief for target roles, covering demand trends, AI displacement signals, and geographic competitiveness. Invokes a market-researcher agent.
How this skill is triggered — by the user, by Claude, or both
Slash command
/career-navigator:market-briefThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Recommended:** run **weekly** via Cowork **`/schedule`** (e.g. same day each week) so market signals stay fresh without daily noise. Example scheduled payload:
Recommended: run weekly via Cowork /schedule (e.g. same day each week) so market signals stay fresh without daily noise. Example scheduled payload:
Run
/career-navigator:market-brief(Career Navigatormarket-briefskill) for my configured{user_dir}.
Invoke the market-researcher agent to generate a current market intelligence brief grounded in the user's role targets and location preferences.
Important invocation/data-source rules:
market-researcher (no aliases).profile.md, tracker.json, ExperienceLibrary.json, analyst norm tables, and AI report) unless the user explicitly asks for live web sourcing.Read {user_dir}/CareerNavigator/profile.md.
If target roles are missing:
"I need your target role(s) to generate a market brief. Run
/career-navigator:launch(or updateCareerNavigator/profile.md) with your target roles first."
If location preferences are missing, continue but mark geographic confidence as limited.
Optionally read:
{user_dir}/CareerNavigator/tracker.json for user-specific conversion/timeline signals{user_dir}/CareerNavigator/ExperienceLibrary.json for capability-fit contextHand off to market-researcher with:
CareerNavigator/profile.mdCareerNavigator/tracker.json (if present)CareerNavigator/ExperienceLibrary.json (if present)If the user asks about a specific role/geography, prioritize that in the brief and treat other profile targets as secondary.
If invocation fails due to agent naming/tooling:
market-researcher name.Render the returned output in this structure:
**Market Brief** — {today's date}
Target role(s): {list}
Geography: {scope}
Confidence: {Preliminary / Directional / Moderate / High}
HIGHLIGHTS
- Demand: {1 line}
- AI outlook: {1 line}
- Geography: {1 line}
ROLE DEMAND TRENDS
{role-by-role demand posture and implications}
AI/AUTOMATION DISPLACEMENT OUTLOOK
{high-risk vs durable task clusters + positioning shift}
GEOGRAPHIC SIGNALS
{market-by-market competitiveness and timeline implications}
PRIORITIZED NEXT MOVES (30-60 days)
1. ...
2. ...
3. ...
Keep the brief practical: concise, evidence-based, and directly tied to search decisions.
Write the rendered brief to {user_dir}/Market-Brief-{YYYY-MM-DD}.md in its own file-write call.
If the file tool fails: output the full brief in a fenced markdown block and tell the user to save manually; skip the index update if the file was not saved.
On success, update {user_dir}/CareerNavigator/artifacts-index.json in a separate call — append:
{
"id": "{uuid}",
"type": "market_brief",
"filename": "Market-Brief-{YYYY-MM-DD}.md",
"path": "{user_dir}/Market-Brief-{YYYY-MM-DD}.md",
"target_company": null,
"target_role": null,
"date_created": "{today}",
"source": "generated",
"notes": "Market intelligence brief — {comma-separated target roles}"
}
Invoke the writer agent in market-brief-pdf mode, passing:
The writer converts the markdown to PDF, saves it alongside the markdown in {user_dir}/, and presents the confirmed PDF path to the user as the completion deliverable for this task.
Based on the top recommendation:
/career-navigator:search-jobs with refined role/location filters./career-navigator:assessment and then /career-navigator:tailor-resume./career-navigator:follow-up and /career-navigator:track-application.npx claudepluginhub tmargolis/career-navigator --plugin career-navigatorSuggests non-obvious career role opportunities by analyzing transferable strengths and market conditions. Invokes honest-advisor and market-researcher agents, then writes scoring signals for job-scout.
Assesses AI disruption risk to user's job role over next 12 months using live research, then delivers evaluation and 6-month mitigation plan. Triggers on career impact queries.
Generates synthetic job description for ideal role from career history files, preferences, and high-scoring assessment patterns. Outputs Markdown file.