agentsclimarketplace

Career plan

Skill tmargolis/career-navigator/skills/career-plan

Builds a realistic, honest near/medium/long-term career trajectory and gap analysis using profile + ExperienceLibrary, with market-informed demand and AI/automation displacement outlook. Saves `career-trajectory.md` for downstream job-scout scoring.From its SKILL.md

Install
npx -y skills add tmargolis/career-navigator --skill career-plan

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 14 stars14 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.5 KB, as published. Nobody here has run it

Run career-plan to produce a realistic career plan and a career_trajectory_v1 JSON artifact saved to: {user_dir}/CareerNavigator/career-trajectory.md.

Workflow

Directory sharing (host integration)

If the host UI asks you for a directory to share with an agent during this skill's run, share only your {user_dir} job-search folder (the one containing CareerNavigator/).

All reads/writes for this skill are under:

  • {user_dir}/CareerNavigator/profile.md
  • {user_dir}/CareerNavigator/ExperienceLibrary.json
  • {user_dir}/CareerNavigator/career-trajectory.md
  • {user_dir}/CareerNavigator/career-trajectory-{as_of}-{ideal_role_slug}.md (versioned snapshot)

Do not share the whole workspace or unrelated folders.

1. Confirm required data exists

Read:

  • {user_dir}/CareerNavigator/profile.md
  • {user_dir}/CareerNavigator/ExperienceLibrary.json

If missing, output:

Career plan skipped: run /career-navigator:launch to initialize CareerNavigator/ first.

2. Optional ideal role argument

If the user provides an explicit target (e.g. "for an Applied AI PM role" or "ideal_role: Senior Product Manager"), capture it as ideal_role for targeted gap analysis. Otherwise set ideal_role = null.

3. Market intelligence pass (demand + AI displacement + compensation direction)

Hand off to the market-researcher agent with:

  • The full profile.md and key target roles/locations (as provided).
  • The full ExperienceLibrary.json (so it can align displacement risk to the user's durable strengths).
  • Instruction: produce horizon-aware signals for:
    • Near-term (0–18 months)
    • Medium-term (18 months–4 years)
    • Long-term (4+ years)
  • Compensation trajectory direction (where compensation tends to rise/flatten over the horizons) and geography competitiveness notes.

4. Honest trajectory synthesis

Hand off to the honest-advisor agent with:

  • The market intelligence output from step 3.
  • The full profile + ExperienceLibrary.
  • The optional ideal_role (if present).
  • Also pass along the ## Employment Context (if present) so the plan can account for transition cost (employed) or urgency/runway (unemployed).

Instruction: apply the norm/exception/strategy pattern and output a CareerTrajectoryReport with:

  • Current position assessment (competitive standing + why, grounded in tracker/ ExperienceLibrary when available)
  • Realistic near-term trajectory (0–18 months), ranked by achievability
  • Medium-term trajectory (18 months–4 years), with branches (e.g. IC vs management; startup vs enterprise)
  • Long-term horizon (4+ years), honest framing of ceiling risk/optionality
  • Market-informed gap analysis ranked by ROI (cost x time x impact)

If ideal_role is set:

  • Add an "Ideal role gap analysis" section stating whether the ideal role is realistically achievable, under what conditions/timeline, and what steps would most change the outcome probability.

5. Save career-trajectory.md + career_trajectory_v1 (with versioned history)

Write the final markdown report (including a fenced career_trajectory_v1 JSON block) to:

  1. A versioned snapshot that will not overwrite prior versions:

{user_dir}/CareerNavigator/career-trajectory-{as_of}-{ideal_role_slug}.md

Where:

  • as_of = current date YYYY-MM-DD
  • ideal_role_slug = ideal_role lowercased, trimmed, spaces collapsed to -, and any characters in \ / : * ? " < > | removed; if ideal_role = null, use no-ideal-role.
  1. The canonical file used by downstream consumers (overwritten each run):

{user_dir}/CareerNavigator/career-trajectory.md

Write order (recommended):

  • First write the versioned snapshot.
  • Then write the canonical file as a copy of the same markdown (so job-scout + daily-schedule behavior is unchanged).

Markdown heading requirement: Include a line like: ## Career trajectory analysis ({YYYY-MM-DD}) so daily-schedule can detect staleness.

career_trajectory_v1 JSON block requirement (for job-scout parsing): Your JSON block must look like:

{
  "schema": "career_trajectory_v1",
  "as_of": "{YYYY-MM-DD}",
  "ideal_role": "{string or null}",
  "near_term_roles": [
    { "rank": 1, "role_title": "...", "achievability_label": "high|med|low", "rationale": "..." }
  ],
  "medium_term_roles": [
    { "rank": 1, "role_title": "...", "achievability_label": "high|med|low", "rationale": "..." }
  ],
  "gap_analysis": [
    { "priority_rank": 1, "gap_area": "...", "why_it_matters": "...", "roi_score_0_100": 0, "cost_time_estimate": "...", "execution_risks": "..." }
  ]
}

If the write-to-disk tool fails:

  • Do not invent a save.
  • Show the full markdown report in a fenced code block and tell the user to save it manually to both paths above (versioned snapshot + canonical career-trajectory.md).

6. Present result

Present the conversational CareerTrajectoryReport in chat and confirm:

Saved snapshot to {user_dir}/CareerNavigator/career-trajectory-{as_of}-{ideal_role_slug}.md (and updated {user_dir}/CareerNavigator/career-trajectory.md for downstream scoring).

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.