Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tmargolis/career-navigator --skill career-plangit clone --depth 1 https://github.com/tmargolis/career-navigatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tmargolis/career-navigator/career-plan)<a href="https://agentmods.dev/skills/tmargolis/career-navigator/career-plan"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/career-plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tmargolis/career-navigator/career-plan"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/career-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.01577 |
| Opus 5 | $0.00033 | $0.00788 |
| Sonnet 5 | $0.00013 | $0.00315 |
| Haiku 4.5 | $0.00007 | $0.00158 |
Grade A, and why
career-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run career-plan to produce a realistic career plan, a human-readable report
at {user_dir}/CareerNavigator/career-trajectory.md, and a structured
career_trajectory_v1 artifact at
{user_dir}/CareerNavigator/career-trajectory-data.json.
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-data.json{user_dir}/CareerNavigator/career-trajectory-{as_of}-{ideal_role_slug}.md(versioned report snapshot){user_dir}/CareerNavigator/career-trajectory-data-{as_of}-{ideal_role_slug}.json(versioned data 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:launchto initializeCareerNavigator/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.mdand 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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 143 lines · 66 tokens per session scan A d4e9e5870461
career-plan is a skill published in the GitHub repository tmargolis/career-navigator (13 stars, last pushed 11d ago), licensed Apache-2.0. It adds 66 tokens to every session and 1,577 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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