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 pipeline-dashboardgit 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/pipeline-dashboard)<a href="https://agentmods.dev/skills/tmargolis/career-navigator/pipeline-dashboard"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/pipeline-dashboard/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/pipeline-dashboard"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/pipeline-dashboard.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 | $0.00067 | $0.07889 |
| Opus 5 | $0.00034 | $0.03945 |
| Sonnet 5 | $0.00013 | $0.01578 |
| Haiku 4.5 | $0.00007 | $0.00789 |
Grade A, and why
pipeline-dashboard 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 — 630 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate a self-contained HTML dashboard visualizing the user's job search pipeline and open it in their browser.
Data files
Application data uses the split layout defined in references/tracker-schema.md — read it before any read or write.
| File | Purpose |
|---|---|
{user_dir}/CareerNavigator/tracker.json |
Summary rows for every application — status, outcome, date_applied, plus application, detail_file, latest_stage, latest_stage_date, notes_count, stage_count, contact_count; also pipeline_summary |
{user_dir}/CareerNavigator/applications/<application_id>.json |
stage_history[] + notes[] for one application — the only source of stage transitions |
{user_dir}/CareerNavigator/recommendations.json |
Pre-application roles being considered (count shown at top of funnel) |
{user_dir}/CareerNavigator/ExperienceLibrary.json |
Experience units with performance weights and update log |
{user_dir}/CareerNavigator/artifacts-index.json |
Generated artifacts with ATS scores |
{user_dir}/CareerNavigator/analyst-graph-data.json |
Optional graph data from the analyst report |
Workflow
1. Assemble the data object
Read the files above and build the following JSON object. This will be embedded directly into the HTML file.
What comes from where. The timeline rows, status colors, considering count, and confidence tier come straight from the tracker.json summary rows — no detail file needed, which is the point of the split. The benchmark conversion rates are different: they are computed from stage transitions, and tracker.json no longer contains stage_history. This dashboard renders per-application history, so you must load each application's detail_file explicitly:
- For every summary row with
stage_countgreater than0, read{user_dir}/CareerNavigator/+ itsdetail_fileand use that file'sstage_history[]for the funnel and conversion math. - Skip rows with
stage_count: 0— there is nothing to load. - Warning: computing this dashboard from
tracker.jsonalone fails silently. No error is raised — the funnel and every conversion rate come out at zero ornull, any per-application stage detail renders empty, and the charts still look like real data.
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 · 630 lines · 67 tokens per session scan A 05575738b42b
pipeline-dashboard is a skill published in the GitHub repository tmargolis/career-navigator (13 stars, last pushed 11d ago), licensed Apache-2.0. It adds 67 tokens to every session and 7,889 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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