# /html-report - Generate Application Tracker Dashboard
Generate a self-contained HTML dashboard from `job_search_tracker.csv` and the application archives under `documents/applications/`. The output is a single `.html` file — no server, no dependencies — that can be opened directly in a browser.
## Step 0: Parse Arguments
- No argument → output to `reports/application-dashboard.html`
- A path argument (e.g. `/html-report ~/Desktop/report.html`) → use that path
- `--open` flag → after writing, tell the user to open the file (cannot open a browser directly)
Create `reports/` if it does not exist.
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## Step 1: Collect Data
Read in parallel:
1. **`job_search_tracker.csv`** — the primary source. Parse every row into a record with fields:
`date`, `company`, `sector`, `role`, `role_type`, `channel`, `status`, `contact_person`, `fit_rating`, `notes`, `cv_file`, `cover_letter_file`, `source`, `deadline`
Rows written before `deadline` existed have thirteen fields and no fourteenth value. Treat the missing field as empty - never drop the row, and never infer a deadline from its `date`.
2. **`documents/applications/*/outcome.md`** — for each resolved application, read the outcome file to get the exact interview stages reached (the checkboxes) and any notes. Merge this into the matching tracker row by company+role fuzzy match (lowercase, ignore punctuation). If an archive exists for a row but there is no match, attach it as extra context anyway.
Status normalisation — map tracker values to six canonical buckets before computing stats:
- `drafted` → **Drafted** (documents written by `/apply`, not yet submitted)
- `applied` → **Active** (resume submitted, no further signal)
- `interview` → **Interview**
- `offer` → **Offer**
- `hired` → **Hired**
- `rejected` / `no_response` / `no response` / `offer_declined` / `offer declined` / `withdrawn` → **Rejected/Closed**
- anything else → **Rejected/Closed**, and name the unrecognised value once in the status breakdown — matching is case-insensitive
The bucket map tolerates the legacy space spellings on read so nothing written before
the canonical forms were locked drops out of the stats; the **Tracker status vocabulary**
in `/outcome` is the authoritative set.
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## Step 2: Compute Summary Stats
From the normalised data compute:
**Drafted rows are excluded from every statistic below** — they were never submitted. Report the Drafted count on its own, and include it only in the status breakdown.
- **Total applications**
- **By status bucket:** count per bucket
- **By sector:** count per unique sector value
- **By channel:** portal vs online vs referral vs other
- **By year/season:** group by the `date` field (which may be a year like `2025` or a full date)
- **Funnel rates:** what % progressed past resume screen (reached Interview or beyond). Compute stage-reached from history, not current status: an application counts as having reached a stage when its current status implies it **or** its merged `outcome.md` stage checkboxes (Step 1.2) show the stage was reached - a `rejected` row whose outcome file ticks an interview stage reached Interview, and a `hired` row reached every stage before Hired. Current status alone structurally undercounts every earlier stage: a finished search would read as though nobody ever interviewed.
- **Rejection rate:** true rejections (`rejected`, `no_response`) ÷ applications with a final outcome. `offer_declined` (the candidate turned the offer down - a success) and `withdrawn` (candidate-initiated) are not rejections and stay out of the numerator; Interview and Offer rows are still unresolved, so they stay out of the denominator along with Active. The Rejected/Closed status *bucket* still groups all closed rows for the doughnut - the rate just must not reuse the bucket blindly.
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## Step 3: Generate the HTML
Write a single self-contained HTML file. All CSS is inline in a `