feat: rebuild evidence-first application workflow

resume_builder/helpers/cohort_tracker.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python3
+"""Record and summarize the controlled ten-application cohort."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[2]
+TRACKER = ROOT / "job_scout" / "state" / "application_cohort.json"
+FIT_CLASSES = ("core", "adjacent", "stretch")
+CHANNELS = ("strong", "moderate", "weak")
+
+
+def load() -> dict:
+    return json.loads(TRACKER.read_text(encoding="utf-8"))
+
+
+def save(data: dict) -> None:
+    TRACKER.write_text(json.dumps(data, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
+
+
+def summary(data: dict) -> None:
+    applications = data["applications"]
+    print(f"Cohort: {data['cohort_id']} ({len(applications)}/10 applications)")
+    for fit_class in FIT_CLASSES:
+        count = sum(item["fit_class"] == fit_class for item in applications)
+        target = data["target_mix"][fit_class]
+        print(f"  {fit_class}: {count}/{target}")
+    for channel in CHANNELS:
+        count = sum(item["channel"] == channel for item in applications)
+        print(f"  channel {channel}: {count}")
+    outcomes: dict[str, int] = {}
+    for item in applications:
+        outcome = item.get("outcome", "open")
+        outcomes[outcome] = outcomes.get(outcome, 0) + 1
+    print("  outcomes: " + ", ".join(f"{key}={value}" for key, value in sorted(outcomes.items())))
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    subparsers = parser.add_subparsers(dest="command", required=True)
+    subparsers.add_parser("summary")
+    add = subparsers.add_parser("add")
+    add.add_argument("--company", required=True)
+    add.add_argument("--role", required=True)
+    add.add_argument("--date", required=True)
+    add.add_argument("--fit-class", choices=FIT_CLASSES, required=True)
+    add.add_argument("--evidence-fit", type=float, required=True)
+    add.add_argument("--channel", choices=CHANNELS, required=True)
+    add.add_argument("--hard-gate", choices=("pass", "fail"), required=True)
+    add.add_argument("--outcome", default="open")
+
+    args = parser.parse_args()
+    data = load()
+    if args.command == "add":
+        if len(data["applications"]) >= 10:
+            raise SystemExit("cohort already contains ten applications")
+        if args.hard_gate == "fail" and args.fit_class != "stretch":
+            raise SystemExit("a hard-gate failure must be recorded as stretch")
+        data["applications"].append(
+            {
+                "company": args.company,
+                "role": args.role,
+                "application_date": args.date,
+                "fit_class": args.fit_class,
+                "evidence_fit": args.evidence_fit,
+                "hard_gate": args.hard_gate,
+                "channel": args.channel,
+                "outcome": args.outcome,
+            }
+        )
+        save(data)
+    summary(data)
+
+
+if __name__ == "__main__":
+    main()