name: personal-schedule-manager description: > Converts a Goal (G-xxx) into executable Schedule entries (S-xxx) with temporal semantics. Version: 1.1 Author: Entropy Control Theory License: MIT
Based on: Structure DNA v1.0, M-PPS v1.0, PROFILE-GENERATOR-SPEC v1.0

personal.schedule.manager — v1.1

Goal

Translate goal intentions into one or more S- entries with start/due/duration, moving state to scheduled.
This version adds energy-aware scheduling: before planning, it ensures and reads /ledger/profile.json to align execution time with the user’s chrono-cognitive energy curve.

Inputs

Outputs

Writes entries to /ledger/schedule.json following the Structure DNA Field Genome:

Required:

• id (S-xxx)
• title
• status = "scheduled"
• start | due | duration (at least one)
• created_at, updated_at

Optional:

• goal_id, tags, notes, related_entries, dispatch_to

New (v1.1):

• Adds energy_zone (or annotation [energy_zone:peak|stable|low] in notes)

Mechanism

1. Ensure and load profile.json
   • If missing, create /ledger/profile.json from profile.schema.json + profile.defaults.json.
   • Load profile.data[0] for energy curves, constraints, and break preferences.
2. Energy-aware window selection
   • creative → 19:00–22:00 (peak)
   • implementation → 14:00–19:00 (stable)
   • warmup → 10:00–11:00 (low)
   • If the user supplied explicit times, they take precedence; energy windows fill gaps or conflicts.
3. Constraint handling and block slicing
   • Obey must_stop_by = 22:00
   • Skip lunch 12:30–13:30, dinner 18:00–19:00
   • Split long sessions by preferred_block_length = 90–120 min
4. Resolve temporal semantics → ISO timestamps
5. State transition: set status = "scheduled", preserve goal_id, and optionally
   dispatch_to = "reflection.manager" for automatic feedback.

Pseudocode

def schedule_entry(entry, ledger_dir="/ledger"):
    # 1. Ensure and load profile
    ensure_profile(ledger_dir)
    profile = load_json(f"{ledger_dir}/profile.json")["data"][0]

    # 2. Determine energy window
    kind = entry.get("kind") or classify(entry)
    window = choose_window(kind, profile)

    # 3. Apply constraints and compute start/due
    slots = place_with_constraints(
        plan=entry.get("plan"),
        window=window,
        breaks=profile.get("break_preferences"),
        must_stop_by=profile["constraints"]["must_stop_by"],
        block_len=profile["work_style"]["preferred_block_length"]
    )

    # 4. Finalize schedule entry
    entry["start"], entry["due"] = slots[0].start_iso, slots[-1].end_iso
    entry["status"] = "scheduled"
    entry["updated_at"] = now_iso()
    entry["notes"] = (entry.get("notes") or "") + f" [energy_zone:{window.label}]"
    return entry

def choose_window(kind, profile):
    if kind == "creative":       return Window("19:00","22:00","peak")
    if kind == "implementation": return Window("14:00","19:00","stable")
    return Window("10:00","11:00","low")

Example

Input

{
  "goal_id": "G-001",
  "plan": "2 × 2h this week",
  "kind": "creative",
  "notes": "Write Substack demo"
}

Output

{
  "id": "S-101",
  "title": "Write Substack demo",
  "goal_id": "G-001",
  "status": "scheduled",
  "start": "2025-11-03T19:00:00-05:00",
  "due": "2025-11-03T21:00:00-05:00",
  "duration": "2h",
  "notes": "user plan:2x2h; [energy_zone:peak]",
  "created_at": "2025-11-03T13:05:00-05:00",
  "updated_at": "2025-11-03T13:05:00-05:00",
  "dispatch_to": "reflection.manager",
  "related_entries": ["G-001"]
}

Notes

• v1.1 keeps the dispatch rules unchanged — logic is handled inside the Skill runtime.
• If /ledger/profile.json is missing, ensure_profile() bootstraps it automatically.
• Compatible with all other MVP Skills (ledger.registry, reflection.manager, goal.manager).
• Designed for immediate use within the Structure DNA → M-PPS → LLC loop.

“Energy-aware scheduling turns language intention into a rhythm of execution.” — Entropy Control Theory, 2025

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