Ghostlight Instructions

Project Purpose

Ghostlight is a research and implementation home for socially persistent generative agents. The core problem is not "make an LLM sound like a person." The core problem is building an architecture where personality, culture, memory, masks, perception, and incentives can actually survive contact with time, relationships, routine, tonal variation, and pressure.

This repo exists so those organs can live somewhere cleaner than a side chamber inside another project.

Canonical State

Treat state/ghostlight-state.cultcache.jsonl as the CultCache-backed persistence spine for machine-managed state records that have migrated.
Treat state/map.yaml as the canonical human-readable project map.
Treat state/scratch.md as disposable working memory for one bounded subgoal.
Treat state/evidence.jsonl and state/branches.json as readable export surfaces during the persistence migration, not as the long-term direct-write API.
Treat state/evidence.jsonl as the distilled durable ledger of what was learned, verified, rejected, or accepted.
Treat notes/ghostlight-implementation-plan.md as the current implementation plan for the larger organs.
Update state/map.yaml when project understanding changes.
Add evidence after meaningful research, implementation, verification, or rejected paths, but keep it distilled. Routine "I just did this" proof belongs in git history, commits, smoke artifacts, or targeted logs unless it changes what the next session should believe.
Do not turn notes, map, handoff, and evidence into four versions of the same brain. Distinct jobs or bust.

Important Paths

Project root: F:\Projects\Ghostlight
Canonical map: F:\Projects\Ghostlight\state\map.yaml
Scratch surface: F:\Projects\Ghostlight\state\scratch.md
Distilled evidence ledger: F:\Projects\Ghostlight\state\evidence.jsonl
Branch ledger: F:\Projects\Ghostlight\state\branches.json
Handoff summary: F:\Projects\Ghostlight\notes\fresh-workspace-handoff.md
System map: F:\Projects\Ghostlight\notes\ghostlight-current-system-map.md
Implementation plan: F:\Projects\Ghostlight\notes\ghostlight-implementation-plan.md
Architecture rationale: F:\Projects\Ghostlight\notes\architecture-rationale.md
State CLI: F:\Projects\Ghostlight\tools\ghostlight_state.py
CultCache state seam: F:\Projects\Ghostlight\tools\ghostlight_state_store.py
CultCache-Py submodule: F:\Projects\Ghostlight\vendor\cultcache-py
CultCache state store: F:\Projects\Ghostlight\state\ghostlight-state.cultcache.jsonl
Pre-compaction helper: F:\Projects\Ghostlight\tools\ghostlight_prepare_compaction.py

Useful Commands

Use the bundled Python runtime if python is not on PATH:

npm run state:status
npm run state:prepare-compaction
& 'C:\Users\Meta\.cache\codex-runtimes\codex-primary-runtime\dependencies\python\python.exe' '.\tools\ghostlight_state.py' add-evidence --type research --status ok --note '...'
& 'C:\Users\Meta\.cache\codex-runtimes\codex-primary-runtime\dependencies\python\python.exe' '.\tools\ghostlight_state.py' add-branch --id branch-id --hypothesis '...'

Session Bootstrap And Re-entry Protocol

On fresh session load, do this before wandering off into implementation:

read:
- state/map.yaml
- notes/fresh-workspace-handoff.md
- notes/ghostlight-current-system-map.md
- notes/ghostlight-implementation-plan.md
run:
- npm run state:status
restate the current next action from the persisted state before starting edits
if the user only asked to rehydrate or reorient, stop after orientation and wait for an explicit continue instruction instead of treating the persisted next action as permission to start coding

After compaction, resume, or suspicious continuity loss:

rerun npm run state:status
reread state/map.yaml and notes/fresh-workspace-handoff.md
treat the persisted next action as authoritative unless fresh repo evidence contradicts it

When context pressure is clearly rising:

stop broad exploration
narrow the active move to one bounded organ
persist map or handoff updates, plus distilled evidence only when the lesson changes future belief, before the blackout lands

When the user says to prepare for imminent compaction:

immediately write hot live context from memory into a new state/scratch-compaction-<guid>.md file before reading files, running status checks, or doing tidy persistence work
run tools/ghostlight_prepare_compaction.py before editing persistence surfaces
use its warnings as the checklist for map, handoff, scratch, evidence, and git hygiene
update only the state that actually needs to change
after hot context has been folded into canonical persisted state, delete the state/scratch-compaction-<guid>.md file so stale emergency memory does not linger
run tools/ghostlight_prepare_compaction.py again after edits and scratch cleanup
fix errors, address warnings, and commit the completed persistence pass unless the work is deliberately mid-surgery

Operating Discipline

Steward persistent state as part of the work. If a lesson changes future behavior, update the smallest correct memory surface before moving on; if a memory surface is stale, duplicated, or making re-entry slower, cut or consolidate it.
Before substantial edits, restate the current mechanism and intended change.
Prefer one clear hypothesis per iteration.
Verify with checks that reflect the real goal, not just proxy success.
Revert or discard changes that do not clearly improve the target.
If the diff grows while understanding shrinks, stop implementation and switch to diagnosis.
Keep maps and prose together; do not replace useful maps with prose-only explanations.
Commit completed work before it rots in the worktree unless the task is deliberately mid-surgery or the user asked to leave changes uncommitted.
Push after major completed passes when a remote exists, unless the user asked not to or there is a concrete reason to keep the commit local for a moment.
Before handoff, compaction, or phase boundaries, sync state/map.yaml, add distilled evidence when the lesson changes future belief, refresh notes/fresh-workspace-handoff.md, and make the next action explicit.
Treat state/map.yaml as a working memory map, not an archive. Preserve current mission, live seams, boundaries, and next action; let git history, evidence, and artifact files carry chronology.
In documentation, describe the live system and current rule directly. Do not write victory laps, scar tours, clever autopsies, or contrastive little boasts about what the project no longer does. If a sentence congratulates the design for not being a previous wrong design, cut it or rewrite it as a plain current rule. If rejected history matters, keep it short, explicit, and decision-relevant; otherwise cut it. The docs are not a trophy case for yesterday's wrong machine.

Aetheria Grounding Doctrine

Before writing or generating Aetheria scenes, check AetheriaLore for the factions, movements, institutions, species or body types, location, and time period involved.
Before drafting story prose, choose an intentional tonal mode or blend for the scene. Aetheria should support wit-with-stakes, warmth, absurdity, domestic texture, ritual quiet, wonder, horror, noir, dour poetry, and dry systems prose as needed. Do not default to constant crisis or procedural severity.
Use Adams/Pratchett-style comic precision and humane levity as a useful default touchstone when no stronger scene-specific style is called for: jokes and absurdity should reveal stakes, not dissolve them.
Establish ordinary life before interruption when the fixture calls for it: routines, work texture, relationships, private jokes, rituals, small desires, and local accommodations are part of worldbuilding, not filler.
For illustrated Ink fixtures, segment prose into click-through visual sections. Distinct places, focal areas, object closeups, arrivals, alarms, pivotal one-sentence beats, and aftermath states need stable visual scene ids and imagegen-ready prompts.
Treat visual artifacts as illustrated replay and website collateral, not core social-model training signal. Visual review judges the playable Ink experience plus the visual plan, not clean-run prose receipts.
Write visual prompts for a general image model, not a lore expert. Explain fictional objects and body affordances in visible terms: geometry, materials, lighting, stance, interfaces, tools, supports, cables, fluids, screens, and crowd positions.
Do the same for environments. A location label like "manifold line," "cavity yard," "supervisor glass," or "anchor rail" is not a drawable scene until the prompt describes its visible geometry, materials, interfaces, lights, and scale.
If a fixture has a target visual style, store that style cue once in the sidecar and include it in every assembled image prompt. Do not rely on memory or unstated website context to carry the look.
Do not treat a character name as a visual description. Illustrated fixtures need stable character visual refs for every recurring named character, and scene prompts should either include those refs during prompt assembly or carry enough appearance detail to stand alone.
Include visual character refs only for characters actually visible in the rendered frame. Do not feed imagegen refs for absent, off-frame, merely mentioned, or object-represented characters.
Treat visual continuity notes as tool/reviewer constraints, not prompt text. If imagegen needs the fact, rewrite it as concrete visible description in the base prompt, character ref, or branch/state modifier.
Treat generated environment images as concept and material reference, not spatial truth. Multi-angle or branch-consistent illustrated IF needs a durable scene-set source such as a hand-built blockout, procedural scene file, layout asset, or camera map. Imagegen can paint over camera-specific visual input; it should not be asked to preserve room topology from a prior generated image or text memory.
Ground scene writing in the source's material details: habitat form, infrastructure, law, class pressure, money, route access, surveillance, communication channels, body affordances, and local failure costs.
If the source is too vague for a concrete scene detail, do not bluff. Mark the lore gap, patch the AetheriaLore source with a narrow elaboration, then regenerate or revise the Ghostlight artifact from that patched source.
Treat this as part of data generation. Ghostlight is expected to stress-test Aetheria at room scale, find missing granularity, and push useful elaborations back into the lore vault.

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