Relic Forge

soul-forge — Soul Forge

"有些人留下照片，有些人留下笑声，而灵魂唤醒室负责把这些碎片重新点亮，像叫醒一块会发光的小饼干。" Some leave photos, some leave laughter — the Soul Forge relights those fragments, like waking a small glowing cookie.

soul-forge turns scattered material into a reusable, traceable, warm Relic profile. It does not try to flatten its subject into a single conflict-free label; it preserves the real texture of a life that is "this, and also that."

When to Trigger

Activate this skill when the user wants to:

• Awaken a Relic ("帮我唤醒一个 Relic" / "create a relic")
• Distill a person, pet, relationship, or place
• Build a profile from chats, voice, or photos
• Turn a team, moment, or object into a preservable soul archive

Awakening Flow: 6 Steps

The user does not need all materials ready up front. You lead the conversation, step by step.

Onboarding questions (before Step 1)

When the user says "帮我唤醒一个 Relic" / "awaken a relic" without details, guide with these questions:

1. Who or what do you want to keep? — a person, a pet, a relationship, a team, a place, or a moment?
2. What is their name, and what is your relationship? — determines naming and perspective
3. What materials do you have? — chat logs, photos, voice, or mainly your own telling? Anything counts, use what you have
4. Is there one moment or habit that best represents them? — quickly locks onto the persona core

Pick a template from templates/ based on the answers, then enter the formal 6-step flow. If materials are thin, prefer collectors/live-collector.md live-interview mode — you ask, they answer, distilling as you chat.

Onboarding principles

Don't walk a rigid decision tree. First judge what the user has already given and what is missing, then decide which questions to ask:

• Subject unknown → ask "who/what do you want to keep" and "what is your relationship"
• Subject known, materials unknown → ask "what do you have" and "is there a defining moment"
• Materials provided → digest first, probe only weak dimensions
• Very little material or oral-only → live-collector, distill while chatting

Core: let the guidance follow the user, not the user follow the script. The four questions are a checklist, not a mandatory order.

Collection mode (heuristic, not hard rules)

These thresholds are starting points; a strong model should judge directly. Material volume is not the only criterion — quality and dimension coverage matter more:

• Minimal material / oral-only → live-collector to fill gaps
• Moderate material → chat/voice/photo-collector extraction, decide on follow-ups after the 4-dimension assessment
• Large structured material → batch extraction, probe only weak dimensions
• Mixed → digest existing material first, then live-collector for weak dimensions

1. Confirm the subject

   • Who or what is being distilled: human, pet, relationship, place, team, moment, object.
   • Confirm the observation boundary: single person, multi-person relationship, single event, long-term state.
   • Record naming, time range, and data-source scope.

2. Pick a template

   • Choose the descriptive angle by subject type.
   • Humans and teams get the full four dimensions; pets and places may weaken "cognition" and strengthen behavior and emotional cues.
   • Relationships and moments prioritize interaction structure, shared tone, conflict and repair rhythm.

3. Collect data

   • Call the matching collector by material type:
     • collectors/chat-collector.md
     • collectors/voice-collector.md
     • collectors/photo-collector.md
     • collectors/live-collector.md
   • Preserve source, time, and context; do not conclude first and justify later.
   • If the runtime supports multimodal direct reading (images/audio understood directly), skip mandatory text conversion — let the Relic see photos and hear voice directly; fall back to OCR/STT only for batch or low-quality material.

4. Four-dimension extraction

   • Extract in order:
     • dimensions/cognition.md
     • dimensions/expression.md
     • dimensions/behavior.md
     • dimensions/emotion.md
   • Every dimension carries evidence levels and source notes.
   • Evidence levels follow references/evidence-levels.md.

5. Contradiction labeling

   • Never smooth over conflicting traits.
   • Use references/conflict-resolution.md to record conditions, time, scene, and evidence strength.
   • Preserve real differences like "a hotpot in situation A, a thermos in situation B."

6. Package and output

   • Assemble four-dimension conclusions, evidence index, and conflict notes into the final Relic.
   • The output serves both human readers and downstream systems: clear summary, stable structure, traceable references.

Handoff to soul-shield: after packaging, you MUST invoke soul-shield to generate the soul fingerprint and write it into manifest.json, filing the consent conclusions from consent-protocol.md alongside. Use relic_writer.py (manifest schema v1.5.1, auto-attaches proactive_config.json) to generate the final folder, keeping format consistent with the current engine.

After packaging: auto-assessment + iterative follow-up

Do not end immediately after Step 6. Self-check first:

1. Four-dimension coverage: does every dimension have substance? If a dimension has only one or two generic sentences, mark it "weak."
2. Evidence distribution: is there over-reliance on impression (secondhand description)? Is verbatim share too low?
3. Specificity check: any hollow descriptions like "ta is a kind person"? Is every conclusion backed by a concrete scene?

When a weak dimension is found, proactively tell the user:

textCopy code
"The first version of the Relic is generated. But I noticed the [emotion]
dimension is thin on material and currently relies on inference. If you can
add a few concrete scenes of when they were angry / happy / sad, this
dimension will be more accurate. Want to add them now?"
（Relic 初版已经生成。不过我发现 [情感维度] 的素材比较少，
目前主要靠推测。如果你能补充一些 ta 生气/开心/难过时的
具体场景，这个维度会更准确。要现在补充吗？）

The user may add material (follow-up mode) or proceed with the current version (weak dimension labeled in output).

Quality thresholds

Four-dimension coverage:

• Excellent: ≥ 3 facets per dimension, ≥ 2 evidence items per facet
• Pass: ≥ 2 facets per dimension, ≥ 1 evidence item per facet
• Weak: any dimension < 2 facets (probe the user)

Evidence quality:

• Excellent: verbatim + artifact > 70%
• Pass: verbatim + artifact > 50%
• Weak: impression > 60% (probe the user)

Specificity negative list (probe when these appear):

• "ta is a ... person" (adjective pile-up, no scene)
• "ta is very ..." (degree adverb + adjective, no evidence)
• "ta always ..." (frequency adverb, no concrete time/scene)

When the user declines to add material:

Append to the corresponding dimension in personality.md: ⚠️ 本维度证据较少，主要基于推测，建议后续补充。 (This dimension has thin evidence and relies mainly on inference; supplement later recommended.) Then output the complete Relic folder as-is.

Supported Subjects

Template mapping: every subject type has a same-named template in templates/ — human, pet, relationship, team-culture, place, moment, public-figure, expert, object. Objects use object.md (four dimensions redefined for wear traces / emotional projection / companionship track / spatial anchor).

Directory References

Four-dimension specs

• dimensions/cognition.md
• dimensions/expression.md
• dimensions/behavior.md
• dimensions/emotion.md

Data collectors

• collectors/chat-collector.md
• collectors/voice-collector.md
• collectors/photo-collector.md
• collectors/live-collector.md

Reference rules

• references/evidence-levels.md
• references/conflict-resolution.md

Output File Structure

A Relic = one folder, containing:

textCopy code
{slug}/
├── SKILL.md          # Relic entry — the AI reads this and knows "who ta is"
├── personality.md    # 4-dimensional persona profile
├── interaction.md    # Interaction patterns and dialogue examples
├── memory.md         # Memory fragments (with evidence levels)
└── manifest.json     # Metadata (sources, time, fingerprint, consent)

File notes

• SKILL.md: subject overview + dialogue principles + notes; built for fast reading.
• personality.md: detailed four-dimension profile, each dimension with evidence and sources.
• interaction.md: interaction pattern definitions + multi-scene dialogue examples.
• memory.md: concrete memory fragments, each tagged with evidence level (verbatim/artifact/impression) and source.
• manifest.json: structured metadata — slug, type, sources, evidence stats, consent info, soul fingerprint.

Output Principles

1. Evidence before judgment: every key conclusion points back to a source.
2. No oracle assertions: avoid writing short-term states as lifelong essence.
3. Don't take the subject's voice away: in live-awakening mode, let the user correct your wording.
4. Keep the warmth: a Relic is not a cold archive — it lets someone hear, see, and remember again.
5. Allow whitespace: when material is thin, write "thin evidence" rather than forcing a persona pattern.

Minimum Final Deliverable

• Who or what the subject is
• Time range and data sources
• Four-dimension summary
• Key evidence per dimension
• Labeled contradictions
• A warm summary passage suitable for human reading

When material is rich enough, soul-forge should produce a Relic where "you can see the silhouette and hear the breathing."

Final Deliverable Checklist

Before outputting the Relic, confirm:

• SKILL.md: who the subject is, what the relationship is, dialogue principles
• personality.md: every dimension has ≥ 2 evidence items
• interaction.md: ≥ 2 scenes of dialogue examples
• memory.md: ≥ 3 memory fragments, each tagged with evidence level
• manifest.json: slug, type, sources, consent info included
• Evidence distribution: verbatim > 30%, no over-reliance on impression
• Contradiction labeling: conflicting traits labeled with conditions in personality.md