ylsssq926/relic.skill/soul-forge
Claude Code and agent skill by ylsssq926/relic.skill
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Checking that the SKILL.md file is still in the repository.
Soul Forge — Distill memories, chat logs, voice, and photos into a 4-dimensional digital soul / persona. Trigger on /relic-forge, or when user wants to distill, awaken, or build a Relic ("distill a relic", "create digital persona", "帮我唤醒/蒸馏Relic", "制作数字分身").
Install
npx vskill@latest install ylsssq926/relic.skill/soul-forgeSKILL.md
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:
- Who or what do you want to keep? — a person, a pet, a relationship, a team, a place, or a moment?
- What is their name, and what is your relationship? — determines naming and perspective
- What materials do you have? — chat logs, photos, voice, or mainly your own telling? Anything counts, use what you have
- 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
- 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.
- 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.
- Collect data
- Call the matching collector by material type:
collectors/chat-collector.mdcollectors/voice-collector.mdcollectors/photo-collector.mdcollectors/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.
- Four-dimension extraction
- Extract in order:
dimensions/cognition.mddimensions/expression.mddimensions/behavior.mddimensions/emotion.md- Every dimension carries evidence levels and source notes.
- Evidence levels follow
references/evidence-levels.md.
- Contradiction labeling
- Never smooth over conflicting traits.
- Use
references/conflict-resolution.mdto record conditions, time, scene, and evidence strength. - Preserve real differences like "a hotpot in situation A, a thermos in situation B."
- 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 invokesoul-shieldto generate the soul fingerprint and write it intomanifest.json, filing the consent conclusions fromconsent-protocol.mdalongside. Userelic_writer.py(manifest schema v1.5.1, auto-attachesproactive_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:
- Four-dimension coverage: does every dimension have substance? If a dimension has only one or two generic sentences, mark it "weak."
- Evidence distribution: is there over-reliance on impression (secondhand description)? Is verbatim share too low?
- 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:
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
| Subject | Typical | Suggested Focus | Common Sources | |
|---|---|---|---|---|
| Human | family, friends, partner, colleague, creator | full four dimensions | chats, voice, photos, live conversation | |
| Pet | cat, dog, parrot, turtle | behavior patterns, emotional bond, expression habits | photos, video descriptions, diary, voice | |
| Relationship | parent-child, partners, duo, mentor-student | interaction rhythm, conflict repair, shared language | both sides' chats, shared photos, interviews | |
| Place | hometown, café, office, neighborhood | atmosphere, memory triggers, action habits | photos, location records, oral recollection | |
| Team | startup, band, class, project group | decision mechanism, collaborative tone, collective emotion | meeting notes, group chats, documents | |
| Moment | wedding, graduation, moving night, farewell | emotional peak, key expressions, on-scene behavior | photos, videos, same-day chats | |
| Object | old camera, kitchen table, travel backpack | wear traces, emotional projection, companionship track | photos, purchase records, narration |
Template mapping: every subject type has a same-named template intemplates/—human,pet,relationship,team-culture,place,moment,public-figure,expert,object. Objects useobject.md(four dimensions redefined for wear traces / emotional projection / companionship track / spatial anchor).
Directory References
Four-dimension specs
dimensions/cognition.mddimensions/expression.mddimensions/behavior.mddimensions/emotion.md
Data collectors
collectors/chat-collector.mdcollectors/voice-collector.mdcollectors/photo-collector.mdcollectors/live-collector.md
Reference rules
references/evidence-levels.mdreferences/conflict-resolution.md
Output File Structure
A Relic = one folder, containing:
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
- Evidence before judgment: every key conclusion points back to a source.
- No oracle assertions: avoid writing short-term states as lifelong essence.
- Don't take the subject's voice away: in live-awakening mode, let the user correct your wording.
- Keep the warmth: a Relic is not a cold archive — it lets someone hear, see, and remember again.
- 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
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingsoul-forge/SKILL.md
Popularity
- Repository stars
- 72
- Repository forks
- 4
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 16 Jun 2026, 4 months ago.
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