Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Ylsssq926/relic.skill --skill soul-forgegit clone --depth 1 https://github.com/Ylsssq926/relic.skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ylsssq926/relic.skill/soul-forge)<a href="https://agentmods.dev/skills/ylsssq926/relic.skill/soul-forge"><img src="https://agentmods.dev/badge/skills/ylsssq926/relic.skill/soul-forge/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ylsssq926/relic.skill/soul-forge"><img src="https://agentmods.dev/badge/skills/ylsssq926/relic.skill/soul-forge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.02790 |
| Opus 5.5 | $0.00033 | $0.01116 |
| Sonnet 5.5 | $0.00017 | $0.00558 |
| Haiku 4.5 | $0.00008 | $0.00279 |
Grade A, and why
relic-forge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- collectors/chat-collector.md 6.1 KB
- collectors/live-collector.md 4.7 KB
- collectors/photo-collector.md 6.0 KB
- collectors/voice-collector.md 4.8 KB
- dimensions/behavior.md 8.1 KB
- dimensions/cognition.md 8.0 KB
- dimensions/emotion.md 9.0 KB
- dimensions/expression.md 8.8 KB
- references/conflict-resolution.md 5.0 KB
- references/evidence-levels.md 3.8 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed cbdd986788da
- 16d ago Changed 5829f3df483e
- 17d ago Changed · +8 lines · +1 tokens per session 5b8ff4b1a346
- 1mo ago Changed · +6 lines 165151340891
- 2mo ago First seen · 223 lines · 82 tokens per session scan A e183e3675854
relic-forge is a skill published in the GitHub repository Ylsssq926/relic.skill (73 stars, last pushed 8d ago), licensed MIT. It adds 83 tokens to every session and 2,790 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
rag-evaluator
Generates tailored giskard.checks evaluation suites for RAG (Retrieval-Augmented Generation) systems. Use whenever a user describes a Q&A bot grounded in documents, a knowledge-base chatbot, a retrieval system, or wants to evaluate answer groundedness, faithfulness, hallucination, retrieval quality, citation accuracy…
scenario-generator
Generates tailored giskard.checks test scenarios and suites for AI agents. Use when user describes their agent and fears, asks to "create scenarios", "test my agent", "generate checks", "evaluate my chatbot", "red-team my AI", or wants to build adversarial test cases for LLM-based applications.
hub-agent-setup
Connect a local or remote AI agent to Giskard Hub through an authenticated, non-streaming HTTPS endpoint. Use when a user asks to connect, integrate, or register their agent with the Hub, including triggered (cron, webhook, event) agents. Build a minimal wrapper, deploy or tunnel it, and use the Hub connection test…
third-party-to-giskard
Convert existing result files from third-party LLM red-teaming and evaluation tools (garak, promptfoo, DeepTeam, PyRIT) into Giskard OSS SuiteResults, one suite per tool, and optionally upload them to Giskard Hub as evaluations. Use this whenever the user has a garak report.jsonl, a promptfoo eval or redteam output, a…
immortal-skill
A framework for building a digital version of a person from conversations, social-media material, and documents. It extracts working methods, interaction patterns, memories, and personality into a reusable agent skill, with templates for different relationships.
distill-shield
A tool for adding traceable markers and optional hardening steps to data packages before handing them to someone else. It is intended for data you own or are authorised to handle.