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 agentmods add skills/epicsagas/velith/loomnpx skills add epicsagas/Velith --skill loomgit clone --depth 1 https://github.com/epicsagas/VelithWrote 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/epicsagas/velith/loom)<a href="https://agentmods.dev/skills/epicsagas/velith/loom"><img src="https://agentmods.dev/badge/skills/epicsagas/velith/loom.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.01963 |
| Opus 5 | $0.00018 | $0.00981 |
| Sonnet 5 | $0.00007 | $0.00393 |
| Haiku 4.5 | $0.00004 | $0.00196 |
Grade A, and why
loom 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 4d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Velith — AI-Native Publishing System
Overview
Build books like software. 6-phase pipeline from blank page to published book, with dedicated skills, agents, and quality gates at every stage.
Phase 0: Onboarding → Phase 1: Ideation → Phase 2: Outlining → Phase 3: Drafting → Phase 4: Editing → Phase 5: Publishing
Genre Support
| Genre | Key Differences | Reference File |
|---|---|---|
| Fiction | Plot structure (Save the Cat!/Snowflake), character bible, scene beats | book-fiction |
| Non-Fiction | Problem-solution structure, persona-driven, evidence hierarchy | book-nonfiction |
| Technical | Concept progression (novice→expert), code examples, diagrams, API docs | book-technical |
| Screenplay | 3-act + sequence method, dialogue/action, A/B story | book-screenplay |
| Poetry | Form-driven (sonnet/haiku/free verse), imagery systems, collection arc | book-poetry |
| Game | Quest trees, branching dialogue, lore bible, flag system | book-game |
| Academic | IMRAD, literature review, argument chains, citation practices | book-academic |
| Custom | Compose patterns from any genre via book-genre-creator |
book-genre-creator |
Phase Router
When /velith is invoked without arguments, detect current project state and route:
- No project exists → Run Phase 0 (Onboarding)
- Project exists, no outline → Run Phase 1 (Ideation)
- Outline exists, no drafts → Run Phase 2 (Outlining) validation, then Phase 3
- Drafts exist, incomplete → Continue Phase 3 (Drafting)
- All drafts complete → Run Phase 4 (Editing)
- Editing complete → Run Phase 5 (Publishing)
Detection: check for drafts/ directory, outline.md, STYLE.md, PRD.md in current project.
Phase Details
Phase 0: Onboarding (/velith onboard)
- Genre selection (fiction/non-fiction/technical/screenplay/poetry/game/academic/custom)
- Target audience definition
- Language selection
- Project directory setup
- Source material scan (existing notes, articles, code)
- Generate
STYLE.md(voice, tone, conventions) - Generate
PRD.md(book requirements)
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.
- 4d ago First seen · 175 lines · 36 tokens per session scan A 28b727c21835
loom is a skill published in the GitHub repository epicsagas/Velith (33 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 1,963 once invoked, about $0.0002 per session on Opus 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
agent-session-monitor
Real-time agent conversation monitoring - monitors Higress access logs, aggregates conversations by session, tracks token usage. Supports web interface for viewing complete conversation history and costs. Use when users ask about current session token consumption, conversation history, or cost statistics.
higress-daily-report
生成 Higress 项目每日报告,追踪 issue/PR 动态,沉淀问题处理经验,驱动社区问题闭环。用于生成日报、跟进 issue、记录解决方案。.
issue-spec-workflow
Use issue-spec to plan and implement a change through exact-head human review handoff.
open-ontologies
AI-native ontology engineering using 50+ MCP tools backed by an in-memory Oxigraph triple store. Build, validate, query, and govern RDF/OWL ontologies with a generate-validate-iterate loop. Use when building ontologies, knowledge graphs, RDF data, SPARQL queries, BORO/4D modeling, SHACL validation, clinical…
shadcn-ui
Provides complete shadcn/ui component library patterns including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building forms with React Hook Form and Zod, customizing themes with Tailwind CSS, or implementing UI patterns like…
debug-trt-mismatch
Use when TensorRT output diverges from a model reference, model-first validation fails, generated text or media is wrong, or a family change introduces a numerical mismatch. Routes the investigation by model modality and escalates from the first divergent boundary to the smallest responsible family-owned operation.