Borrowing it
Nothing to install: this file belongs to BlocUnited-LLC/mozaiks. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/BlocUnited-LLC/mozaiks/main/.agents/skills/add-feature/SKILL.mdgit clone --depth 1 https://github.com/BlocUnited-LLC/mozaiksWrote 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/blocunited-llc/mozaiks/add-feature)<a href="https://agentmods.dev/skills/blocunited-llc/mozaiks/add-feature"><img src="https://agentmods.dev/badge/skills/blocunited-llc/mozaiks/add-feature/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/blocunited-llc/mozaiks/add-feature"><img src="https://agentmods.dev/badge/skills/blocunited-llc/mozaiks/add-feature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 103 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00022 | $0.01174 |
| Opus 5 | $0.00011 | $0.00587 |
| Sonnet 5 | $0.00004 | $0.00235 |
| Haiku 4.5 | $0.00002 | $0.00117 |
Grade A, and why
add-feature 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 9d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before starting: git fetch origin && gh pr list --state open && git log origin/main --oneline -3 — if another agent has an open PR touching the same files you need, wait for it to merge or branch off it instead of main.
Help the user add features to an existing Mozaiks project.
Available Features
Mozaiks features are additive. You can enable them individually or upgrade to a higher tier preset.
Individual Features
| Feature | What It Enables | Requires |
|---|---|---|
| chat_ui | Frontend chat interface | - |
| modules | Deterministic CRUD/action modules and module routes | - |
| event_bus | Domain event bus for module↔workflow communication | - |
| auth | Provider-neutral OIDC/JWT validation and browser PKCE auth | OIDC provider or local mock |
| admin | Admin portal with observability, token tracking | auth |
Tier Presets
| Preset | Features Included |
|---|---|
| engine | ai_runtime |
| chat | ai_runtime, chat_ui |
| integrated | ai_runtime, chat_ui, modules, event_bus, auth |
| full | All features |
Commands
Enable Individual Feature
mozaiks add <feature>
Examples:
mozaiks add modules # Add deterministic module handling
mozaiks add event_bus # Add event-driven automation
mozaiks add auth # Add provider-neutral OIDC/JWT authentication
mozaiks add admin # Add admin portal
Upgrade to Higher Tier
mozaiks add --preset <tier>
Examples:
mozaiks add --preset chat # Upgrade to chat tier
mozaiks add --preset integrated # Upgrade to integrated tier
mozaiks add --preset full # Upgrade to full tier
What Happens
When you add a feature:
-
Updates app/app.json:
- Adds feature override OR upgrades preset
- Example:
{"features": {"modules": true}}
-
Shows next steps:
- What directories to create
- What config to update
- What services to start
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.
- 9d ago First seen · 163 lines · 22 tokens per session scan A 5db92f11630a
add-feature is a skill published in the GitHub repository BlocUnited-LLC/mozaiks (25 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 1,174 once invoked, about $0.0001 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
building-pydantic-ai-agents
Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydanticai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents…
migrating-langchain-to-pydantic-ai
Migrate Python LangChain or LangGraph applications to Pydantic AI. Use for LangChain agents, chains, LCEL, or direct LangGraph graphs, persistence, interrupts, and streaming. Do not use for migrations centered on createdeepagent or Deep Agents harness features.
agentfield-use
Whenever you have a discrete task to perform — one the user delegated, or one that arose inside your own work — check FIRST whether an installed AgentField agent covers it, and offload to it by default when one does. Coverage, not task size, is the test: even a small job goes to a covering agent. The check is cheap …
agentfield
Design and ship a multi-agent system on AgentField. Use when the user asks to build, scaffold, design, or run an agent, reasoner network, multi-agent backend, or 'an agent that does X' — whenever the work would otherwise be a single LLM call or a flat LangChain/CrewAI/AutoGen chain. The skill produces composite…
agentfield-personal
Build and install a personal AI agent on this machine's AgentField: real source in /agentfield-agents, packaged with agentfield-package.yaml, installed with af install, started with af run, registered on the local control plane, and visible in AgentField Desktop with a keys form and an auto-start toggle. Use when the…
hephaestus-network
Use when the user types $hephaestus-network, /hep-network, or /agentlas-network, mentions @Hephaestus, or asks Agentlas to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM staffs each turn; the exact roster remains goal-bound until explicit completion.