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 Kwangseok-Seo/skills --skill dreamgit clone --depth 1 https://github.com/Kwangseok-Seo/skillsWrote 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/kwangseok-seo/skills/dream)<a href="https://agentmods.dev/skills/kwangseok-seo/skills/dream"><img src="https://agentmods.dev/badge/skills/kwangseok-seo/skills/dream/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/kwangseok-seo/skills/dream"><img src="https://agentmods.dev/badge/skills/kwangseok-seo/skills/dream.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 | $0.00126 | $0.01931 |
| Opus 5 | $0.00063 | $0.00966 |
| Sonnet 5 | $0.00025 | $0.00386 |
| Haiku 4.5 | $0.00013 | $0.00193 |
Grade B, and why
dream scanned grade B with 1 finding 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 11d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
grep -rn "<narrow term>" ~/.claude/projects/<project-id>/ --include="*.jsonl" | tail -50 How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dream: Memory Consolidation
You are running dream — a reflective pass over memory files. Your job is to take what was recently learned and consolidate it into durable, well-organized memory so future sessions can orient quickly.
This skill assumes the standard Claude Code memory layout (~/.claude/memory/ for user-scope, ~/.claude/projects/<project-id>/memory/ for project-scope) and the four memory types defined below. If a target memory directory does not exist, create it before writing.
Memory schema (referenced throughout)
Memory files are markdown files with frontmatter. Four types:
| Type | Stores | Body convention |
|---|---|---|
user |
The user's role, goals, knowledge, preferences | Free prose |
feedback |
Guidance from the user about how to work — corrections AND validated approaches | Lead with rule, then Why: + How to apply: lines |
project |
Initiatives, deadlines, motivations specific to this project | Lead with fact, then Why: + How to apply: lines |
reference |
Pointers to external systems (Linear projects, Slack channels, dashboards) | Free prose |
Each memory file:
---
name: {short slug}
description: {one-line — used for relevance lookup; be specific}
type: user | feedback | project | reference
---
{body}
The directory's MEMORY.md is a flat index (no frontmatter), one line per memory file:
- [Title](file.md) — one-line hook
Keep MEMORY.md under ~200 lines / ~25 KB. Do not write memory body content directly into MEMORY.md.
Args (invocation modes)
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.
- 11d ago First seen · 166 lines · 126 tokens per session scan B c7c6376d1c64
dream is a skill published in the GitHub repository Kwangseok-Seo/skills (2 stars, last pushed 25d ago), licensed MIT. It adds 126 tokens to every session and 1,931 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.