Borrowing it
Nothing to install: this file belongs to cq27-dev/rag-rat. 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/cq27-dev/rag-rat/main/.agents/skills/dream-review/SKILL.mdgit clone --depth 1 https://github.com/cq27-dev/rag-ratWrote 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/cq27-dev/rag-rat/dream-review)<a href="https://agentmods.dev/skills/cq27-dev/rag-rat/dream-review"><img src="https://agentmods.dev/badge/skills/cq27-dev/rag-rat/dream-review.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00101 | $0.01941 |
| Opus 5 | $0.00051 | $0.00971 |
| Sonnet 5 | $0.00020 | $0.00388 |
| Haiku 4.5 | $0.00010 | $0.00194 |
Grade A, and why
dream-review 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 8d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dream-review — triage and resolve the rag-rat dream worklist
The dream tool surfaces findings about the repo's memories and load-bearing code. It never
mutates a memory — the deterministic passes and the optional model propose; a reviewer
decides. This skill is that reviewer loop: for each open finding, investigate with the rag-rat
MCP tools, then resolve it — preferring a root fix (repair the memory / close the coverage gap,
so the finding resolves on its own next run) over a bare verdict.
Drive the whole loop through the rag-rat MCP tools — dream and dream_review for the worklist,
and semantic_search / symbol_lookup / impact_surface / find_callers / git_history_for_symbol
/ memory_search / read_chunk to investigate — not grep, and not the rag-rat CLI (an agent has
the MCP but may not have the binary on PATH). It is a batch chore meant to run a few times a day, not
continuously.
1. Preflight
- Confirm the index is fresh: call
index_status. If it reports drift, callheal_indexto repair already-indexed files. (Discovering brand-new files and re-embedding is a CLI/cron job —rag-rat index --discoverthenrag-rat reconcile— outside this MCP loop; if findings look empty, that's the thing to ask a human to run.) - The
dreamtool is deterministic-only. It recomputescoverage_gap+stale_referenceon every call and surfaces anymemory_divergence/memory_unverifiablefindings a prior model run persisted — but it does not run the model itself. Generating fresh model findings is the CLI/cronrag-rat dream --verify --compactpass (it provisions a GPU and takes minutes, so it never runs from a tool call). If the divergence findings look stale, that CLI pass is what refreshes them.
2. Pull the open worklist
Call dream — no args needed (limit caps the number of coverage_gap findings, default 20).
It returns findings[], each { id, kind, subject, evidence, rank, status }. Work highest rank
first (rank decays with age). The id (a short hex; a unique prefix also works) is what you pass
to dream_review.
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.
- 8d ago First seen · 127 lines · 101 tokens per session scan A 1e53ebea18aa
dream-review is a skill published in the GitHub repository cq27-dev/rag-rat (20 stars, last pushed 2d ago), licensed MIT. It adds 101 tokens to every session and 1,941 once invoked, about $0.0005 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.
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Use when an agent needs to read, search, create, edit, organize, upload, or chat with Anytype through the bounded any-mcp server. Covers safe tool selection, exact identifier chaining, optional toolsets, common PKM workflows, and the narrow anyr fallbacks for chat subscriptions and rich chat blocks.