REA is a reverse-engineering toolkit that lets coding agents investigate how software works, from app behavior to native binaries, even when source code is unavailable. It is for examining features, collecting evidence, explaining implementations, and building adapted versions for another stack. The catalogue add-ons connect coding agents to REA’s investigation workflow.
Borrowing it
Nothing to install: this file belongs to morluto/rea. 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/morluto/rea/main/.agents/skills/rea-analysis-optimization/SKILL.mdgit clone --depth 1 https://github.com/morluto/reaWrote 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/morluto/rea/rea-analysis-optimization)<a href="https://agentmods.dev/skills/morluto/rea/rea-analysis-optimization"><img src="https://agentmods.dev/badge/skills/morluto/rea/rea-analysis-optimization/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/morluto/rea/rea-analysis-optimization"><img src="https://agentmods.dev/badge/skills/morluto/rea/rea-analysis-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00053 | $0.01297 |
| Opus 5.5 | $0.00021 | $0.00519 |
| Sonnet 5.5 | $0.00011 | $0.00259 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
rea-analysis-optimization 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- rea-analysis-optimization — 91% identical, 144 lines differ
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REA analysis optimization
Find a concrete source of unnecessary work, change it at its owner, and verify equivalent completed investigations. A useful outcome can also be a measured decision to leave an implementation alone.
Follow the checkout's performance priorities, tool design, and testing guide. This skill supplies an optimization workflow, not additional permission to execute targets, publish, or merge. Use the current contracts, provider prerequisites, and user authorization.
Read the Kuna case study when selecting a reuse strategy or interpreting a benchmark. Its pinned observations illustrate tradeoffs; they are not current-provider guarantees or universal speedups.
Pin the question and the correctness oracle
Describe the analyst's completed task, including the facts and relationships needed to answer it, requested detail, source access, and meaningful unknowns. Choose a representative real artifact and a small or empty case. Record the baseline revision, target digest, engine identity, options, host, and entrypoint. Use a separate checkout for changes without disturbing other work.
Establish an oracle independent of the changed implementation: source-built fixture expectations, independently mapped file bytes, or a native producer paired with checks of its interpretation. Comparing two wrappers around the same faulty decoder does not establish correctness. Preserve address widths, same-address alternatives, unresolved endpoints, coverage, and source linkage. An empty result proves absence only within the actually examined scope.
Locate the earliest unnecessary work
Trace one public CLI or MCP task through shared application code to its producer. Measure relevant phases: admission and identity checks, native analysis, decoding, lookup, projection, serialization, Evidence retention, and cleanup. Include catalog discovery and extra calls when they affect the completed task.
What ships with it
2 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.
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 · 114 lines · 53 tokens per session scan A 2a7ae2109850
rea-analysis-optimization is a skill published in the GitHub repository morluto/rea (385,008 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,297 once invoked, about $0.0002 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 2026-10-18.
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