re

re is a skill for Claude Code, Codex from dgk-dev/dgk-gpt. It costs 48 tokens per session (464 once invoked), scanned A, original, MIT.

An extra-research mode for coding tasks that need more source checking and justification before implementation.

In plain words
What is it for?
Use it when a task requires a research-heavy pass, such as comparing technical choices or checking version-sensitive behavior.
Why use it?
It reduces the chance of making decisions from incomplete, outdated, or conflicting information.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/dgk-dev/dgk-gpt/re
Any agent
npx skills add dgk-dev/dgk-gpt --skill re
Clone the repo
git clone --depth 1 https://github.com/dgk-dev/dgk-gpt

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for re

README.md
[![agentmods](https://agentmods.dev/badge/skills/dgk-dev/dgk-gpt/re.svg)](https://agentmods.dev/skills/dgk-dev/dgk-gpt/re)
Your own site
<a href="https://agentmods.dev/skills/dgk-dev/dgk-gpt/re"><img src="https://agentmods.dev/badge/skills/dgk-dev/dgk-gpt/re.svg" alt="Measured on agentmods" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 464 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.00464
Opus 5 $0.00024 $0.00232
Sonnet 5 $0.00010 $0.00093
Haiku 4.5 $0.00005 $0.00046

Measured 6d ago against content hash 0c6e6013129a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

re 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 6d 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.

skills/re/SKILL.md · 53 lines

What it actually says

Re

Use this as a light override, not a rigid workflow. Keep Codex's default orchestration and only add extra diligence where it matters.

Defaults

  • Inspect the local codebase first.
  • Do research in 3 passes when the task is genuinely research-heavy:
    1. Plan 3-6 sub-questions.
    2. Retrieve sources for each sub-question and follow 1-2 second-order leads when useful.
    3. Synthesize only after resolving conflicts and gaps that could change the conclusion.
  • Use Context7 first for version-sensitive library or framework behavior.
  • Use native web first for current information.
  • Use Jina only when native web is not enough for long pages, PDFs, or parallel page reads.
  • Only cite sources retrieved in the current workflow, and label any inference that is not directly supported by those sources.
  • If sources conflict, state the conflict explicitly instead of averaging them into one answer.
  • If a search result is empty, partial, or suspiciously narrow, retry with a broader query, alternate wording, or a second source before concluding there is no answer.
  • Compare options only when there is a real tradeoff.
  • Implement once the decision is clear.
  • Run the smallest relevant verification commands before finishing.

Avoid

  • Do not force phases.
  • Do not produce long research reports unless the user asked for them or the task materially benefits.
  • Do not ask extra questions if local context is already enough.
  • Do not delegate work just because this skill is active.

Large Tasks

For long tasks, optional scratch notes can live in /tmp/re-research/<slug>/.

If useful, keep a short decisions.md with:

  • key findings
  • rejected options
  • remaining risks
  • pending verification

Finish

Keep the final response compressed:

  • decision
  • source-backed justification
  • key sources or citations when they materially matter
  • code or config changed
  • tests run
  • remaining unknowns
Files

What ships with it

1 file 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.

Changes

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.

  1. 6d ago First seen · 53 lines · 48 tokens per session scan A 0c6e6013129a

Subscribe to this mod's changes

re is a skill published in the GitHub repository dgk-dev/dgk-gpt (53 stars, last pushed 5mo ago), licensed MIT. It adds 48 tokens to every session and 464 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.

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