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explore-code

explore-code is a skill for Codex from lllllllama/RigorPilot-Skills. It costs 112 tokens per session (525 once invoked), scanned A, original, MIT.

A controlled coding task for exploratory changes in deep-learning research repositories, which contain model and training code. It is intended for candidate implementations kept separate from the trusted baseline.

In plain words
What is it for?
Use it when a researcher has explicitly approved isolated experimental code changes, such as combining modules or testing a model adaptation.
Why use it?
It provides a bounded way to test ideas such as moving a module, adapting a model backbone, adding LoRA or adapter layers, or replacing a model head without treating the result as verified research code.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 484repo +2 changed 1mo ago A scan Socket: passSnyk: passSkillSpector: pass 112 tokens original MIT

Good fit Use it when a researcher has explicitly approved isolated experimental code changes, such as combining modules or testing a model adaptation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lllllllama/rigorpilot-skills/explore-code
View source ↗ lllllllama/RigorPilot-Skills
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.

Any agent
npx skills add lllllllama/RigorPilot-Skills --skill explore-code
Clone the repo
git clone --depth 1 https://github.com/lllllllama/RigorPilot-Skills

Made for: 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 explore-code

README.md
[![agentmods](https://agentmods.dev/badge/skills/lllllllama/rigorpilot-skills/explore-code/github.svg)](https://agentmods.dev/skills/lllllllama/rigorpilot-skills/explore-code)
Your own site
<a href="https://agentmods.dev/skills/lllllllama/rigorpilot-skills/explore-code"><img src="https://agentmods.dev/badge/skills/lllllllama/rigorpilot-skills/explore-code/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.

agentmods 80×15 button for explore-code

Your own site · 80×15
<a href="https://agentmods.dev/skills/lllllllama/rigorpilot-skills/explore-code"><img src="https://agentmods.dev/badge/skills/lllllllama/rigorpilot-skills/explore-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 525 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 14 Sept 2026
  • Snyk pass 14 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00112 $0.00525
Opus 5.5 $0.00045 $0.00210
Sonnet 5.5 $0.00022 $0.00105
Haiku 4.5 $0.00011 $0.00052

Measured 1mo ago against content hash aab7d2f9c831, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

explore-code 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 1mo ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/plan_code_changes.py, scripts/write_outputs.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/explore-code/SKILL.md · 49 lines

What it actually says

explore-code

Use this as the Rigor Improve implementation leaf skill. The installed slug remains explore-code for compatibility.

Use the shared operating principles in ../ai-research-reproduction/references/agent-operating-principles.md; this skill should guide bounded candidate code work without over-prescribing implementation details.

When to apply

  • When the researcher explicitly authorizes exploratory code changes on an isolated branch or worktree.
  • When the task is source-anchored module transplant, backbone adaptation, LoRA or adapter insertion, or low-risk module combination.
  • When summary-level recording is sufficient and the result is a candidate, not a trusted conclusion.

When not to apply

  • When the request is for trusted baseline work, conservative debugging, or normal training execution.
  • When the user did not explicitly authorize exploratory modifications.
  • When the task is a broad refactor or a from-scratch idea implementation.

Clear boundaries

  • This skill owns exploratory code modifications only.
  • It must keep work isolated from the trusted baseline.
  • Use ai-research-explore instead when the task spans both current_research coordination and exploratory runs.
  • It may hand off execution to minimal-run-and-audit or run-train.
  • It should favor source-anchored copying and minimal adaptation over freeform rewrites.
  • It should record why a candidate change is meaningful, how to roll it back, and why it remains a candidate rather than a verified contribution.

Output expectations

  • explore_outputs/CHANGESET.md
  • explore_outputs/SCIENTIFIC_CHANGELOG.md
  • explore_outputs/COMPARABILITY_REPORT.md
  • explore_outputs/TOP_RUNS.md
  • explore_outputs/status.json

Notes

Use references/explore-policy.md, ../ai-research-reproduction/references/research-rigor-principles.md, scripts/plan_code_changes.py, and scripts/write_outputs.py.

Files

What ships with it

4 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.

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. 1mo ago Changed aab7d2f9c831
  2. 1mo ago First seen · 49 lines · 112 tokens per session scan A aad15b9878fe

Subscribe to this mod's changes

explore-code is a skill published in the GitHub repository lllllllama/RigorPilot-Skills (484 stars, last pushed 1mo ago), licensed MIT. It adds 112 tokens to every session and 525 once invoked, about $0.0004 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 2026-08-30.

Languagesagent-skillsai-agentsdeep-learningreproducibilityresearch-tools
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