experiment_loop_resume

experiment_loop_resume is a skill for Claude Code from AnirudhaRamesh/experiment-automation-claude-code-plugin. It costs 16 tokens per session (599 once invoked), scanned B, original, no licence file.

A control for continuing an experiment loop that stopped or failed. An experiment loop is a repeated automated run used to test or improve something.

In plain words
What is it for?
It is for resuming an interrupted experiment loop from its previous point.
Why use it?
It avoids having to restart a stopped or failed experiment from the beginning.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: model in frontmatter.

Part of the aichor-experiment-automation plugin — 9 skills, 6 agents shipped together

Good fit It is for resuming an interrupted experiment loop from its previous point.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume
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 AnirudhaRamesh/experiment-automation-claude-code-plugin --skill experiment-loop-resume
Clone the repo
git clone --depth 1 https://github.com/AnirudhaRamesh/experiment-automation-claude-code-plugin

Made for: Claude Code.

Or install aichor-experiment-automation, the plugin that ships this one along with the rest of its 9 skills, 6 agents.

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 experiment_loop_resume

README.md
[![agentmods](https://agentmods.dev/badge/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume/github.svg)](https://agentmods.dev/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume)
Your own site
<a href="https://agentmods.dev/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume"><img src="https://agentmods.dev/badge/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume/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 experiment_loop_resume

Your own site · 80×15
<a href="https://agentmods.dev/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume"><img src="https://agentmods.dev/badge/skills/anirudharamesh/experiment-automation-claude-code-plugin/experiment-loop-resume.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 599 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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 $0.00016 $0.00599
Opus 5 $0.00008 $0.00300
Sonnet 5 $0.00003 $0.00120
Haiku 4.5 $0.00002 $0.00060

Measured 9d ago against content hash 5ce47d263b32, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade B, and why

experiment_loop_resume 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 9d 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.

2. Monitor with: `tail -f .claude/loop-state/<loop-id>/progress.log`
skills/experiment-loop-resume/SKILL.md · 69 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 9d ago First seen · 69 lines · 16 tokens per session scan B 5ce47d263b32

Subscribe to this mod's changes

experiment_loop_resume is a skill published in the GitHub repository AnirudhaRamesh/experiment-automation-claude-code-plugin (4 stars, last pushed 6mo ago), with no licence file. It adds 16 tokens to every session and 599 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens