agentgym-run

agentgym-run is a skill for Claude Code from POWERFULMOVES/PMOVES.AI. It costs 130 tokens per session (1,169 once invoked), scanned A, original, no licence file.

A launcher for an AgentGym reinforcement-learning training session on a configured machine. Reinforcement learning trains an agent through repeated attempts in environments such as BabyAI, TextCraft, Maze, and Wordle.

In plain words
What is it for?
Use it to run AgentGym training with the specified Qwen model and publish completed episode results through NATS.
Why use it?
It removes the need to assemble the provided runner configuration and start the training session manually.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to run AgentGym training with the specified Qwen model and publish completed episode results through NATS.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/powerfulmoves/pmoves.ai/agentgym-run
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 POWERFULMOVES/PMOVES.AI --skill agentgym-run
Clone the repo
git clone --depth 1 https://github.com/POWERFULMOVES/PMOVES.AI

Made for: Claude Code.

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 agentgym-run

README.md
[![agentmods](https://agentmods.dev/badge/skills/powerfulmoves/pmoves.ai/agentgym-run.svg)](https://agentmods.dev/skills/powerfulmoves/pmoves.ai/agentgym-run)
Your own site
<a href="https://agentmods.dev/skills/powerfulmoves/pmoves.ai/agentgym-run"><img src="https://agentmods.dev/badge/skills/powerfulmoves/pmoves.ai/agentgym-run.svg" alt="Measured on agentmods" height="20"></a>
Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,169 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 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 $0.00130 $0.01169
Opus 5 $0.00065 $0.00584
Sonnet 5 $0.00026 $0.00234
Haiku 4.5 $0.00013 $0.00117

Measured 3d ago against content hash 57984dbeeca4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

agentgym-run scanned grade A 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 3d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sf http://localhost:3030/health && echo "TensorZero: OK" || echo "TensorZero: DOWN"
.claude/skills/agentgym-run/SKILL.md · 97 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

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. 3d ago First seen · 97 lines · 130 tokens per session scan A 57984dbeeca4

Subscribe to this mod's changes

agentgym-run is a skill published in the GitHub repository POWERFULMOVES/PMOVES.AI (7 stars, last pushed today), with no licence file. It adds 130 tokens to every session and 1,169 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

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