reproduce

A workflow for reproducing a reported Cloudflare Workers or Agents GitHub issue in a small project. It deploys that project to a temporary Cloudflare account and reports the findings back on the issue.

In plain words
What is it for?
Use it when an agent-triggered GitHub issue needs a minimal Agents or Worker project, a temporary deployment, and a written reproduction report.
Why use it?
It gives maintainers an end-to-end reproduction instead of relying only on the issue description, which helps distinguish a real platform problem from project-specific setup.

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/cloudflare/agents/reproduce
Any agent
npx skills add cloudflare/agents --skill reproduce
Clone the repo
git clone --depth 1 https://github.com/cloudflare/agents

Made for: Claude Code, Codex.

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,761 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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 $0.00040 $0.03761
Opus 5 $0.00020 $0.01880
Sonnet 5 $0.00008 $0.00752
Haiku 4.5 $0.00004 $0.00376

Measured yesterday against content hash 70bf6ecdb16c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

reproduce scanned grade C with 2 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 yesterday.

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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

cd /workspace && rm -rf "$PUBLISH_DIR"

Makes network callslowCapability

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

All `gh`, `git`, `npm`, `curl`, and `wrangler` commands must run on the
agent-think/skills/reproduce/SKILL.md · 350 lines

How it starts

The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.

The current user message contains an <agent-think-run> envelope with repository, issue, instruction, requested-by, and (when available) trigger-comment-id. Use those values exactly. Never infer or substitute another target from examples, workspace contents, GitHub searches, or concurrent issues. If the envelope or a required field is absent, stop without cloning/editing/posting and return a structured skipped result. When trigger-comment-id is present, your first container action is the liveness reaction:

gh api repos/<repository>/issues/comments/<trigger-comment-id>/reactions \
  -f content=rocket

Reproduce the bug end-to-end and post your findings as an issue comment.

The instruction is the free-form text the user typed after @agent-think (it may be empty). Treat it as an extra hint from the triggering user — e.g. additional reproduction steps, a specific version, or a pointer to the suspect area. Let it guide your reproduction, but the issue itself remains the source of truth.

All gh, git, npm, curl, and wrangler commands must run on the container backend (bash({ command, backend: "container" })) — the shell backend has no real binaries or network. gh is already authenticated as the app; use it directly (no token handling).

0. Clone the repo

Clone the target repo directly under /workspace using its repository name (cloudflare/agents/workspace/agents):

REPO_DIR="/workspace/$(basename <repo>)"
if [ ! -d "$REPO_DIR/.git" ]; then
  git clone --depth=1 https://github.com/<repo>.git "$REPO_DIR"
fi

1. Understand the issue

gh issue view <issueNumber> --repo <repo> --json title,body,labels,comments

Read it carefully. Extract:

  • the observed behavior (the bug),
  • the expected behavior,
  • any "To Reproduce" steps, code snippets, versions, or stack traces.

Decide if it is reproducible at all. If it is a feature request, a question, a pure-docs issue, or has no concrete runnable behavior, stop here: return skipped: true, reproduced: false, and a summary explaining why. Still post a short, polite comment saying the repro-agent skipped it and why; begin it with Requested by @<requestedBy> when the run envelope has a requester.

Read the full file on GitHub · 350 lines

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. yesterday First seen · 350 lines · 40 tokens per session scan C 70bf6ecdb16c

Subscribe to this mod's changes

reproduce is a skill published in the GitHub repository cloudflare/agents (5,498 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 3,761 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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