deploy

A guarded release procedure for publishing a Worker, a small server program, to Cloudflare Workers. It checks the shared secret and pending changes before running the deployment pipeline.

In plain words
What is it for?
Use it to check deployment readiness, ask for confirmation, deploy the Worker, report its live URL, and optionally smoke-test it.
Why use it?
It reduces the risk of exposing a placeholder or committed secret and helps prevent unintended changes from reaching production.

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/billduke13/code-explainer-mcp/deploy
Any agent
npx skills add BillDuke13/code-explainer-mcp --skill deploy
Clone the repo
git clone --depth 1 https://github.com/BillDuke13/code-explainer-mcp

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 337 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 $0.00039 $0.00337
Opus 5 $0.00019 $0.00169
Sonnet 5 $0.00008 $0.00067
Haiku 4.5 $0.00004 $0.00034

Measured 2d ago against content hash 71e91b1b9951, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deploy 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 2d 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.

.claude/skills/deploy/SKILL.md · 38 lines

What it actually says

Deploy to Cloudflare Workers

Deploying mutates production. Run the pre-flight checks, get explicit confirmation, then deploy.

Pre-flight

  1. Secret is set as a real secret, not the placeholder. Check that SHARED_SECRET exists in the secret store:

    wrangler secret list
    

    If SHARED_SECRET is missing, stop and tell the user to run wrangler secret put SHARED_SECRET first.

  2. No real secret is committed. Confirm wrangler.jsonc still has vars.SHARED_SECRET set to "YOUR_SECRET_KEY_HERE". If it holds a real value, warn the user (it would commit a secret and override the secret store) before continuing.

  3. Working tree is clean enough to deploy — surface anything uncommitted that would ship unexpectedly (git status --short).

Deploy

  1. Confirm with the user that they want to deploy to production. Wait for an explicit yes.

  2. Run the pipeline:

    npm run deploy
    

    (= workers-mcp docgen src/index.ts && wrangler deploy)

  3. Report the deployed *.workers.dev URL (or custom route) from the wrangler output. Offer to smoke-test it with /smoke pointed at the deployed URL.

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. 2d ago First seen · 38 lines · 39 tokens per session scan A 71e91b1b9951

Subscribe to this mod's changes

deploy is a skill published in the GitHub repository BillDuke13/code-explainer-mcp (8 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 337 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens