Anth Prod Checklist

What it does

When your agent uses it

• Deploying Claude-powered features to production
• Preparing for launch
• Implementing go-live validation
• With phrases like anthropic production

Example prompts

• “anthropic production”
• “deploy claude”
• “claude go-live”
• “/anth-prod-checklist”

Requirements

• Python 3
• Compatibility (from SKILL.md): Designed for Claude Code
• Pre-approved tools (allowed-tools): Read, Bash(curl:*), Grep

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Confirm every checklist item with an evidence link or redacted receipt: authentication, workspace isolation, model/version, error…
2. 2Run staging contract, health, synthetic redaction, timeout, rate-limit, permission, and output-safety tests. Verify logs/metrics contain…
3. 3Deploy the approved artifact to a small internal canary. Monitor p95/p99 latency, 4xx/5xx/429, token/cost aggregates, rate-limit headroom…
4. 4Require owner and on-call approval before staged production promotion. Preserve the prior revision and ensure the rollback path is…
5. 5After rollout, issue a redacted receipt, revoke temporary test access, and retain only the evidence required by the documented policy.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Bash(curl:*)
  • Grep

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • platform.claude.com
  • console.anthropic.com
  • status.anthropic.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Designed for Claude Code

  From compatibility in the SKILL.md frontmatter.

Context cost

Anth Prod Checklist loads about 1.8k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 586 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~87

When it runs · the whole SKILL.md, loaded when a task matches

~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 586 words, ~1,808 tokens.

name

anth-prod-checklist

description

Execute production deployment checklist for Claude API integrations. Use when deploying Claude-powered features to production, preparing for launch, or implementing go-live validation. Trigger with phrases like "anthropic production", "deploy claude", "claude go-live", "anthropic launch checklist", "production ready claude".

allowed-tools

Read, Bash(curl:*), Grep

compatibility

Designed for Claude Code

version

1.7.0

license

MIT

author

Jeremy Longshore <jeremy@intentsolutions.io>

tags

saas, ai, anthropic

async def health_check():
    try:
        # Use token counting as a cheap health probe (no generation cost)
        count = client.messages.count_tokens(
            model="claude-haiku-4-20250514",
            messages=[{"role": "user", "content": "ping"}]
        )
        return {"status": "healthy", "tokens": count.input_tokens}
    except Exception as e:
        return {"status": "degraded", "error": str(e)}

import logging
import time

logger = logging.getLogger("anthropic")

def tracked_create(**kwargs):
    start = time.monotonic()
    try:
        response = client.messages.create(**kwargs)
        duration = time.monotonic() - start
        logger.info(
            "claude_request",
            extra={
                "request_id": response._request_id,
                "model": response.model,
                "input_tokens": response.usage.input_tokens,
                "output_tokens": response.usage.output_tokens,
                "duration_ms": int(duration * 1000),
                "stop_reason": response.stop_reason,
            }
        )
        return response
    except Exception as e:
        duration = time.monotonic() - start
        logger.error("claude_error", extra={"error": str(e), "duration_ms": int(duration * 1000)})
        raise

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/.curated/anth-prod-checklist of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287