receiving-code-review

receiving-code-review is a skill for Claude Code, Codex from mambo-wang/ShowTime. It costs 50 tokens per session (1,913 once invoked), scanned A, original, no licence file.

A guide for handling code-review feedback before making the suggested changes, especially when the comments are unclear or technically questionable.

In plain words
What is it for?
It is for analysing review comments, validating technical concerns, and deciding how to respond or implement them.
Why use it?
It helps developers check whether feedback is correct and understand what it means instead of agreeing or making changes blindly.

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/mambo-wang/showtime/receiving-code-review
Any agent
npx skills add mambo-wang/ShowTime --skill receiving-code-review
Clone the repo
git clone --depth 1 https://github.com/mambo-wang/ShowTime

Made for: Claude Code, Codex.

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 receiving-code-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/mambo-wang/showtime/receiving-code-review.svg)](https://agentmods.dev/skills/mambo-wang/showtime/receiving-code-review)
Your own site
<a href="https://agentmods.dev/skills/mambo-wang/showtime/receiving-code-review"><img src="https://agentmods.dev/badge/skills/mambo-wang/showtime/receiving-code-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,913 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00050 $0.01913
Opus 5 $0.00025 $0.00957
Sonnet 5 $0.00010 $0.00383
Haiku 4.5 $0.00005 $0.00191

Measured 3d ago against content hash d2abac33cee0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

receiving-code-review 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 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.

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.

.codebuddy/skills/receiving-code-review/SKILL.md · 214 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. 3d ago First seen · 214 lines · 50 tokens per session scan A d2abac33cee0

Subscribe to this mod's changes

receiving-code-review is a skill published in the GitHub repository mambo-wang/ShowTime (10 stars, last pushed 3mo ago), with no licence file. It adds 50 tokens to every session and 1,913 once invoked, about $0.0003 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

material_converter

原生 OMML→LaTeX、page/slide/heading 锚点、manifest 记录);.

AlexBybye/SCUT_CS · 0 tokens

claude-md-improver

Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…

anthropics/claude-plugins-official · 82 tokens

debugging-output-and-previewing-html-using-ray

Use when user says "send to Ray," "show in Ray," "debug in Ray," "log to Ray," "display in Ray," or wants to visualize data, debug output, or show diagrams in the Ray desktop application.

coollabsio/coolify · 58 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

chenhao-limit-up

Use when evaluating A-share limit-up (涨停板) setups through Chen Hao's sentiment and momentum lens: market emotion cycles, board strength, follow-through, and short-term aggressive momentum trading.

questflowai/investorskills · 44 tokens