A review skill for checking work handed from a Kanban implementation queue. It independently verifies the result and its evidence before deciding whether to approve it, request changes, or escalate it.

Use it to review completed development work against its requirements, inspect supporting evidence, and record an approval, change request, or escalation.

It provides a separate quality check before an implementation task is marked complete.

sdlc-review — Skill for Claude Code and Codex by ggg123124

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 ggg123124/vrchat-assistant --skill sdlc-review

Clone the repo

git clone --depth 1 https://github.com/ggg123124/vrchat-assistant

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ggg123124/vrchat-assistant/sdlc-review/github.svg)](https://agentmods.dev/skills/ggg123124/vrchat-assistant/sdlc-review)

Your own site

<a href="https://agentmods.dev/skills/ggg123124/vrchat-assistant/sdlc-review"><img src="https://agentmods.dev/badge/skills/ggg123124/vrchat-assistant/sdlc-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ggg123124/vrchat-assistant/sdlc-review"><img src="https://agentmods.dev/badge/skills/ggg123124/vrchat-assistant/sdlc-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,861 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 100% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5.1	$0.00015	$0.01861
Opus 5	$0.00008	$0.00931
Sonnet 5	$0.00003	$0.00372
Haiku 4.5	$0.00002	$0.00186

Measured 7d ago against content hash ce90e8a3e145, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

sdlc-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 7d 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.

Origin

This is a copy

100% identical to sdlc-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/sdlc-review/SKILL.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SDLC Review Skill

Independently verify work handed from a Kanban implementation run to the review lane, then approve it, request changes, or escalate. This skill reviews the deliverable and its evidence; it does not take over the implementer's work.

When to Use

Use this skill when all of the following are true:

the dispatcher spawned you for a task claimed from the review lane;
an implementer submitted a review_requested handoff;
the task needs an independent verdict before it can be completed.

Do not use it for a separate downstream review card. A downstream card is ordinary implementation work with a review-oriented specification and completes through its own lifecycle.

Prerequisites

A Kanban worker context with the current task and run identifiers.
Native Kanban tools: kanban_show, kanban_comment, kanban_complete, kanban_request_changes, and kanban_block.
Workspace access through read_file, search_files, and terminal when the deliverable is code.
The task's original specification, acceptance criteria, handoff summary, and prior run history must be available through kanban_show.

How to Run

This skill is loaded automatically by the review dispatcher. Start with kanban_show before inspecting files or choosing a verdict.

Read the task specification and the latest review_requested handoff.
Inspect the actual deliverable and run relevant verification.
Choose exactly one verdict: approve, request changes, or escalate.
Record concrete evidence in the terminal Kanban transition.

Quick Reference

Verdict	When	Final action
Approve	Acceptance criteria and verification pass	`kanban_complete`
Request changes	Correctable implementation defects remain	`kanban_comment`, then `kanban_request_changes`
Escalate	A human decision or external prerequisite is required	`kanban_block`

A requested-changes transition returns the task to its original implementer. When that implementer requests review again without naming a reviewer, the persisted reviewer provenance routes the re-review back to the same reviewer profile.

Read the full file on GitHub · 182 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.

7d ago First seen · 182 lines · 15 tokens per session scan A ce90e8a3e145

Subscribe to this mod's changes

sdlc-review is a skill published in the GitHub repository ggg123124/vrchat-assistant (21 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,861 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to sdlc-review, differing in 0 lines, and is treated as a copy.

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