vc-predict

vc-predict is a skill for Claude Code, Codex from withkynam/vibecode-pro-max-kit. It costs 34 tokens per session (1,890 once invoked), scanned A, original, MIT.

A pre-implementation review in which five expert viewpoints analyze and debate a proposed change. It produces a shared recommendation before coding starts.

In plain words
What is it for?
Assessing major features, risky refactors, competing technical approaches, and other designs with unresolved questions.
Why use it?
It can expose architecture, security, performance, and user-experience problems while changes are still inexpensive to revise.

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/withkynam/vibecode-pro-max-kit/vc-predict
Any agent
npx skills add withkynam/vibecode-pro-max-kit --skill vc-predict
Clone the repo
git clone --depth 1 https://github.com/withkynam/vibecode-pro-max-kit

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 vc-predict

README.md
[![agentmods](https://agentmods.dev/badge/skills/withkynam/vibecode-pro-max-kit/vc-predict.svg)](https://agentmods.dev/skills/withkynam/vibecode-pro-max-kit/vc-predict)
Your own site
<a href="https://agentmods.dev/skills/withkynam/vibecode-pro-max-kit/vc-predict"><img src="https://agentmods.dev/badge/skills/withkynam/vibecode-pro-max-kit/vc-predict.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,890 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 $0.00034 $0.01890
Opus 5 $0.00017 $0.00945
Sonnet 5 $0.00007 $0.00378
Haiku 4.5 $0.00003 $0.00189

Measured 4d ago against content hash c8b78a0bef17, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vc-predict 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 4d 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/vc-predict/SKILL.md · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

vc-predict — Multi-Persona Pre-Analysis

Output style: Follow process/development-protocols/communication-standards.md — answer-first, plain language, no unexplained jargon, TL;DR on long responses.

Five expert personas independently analyze a proposed change, then debate conflicts to produce a consensus verdict before a single line of code is written.

When to Use

  • Before implementing a major or high-risk feature
  • Before a significant refactor or architecture change
  • Evaluating competing technical approaches
  • Stress-testing assumptions in a proposed design

When NOT to Use

  • Trivial or low-risk changes (use debugger for bugs, generate-plan / plan-agent for already-decided tasks)
  • Already-approved work with no open design questions
  • Pure dependency upgrades with no API changes

Mode Selection

vc-predict runs in Simple or Deep mode. Choose based on the conditions below.

Simple Deep
Context source Approach description already in context Approach description + historical research subagent
Subagent spawned No Yes — reads git log, prior reports, test failure history
Persona debate quality Reasons from first principles "We tried this 3 months ago and hit X"
When to use Contained feature, clear scope, no prior attempts See trigger conditions below

Deep Mode — Trigger Conditions (any one is sufficient)

  • The approach involves a pattern previously attempted in this codebase (git history may show prior attempts)
  • The approach touches a surface with known failure history: auth, billing, container lifecycle, streaming, or WebSocket reconnect
  • Caller explicitly requests deep mode (--deep flag or "use deep predict")
  • The plan is COMPLEX shape and this is the pre-checklist predict call

Simple Mode — Trigger Conditions (default)

  • Approach is a contained feature with clear scope
  • No prior attempts at this surface area are likely
  • Plan is SIMPLE shape and the design is not controversial

Read the full file on GitHub · 185 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. 4d ago First seen · 185 lines · 34 tokens per session scan A c8b78a0bef17

Subscribe to this mod's changes

vc-predict is a skill published in the GitHub repository withkynam/vibecode-pro-max-kit (1,115 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 1,890 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 2026-08-30.

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