cuecards: Skill for Claude Code

.agents/skills/vc-predict/SKILL.md

vc:predict is a skill for Claude Code from opencue/cuecards. It costs 34 tokens per session (1,020 once invoked), scanned A, original, MIT.

A pre-change review helper in which five specialist viewpoints examine a proposed change for architecture, security, performance, and user experience risks.

In plain words
What is it for?
Use it to stress-test major features, refactors, and competing technical approaches before implementation.
Why use it?
It surfaces design problems and conflicting concerns before significant or high-risk code changes are made.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is opencue/cuecards's own configuration. It tells Claude Code how to work on cuecards itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything cuecards configures →

Reuse

Borrowing it

Nothing to install: this file belongs to opencue/cuecards. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/opencue/cuecards/main/.agents/skills/vc-predict/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/opencue/cuecards

Made for: Claude Code.

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/opencue/cuecards/vc-predict.svg)](https://agentmods.dev/skills/opencue/cuecards/vc-predict)
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<a href="https://agentmods.dev/skills/opencue/cuecards/vc-predict"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/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 1,020 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 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 5.1 $0.00034 $0.01020
Opus 5 $0.00017 $0.00510
Sonnet 5 $0.00007 $0.00204
Haiku 4.5 $0.00003 $0.00102

Measured 3d ago against content hash 9357ac21d141, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, 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 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.

.agents/skills/vc-predict/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

vc:predict — Multi-Persona Pre-Analysis

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

The 5 Personas

Persona Focus Core Questions
Architect System design, scalability, coupling Does this fit the architecture? Will it scale? What new coupling does it introduce?
Security Attack surface, data protection, auth What can be abused? Where is data exposed? Are auth boundaries respected?
Performance Latency, memory, queries, bundle size What is the latency impact? N+1 queries? Memory leaks? Bundle bloat?
UX User experience, accessibility, error states Is this intuitive? What does the error state look like? Accessible on mobile?
Devil's Advocate Hidden assumptions, simpler alternatives Why not do nothing? What is the simplest alternative? Which assumption could be wrong?

Debate Protocol

  1. Read the proposed change/feature description from the argument
  2. Read relevant code if file paths are provided (grep for affected areas)
  3. Each persona analyzes independently — do not let personas influence each other during this phase
  4. Identify agreements — points where all (or 4+) personas align
  5. Identify conflicts — points where personas meaningfully disagree
  6. Weigh tradeoffs — for each conflict, evaluate which concern has higher impact
  7. Produce verdict — GO / CAUTION / STOP with actionable recommendations

Read the full file on GitHub · 120 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. 3d ago First seen · 120 lines · 34 tokens per session scan A 9357ac21d141

Subscribe to this mod's changes

vc:predict is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 1,020 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 2026-09-03.

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