vc-predict

name	vc-predict
description	5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
argument-hint	<feature description or change proposal> [--files <glob>]
trigger_keywords	risks, predict issues, architectural review
layer	helper
metadata	{"author":"claudekit","attribution":"Multi-persona prediction pattern adapted from autoresearch by Udit Goenka (MIT)","license":"MIT","version":"1.0.0"}

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

---

Deep Mode — Research Subagent Protocol

Before the 5-persona debate, spawn a research subagent that performs the following steps in order:

1. Git history scan — run git log --oneline --all -- [relevant files] for each file or directory the approach touches. Flag any commits within the last 6 months that suggest a prior attempt, revert, or known fix.
2. Prior phase reports — search task folders under process/features/{feature}/active/ and process/features/{feature}/completed/ for _REPORT_ files mentioning this surface (pattern: active/{slug}_{date}/{slug}_REPORT_{date}.md). Read any that contain keywords from the approach (e.g. "streaming", "SSE", "auth", "billing", "container lifecycle"). Legacy sibling reports/ dir may also exist — scan it too if present.
3. Test failure history — grep test output files and CI logs for FAIL or Error patterns on relevant module names. Note recurring failures.
4. Return a Historical Context block containing:
   • What was tried before (commit refs, dates, brief description)
   • What failed and why
   • Current state of the surface (is it stable, under active churn, recently refactored?)
   • Known landmines (specific lines, patterns, or edge cases that broke before)

The 5 personas then receive this Historical Context block before their independent analysis phase. Each persona incorporates it when relevant.

Output Quality Difference

Simple predict (no research):

"Senior dev: this streaming approach could cause a memory leak in the SSE proxy."

Deep predict (with historical research):

"Senior dev: we tried this exact streaming approach in commit a3f921 (2026-03-15) — it caused a memory leak in the SSE proxy because the Bun response body was never released on client disconnect. The current proposal has the same pattern in packages/api/src/routes/gateway-proxy.ts line 84. The fix at the time was adding an AbortController listener; verify that is still present or re-apply."

---

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

---

Output Format

## Prediction Report: [proposal title]

## Verdict: GO | CAUTION | STOP

### Agreements (all personas align)
- [Point 1 — what they all agree on]
- [Point 2]

### Conflicts & Resolutions

| Topic | Architect | Security | Performance | UX | Devil's Advocate | Resolution |
|-------|-----------|----------|-------------|-----|-----------------|------------|
| [Issue] | [View] | [View] | [View] | [View] | [View] | [Recommendation] |

### Risk Summary

| Risk | Severity | Mitigation |
|------|----------|------------|
| [Risk description] | Critical/High/Medium/Low | [Concrete action] |

### Recommendations
1. [Action item — rationale]
2. [Action item — rationale]
3. [Action item — rationale]

---

Verdict Levels

Verdict	Meaning
GO	All personas aligned, no critical risks, proceed with confidence
CAUTION	Concerns exist but are manageable — mitigations identified, proceed carefully
STOP	Critical unresolved issue found — needs redesign or more information before proceeding

STOP Triggers (any one is sufficient)

• Security persona identifies auth bypass or data exposure with no viable mitigation
• Architect identifies fundamental design incompatibility requiring significant rework
• Performance persona identifies unacceptable latency or query explosion with no workaround
• Devil's Advocate exposes a false assumption that invalidates the entire approach

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Integration with Other Skills

Workflow Step	Skill	How
Deepen risk scenarios	vc-scenario	Feed Risk Summary rows as feature description
Create implementation plan	generate-plan / plan-agent	Attach Recommendations as constraints to the canonical planning path
High-risk feature implementation	execute-agent	Reference CAUTION/STOP items as acceptance gates

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Example Invocations

Simple Mode (default)

/vc-predict "Add WebSocket support for real-time notifications"
/vc-predict "Migrate authentication from JWT to session cookies"
/vc-predict "Add multi-tenancy to the database layer"
/vc-predict "Replace REST API with GraphQL" --files src/api/**/*.ts

Deep Mode

/vc-predict "Rework SSE streaming for chat responses" --deep
/vc-predict "Change container lifecycle on instance stop" --deep --files packages/api/src/infra/**/*.ts
/vc-predict "Refactor billing credit deduction" --deep

Deep mode is also auto-triggered (no flag needed) when the plan is COMPLEX shape or the approach touches auth, billing, container lifecycle, or streaming surfaces.