Vc Risk Evidence Pack logo

Vc Risk Evidence Pack

CommunityPopular
withkynam
vc-risk-evidence-pack

Define and generate the manual-first evidence pack for high-risk work. Covers 6 high-risk class definitions and the 5-artifact schema required before finalizing, pushing, or handing off.

Overview

Publisherwithkynam
Repositoryvibecode-pro-max-kit
Skill namevc-risk-evidence-pack
Stars
1.1K
Forks
234
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by withkynam on GitHub. Read the source before you install it.

Installation

Install the Vc Risk Evidence Pack AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-risk-evidence-pack
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/withkynam/vibecode-pro-max-kit.git /tmp/vibecode-pro-max-kit
mkdir -p .claude/skills
cp -r /tmp/vibecode-pro-max-kit/.claude/skills/vc-risk-evidence-pack .claude/skills/vc-risk-evidence-pack
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vc Risk Evidence Pack in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vc Risk Evidence Pack on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vc Risk Evidence Pack is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

vc-risk-evidence-pack

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

Generate and validate the manual-first evidence pack required before finalizing, pushing, or handing off high-risk implementation work.

When To Invoke

  • VALIDATE Layer 1 security surface check — when the plan touches a high-risk class, flag the need for an evidence pack before routing to execute-agent.
  • EXECUTE before marking high-risk work complete — execute-agent must produce or verify the evidence pack exists before reporting DONE on any high-risk class.
  • code-reviewer as pre-PR quality gate — code-reviewer checks for the evidence pack presence before approving changes that touch a high-risk surface.

6 High-Risk Class Definitions

From process/development-protocols/orchestration.md ("High-Risk Execution Handoff") and process/development-protocols/implementation-standards.md ("Risky Work Evidence Contract") — both sources agree:

  1. auth or identity — authentication flows, session tokens, user identity resolution, Clerk JWT handling, or any surface that determines who the caller is.
  2. billing or credits — billing events, credit balance mutations, Stripe charge flows, OpenRouter credit accounting, credit transaction records, or subscription state changes.
  3. schema/data migration or destructive data mutation — Prisma migrations, raw SQL mutations, destructive writes that delete or overwrite persistent data, or schema changes to existing models.
  4. public API or external contract changes — tRPC procedure signature changes visible to the frontend, Hono route contract changes consumed by external callers, webhook shape changes, or any API surface that third parties or the client app depend on.
  5. deploy/runtime/container/proxy/gateway behavior — Dockerfile changes, supervisord config, start.sh, container service ports, Bun server entry, Hono route registration, Caddy proxy config, worker-node provisioning, or any change that affects how a running service starts or routes traffic.
  6. permission, secret, or trust-boundary logic — instance token gating, verifyInstanceOwnership, BYOK secret fetch paths, MITM proxy key injection, Bright Data credential handling, or any logic that controls what a caller is allowed to access.

5-Artifact Schema

Per task-folder artefact colocation, all artifacts go inside the selected plan's task folder (e.g. process/features/{feature}/active/{slug}_{date}/harness/ or process/general-plans/active/{slug}_{date}/harness/), so the whole pack moves with the plan as a unit. Legacy path reports/harness/ is deprecated for new writes; never write the pack to a sibling reports/ dir or any ad-hoc location. The validator script lives at .claude/skills/vc-risk-evidence-pack/scripts/validate-risk-artifacts.mjs.

1. risk-gate.json

Records the risk class, work description, and approver identity before work begins or is finalized.

json
{
  "riskClass": "<one of the 6 classes above>",
  "workDescription": "<short description of the change>",
  "approver": "<person or agent that reviewed the risk classification>",
  "mustStopBeforeFinalize": true
}

2. context-snippets.json

Relevant code snippets with exact file and line citations for every surface the change touches in the high-risk class.

json
{
  "snippets": [
    {
      "file": "packages/api/src/router/billing.ts",
      "lines": "120-145",
      "description": "verifyInstanceOwnership call before secret read",
      "content": "<excerpt>"
    }
  ]
}

3. verification.json

Documents every verification step taken and its result. Steps must cover both the happy path and at least one failure or boundary case.

json
{
  "steps": [
    {
      "step": "<what was verified>",
      "command": "<command run, if applicable>",
      "result": "PASS | FAIL | SKIP",
      "notes": "<observations>"
    }
  ]
}

4. review-decision.json

The explicit reviewer decision record. Must contain APPROVE or REJECT with a written rationale — no implicit approvals.

json
{
  "reviewer": "<name or agent>",
  "decision": "APPROVE | REJECT",
  "rationale": "<written reason>",
  "timestamp": "<ISO 8601 date>"
}

5. adversarial-validation.json

Required when the path is high-risk or attack-sensitive (e.g. auth bypass, privilege escalation, secret exfiltration). Documents adversarial scenarios considered and whether each was ruled out.

json
{
  "scenarios": [
    {
      "scenario": "<attack or misuse description>",
      "ruled_out": true,
      "rationale": "<why this path is not exploitable>"
    }
  ]
}

Auto-Stop Rule

If risk is high, do not treat the work as ready to finalize until the evidence pack exists and the reviewer decision is recorded.

If the evidence pack is missing, say so explicitly — do not proceed silently, do not imply the work is proven, and do not report DONE.

Verbatim from implementation-standards.md:

Auto-stop rule:

  • if risk is high, do not treat the work as ready to finalize until the evidence pack exists and the reviewer decision is recorded
  • if the evidence pack is missing, say so explicitly instead of implying the work is proven

This contract is manual-first and opt-in by risk class. It is not a default blocking hook.

Verbatim from orchestration.md:

If the risk gate says mustStopBeforeFinalize: true, do not imply the work is fully proven until the pack exists and the reviewer decision is present. Keep this manual-first. Do not invent a blocking hook or alternate workflow owner.

Validation Checklist

Steps to confirm each artifact is complete before handoff:

  • risk-gate.json populated with correct risk class, work description, approver, and mustStopBeforeFinalize flag
  • context-snippets.json includes all affected file:line citations for every surface touching the high-risk class
  • verification.json documents each test step and result, covering happy path and at least one boundary/failure case
  • review-decision.json has explicit APPROVE or REJECT with written rationale and timestamp — no implicit approvals
  • adversarial-validation.json present if the path is attack-sensitive (auth bypass, privilege escalation, secret exfiltration, trust-boundary violation)

High-Risk Work Evidence Contract

Verbatim from process/development-protocols/implementation-standards.md ("Risky Work Evidence Contract"):

For high-risk work, use a manual-first evidence pack before calling the change ready for finalize, push, or human handoff.

High-risk classes include:

  • auth or identity flows
  • billing, payments, or credit accounting
  • schema/data migrations or destructive writes
  • public API or external contract changes
  • deploy/runtime/container/proxy/gateway behavior
  • permission, secret, or trust-boundary logic

Preferred artifact set inside the selected plan's task folder ({slug}_{date}/harness/):

  • risk-gate.json
  • context-snippets.json
  • verification.json
  • review-decision.json
  • adversarial-validation.json for high-risk or adversarial paths

Auto-stop rule:

  • if risk is high, do not treat the work as ready to finalize until the evidence pack exists and the reviewer decision is recorded
  • if the evidence pack is missing, say so explicitly instead of implying the work is proven

This contract is manual-first and opt-in by risk class. It is not a default blocking hook.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vc Risk Evidence Pack AI skill do?

Define and generate the manual-first evidence pack for high-risk work. Covers 6 high-risk class definitions and the 5-artifact schema required before finalizing, pushing, or handing off.

Why use Vc Risk Evidence Pack on TypingMind?

Because you install it once and use it with any model. Vc Risk Evidence Pack is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vc Risk Evidence Pack in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-risk-evidence-pack. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vc Risk Evidence Pack?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vc Risk Evidence Pack?

As many as you like. As long as a model supports skills, you can use Vc Risk Evidence Pack with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vc Risk Evidence Pack AI skill free?

Yes. It is published on GitHub by withkynam under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇