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Vc Audit Plans

CommunityPopular
withkynam
vc-audit-plans

Audit active project plan files for staleness, completion, and routing truth. Use when cleaning up plans, reconciling active work, or archiving completed artifacts.

Overview

Publisherwithkynam
Repositoryvibecode-pro-max-kit
Skill namevc-audit-plans
Stars
1.1K
Forks
234
Bundled files
8
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.

  • 8 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 Audit Plans 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-audit-plans
  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-audit-plans .claude/skills/vc-audit-plans
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vc Audit Plans 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 Audit Plans 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 Audit Plans 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.

Audit Plans

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

Use this skill to review active plan artifacts and reconcile them with the current codebase.

This is a maintenance and recovery skill, not an automatic post-task hook.

Optional input: a feature, folder, plan filename, or maintenance scope to prioritize.

Prefer it when:

  • UPDATE PROCESS was skipped and active-plan cleanup drift accumulated
  • the user wants a periodic active-plan cleanup pass
  • multiple active plans need reconciliation after a burst of work

Workflow

  1. Read references/audit-plans.md for the full audit process.
  2. Run the inventory validator:
    bash
    node .claude/skills/vc-audit-plans/scripts/validate-plan-inventory.mjs
  3. Inventory plans in process/general-plans/active/ and process/features/*/active/. Plans now live inside {slug}_{date}/ task subfolders — scan one level deep. Do NOT count _REPORT_, _REF_, or _SPEC_ files inside task folders as plans; only _PLAN_ files count. For feature-scoped audits, first run find process/features/{feature}/ -type f | sort for full artifact visibility. For full audits, run find process/features/ -type f | sort to see all feature artifacts across all subdirs (active, completed, backlog, references, reports). 3.5. Scan task folder contents (co-located REPORT/REF/SPEC files) alongside each plan. Per task-folder artefact colocation, the correct home for every artefact (plan, spec, reports, references) is INSIDE its {slug}_{date}/ task folder; flag any task artefact found in the deprecated sibling reports//references/ dirs or any ad-hoc location as mis-located, and recommend moving it into the owning task folder. Match by feature slug, date proximity (7 days), or content reference to the plan filename.
  4. Cross-check each plan against the actual codebase with file existence checks and targeted rg searches.
  5. Classify each plan as Completed, Partially Done, Obsolete, Stale, Active, or Reference.
  6. Move only clearly completed or obsolete plans to the appropriate completed/ folder. Use git mv active/{slug}_{date}/ completed/{slug}_{date}/ — move the WHOLE task folder; no completed_ prefix added.
  7. Ask before deleting anything.
  8. Re-run the inventory validator after moving or editing plan files.

Output

Return a concise summary table with classification, action taken, and any user decisions needed. Include stale artifact findings (reports/references tied to completed or obsolete plans) with recommended actions.

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 Audit Plans AI skill do?

Audit active project plan files for staleness, completion, and routing truth. Use when cleaning up plans, reconciling active work, or archiving completed artifacts.

Why use Vc Audit Plans on TypingMind?

Because you install it once and use it with any model. Vc Audit Plans 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 Audit Plans 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-audit-plans. 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 Audit Plans?

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 Audit Plans?

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

Is the Vc Audit Plans 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.

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