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Plan Kb

Organization
hraness
plan-kb

Create or evolve a durable Markdown plan inside a hraness/wordcell vault. Use when a user asks for an implementation plan, proposal, RFC, migration plan, execution audit, phased checklist, or an update to an existing plan's decisions, progress, review findings, verification evidence, or final result.

Overview

Publisherhraness
Repositoryslopcamera
Skill nameplan-kb
Stars
7
Forks
1
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Plan Kb 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/hraness/slopcamera/tree/main/.agents/skills/plan-kb
  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/hraness/slopcamera.git /tmp/slopcamera
mkdir -p .claude/skills
cp -r /tmp/slopcamera/.agents/skills/plan-kb .claude/skills/plan-kb
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Kb 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 Plan Kb 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 Plan Kb 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.

Write a durable plan

Keep the plan useful before, during, and after execution. It is the coordination record, not a disposable answer or a duplicate task tracker.

Find the plan's owner

  1. Resolve <vault> to the directory containing its authored or managed index.md front door, then set the shell-local KB_ROOT to that path (KB_ROOT=kb from a typical repository root, or KB_ROOT=. from inside the vault). Read the vault's AGENTS.md and the nearest guide under <vault>/plans/. Pass that resolved root to every command; do not assume the starting directory is the vault.
  2. When the plan owns a repository path, resolve the repository root as KB_REPO and load that path's current memory before a whole-vault search:
sh
wordcell context "<repository-path>" --root "$KB_ROOT" --repo "$KB_REPO"

Use --kind file or --kind directory when an absent future path cannot be classified from the filesystem. Read the inherited guides first, then the applicable maintained knowledge, active plans, dated research, reports, and separate historical-plan group.

  1. Search existing plans before creating one:
sh
wordcell list --root "$KB_ROOT" --where type=plan --sort area --json
wordcell search "the intended outcome" --root "$KB_ROOT" --json

If wordcell is not installed, do not let retrieval tooling block the plan: use rg or the available file search over <vault>/plans/, titles, aliases, and relevant terms. If the directory is not an initialized hraness/wordcell vault, follow the repository's existing planning convention instead of initializing one without being asked. Semantic search writes only a derived local cache; when that cache location is not writable, use exact search or point XDG_CACHE_HOME at a writable cache directory.

  1. Update an existing plan when it already owns the outcome. Create a new file only for independently executable work.
  2. Use <vault>/plans/<descriptive-kebab-name>.md unless the local guide already groups plans by area. Do not reorganize older plans merely to impose a new tree.

Write from evidence

Read the plan structure reference, then tailor it to the work. Preserve these invariants:

  • State one concrete outcome and the current status.
  • Record what is known, what is assumed, and what remains to discover.
  • Separate in-scope work from non-goals.
  • Put constraints and decisions before the steps they shape.
  • Make dependencies and ordering visible.
  • Give each acceptance claim a verification method.
  • Include rollback or recovery when a change can leave durable state behind.

Turn a missing implementation detail into an ordered discovery gate when the outcome and authorization are already clear and the decision can be made from in-scope evidence. Stop and request direction when the unknown would change the intended outcome, expand authority or external coordination, or choose between materially different products.

Use small frontmatter. Start with type: plan, a descriptive title and one-sentence description, a kebab-case area, and one of proposed, accepted, in-progress, blocked, completed, superseded, or cancelled. When the plan owns work in a code repository, add repository_scopes with the few exact canonical repository-relative files or directories it explains. Use no globs. A future path is valid; update an active plan deliberately when code moves instead of relying on inferred Git renames. Add aliases or tags only when they help humans or structured queries.

Grow the same file during execution

  • Change status when reality changes, not in anticipation.
  • Check off completed work without deleting the original intent.
  • Incorporate decisions, review findings, deviations, and command or test evidence where a future reader can understand their consequence.
  • When blocked, name the exact missing condition and the safe work already completed.
  • When a plan becomes completed, superseded, or cancelled, write a non-empty ## Result and ## Durable memory. State what shipped or why work stopped in Result. In Durable memory, link each reusable conclusion to the maintained note, guide, documentation, or checked code contract that now owns it. When nothing warrants promotion, say so explicitly and give the reason. Retain the terminal plan as history.
  • Do not create separate progress, review, or completion files for the same plan.

Connect and verify

Add wikilinks or typed relationships only where the prose and evidence explain a useful connection. Review the changed plan for reusable concepts before refreshing:

sh
wordcell percolate "<plan-note-id>" --root "$KB_ROOT" --limit 25 --json
wordcell refresh --root "$KB_ROOT"
wordcell check --root "$KB_ROOT"

Run those commands when the plan lives in an initialized hraness/wordcell vault. In a repository-native planning directory, use that repository's own validation instead. Review broken links first, then inspect orphan and mention advisories in context. Promote only concepts likely to be reused, and ground every typed relationship in the plan's prose. An independently useful plan may legitimately remain an orphan in a new or sparse vault. Record that disposition mentally or in the task handoff; do not manufacture links or relations merely to improve graph counts.

In an authored-catalog vault, refresh leaves the front door unchanged and wordcell catalog --root "$KB_ROOT" renders an exhaustive disposable inventory. In a managed vault, independent edit lanes use wordcell check --root "$KB_ROOT" --no-catalog; the integrating lane performs the single catalog refresh.

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 Plan Kb AI skill do?

Create or evolve a durable Markdown plan inside a hraness/wordcell vault. Use when a user asks for an implementation plan, proposal, RFC, migration plan, execution audit, phased checklist, or an update to an existing plan's decisions, progress, review findings, verification evidence, or final result.

Why use Plan Kb on TypingMind?

Because you install it once and use it with any model. Plan Kb 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 Plan Kb in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hraness/slopcamera/tree/main/.agents/skills/plan-kb. 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 Plan Kb?

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 Plan Kb?

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

Is the Plan Kb AI skill free?

Yes. It is published on GitHub by hraness 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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