Janitor Value

Community

khendzel

janitor-value

Show whether each skill is earning its context-window cost — combined tokens-used view sorted by waste. Use when the user asks 'are my skills worth it', 'what's my context budget', 'which skills are dead weight', or wants to audit skill value, token cost, or usage. Trigger with '/janitor-value'.

Overview

Publisher	khendzel
Repository	`skills-janitor`
Skill name	`janitor-value`
Stars	124
Forks	19
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by khendzel on GitHub. Read the source before you install it.

Installation

Install the Janitor Value AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/khendzel/skills-janitor/tree/main/skills/janitor-value
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.

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/khendzel/skills-janitor.git /tmp/skills-janitor
mkdir -p .claude/skills
cp -r /tmp/skills-janitor/skills/janitor-value .claude/skills/janitor-value

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Janitor Value 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 Janitor Value 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 Janitor Value 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.

Skill Value Report

Show whether each installed skill is earning the context-window tokens it costs.

Overview

Combine token cost and usage tracking into a single view of every installed skill, sorted with the heaviest unused skills at the top. The report splits each skill's cost into what is permanently loaded (the description) and what only loads on demand (the body), then cross-references recent invocations so the user can see which skills are dead weight.

Replaces the v1.2 split between /janitor-tokens (cost only) and /janitor-usage (usage only).

Prerequisites

Claude Code with the skills-janitor plugin installed (provides scripts/value.sh)
bash 3.2+ (the stock macOS bash works; no external dependencies)
Read access to ~/.claude/skills, ~/.claude/agents, and local Claude Code session history
No authentication or API keys required — the script reads local files only

Instructions

Step 1: Run the value script

bash
bash ~/.claude/skills/skills-janitor/scripts/value.sh [--weeks N] [--budget N] [--json]

--weeks N — usage lookback window (default: 4)
--budget N — context window size for % calculations (default: 200000)
--json — emit raw JSON

Step 2: Present the results

Show the table and summary to the user. When explaining results, do NOT describe body tokens as permanent context cost — only descriptions are always loaded. Plugin-namespaced skills appear with their full invocation name (e.g., marketing-skills:image, figma:figma-use).

Step 3: Suggest action when waste is high

If "unused skill cost" exceeds 20% of the budget, recommend the user run /janitor-report for a full health check or (in v1.4+) /janitor-swipe to triage interactively.

Output

A table of every installed skill with:

Always — description tokens, permanently in the system prompt (the real context rent)
Body — the rest of SKILL.md, loaded only when the skill triggers (progressive disclosure)
Used? — yes if invoked in the lookback window, else NO
Last Used — date of most recent invocation

Followed by a summary:

Total tokens loaded into context (the always-loaded TOTAL includes skills plus subagent descriptions from ~/.claude/agents, reported as % of budget)
Active vs. unused split
Top wasters: heavy skills with zero usage

Error Handling

Error: value.sh: No such file or directory Solution: The plugin is installed under a different root. Locate it with ls ~/.claude/skills or check the plugin cache, then run the script from its actual location.
Error: Every skill shows NO in the Used? column Solution: The lookback window may be too short or session history is empty. Re-run with a longer window, e.g. --weeks 12.
Error: A skill shows 0 tokens Solution: Its SKILL.md is missing or unreadable. Run /janitor-report to surface broken skills, then /janitor-fix --prune to clean them up.
Error: Percentages look wrong for a non-default model Solution: Pass the correct context size explicitly, e.g. --budget 500000.

Examples

Example 1: Standard value check

Input: "Are my skills worth their token cost?"

Output: Run bash ~/.claude/skills/skills-janitor/scripts/value.sh, then present the table sorted by waste and the summary line, e.g. "Always-loaded total: 8,420 tokens (4.2% of 200k budget). 6 of 31 skills unused in 4 weeks; top waster: heavy-skill (1,900 tokens, never used)."

Example 2: Longer lookback, custom budget

Input: "Check skill usage over the last quarter against a 500k window."

Output: Run bash ~/.claude/skills/skills-janitor/scripts/value.sh --weeks 12 --budget 500000 and present the same table with the adjusted lookback and percentages.

Example 3: Machine-readable output

Input: "Give me the raw skill value data."

Output: Run the script with --json and return the JSON payload unmodified.

MCP servers (v1.7)

For the MCP side of context cost, run bash {baseDir}/../../scripts/mcp.sh [--weeks N] — inventories every configured server (user, project, plugin) with REAL call counts from session transcripts, and lists servers unused in the window. No token guesses: schemas live server-side, so the janitor reports calls, distinct tools used, and last-used instead.

Resources

Report script (plugin-relative): {baseDir}/../../scripts/value.sh
/janitor-report — full health check including duplicates and broken skills
/janitor-fix --prune — remove broken symlinks and empty skill dirs
/janitor-discover — find new skills or check one before installing

Frequently asked questions

What does the Janitor Value AI skill do?

Why use Janitor Value on TypingMind?

Because you install it once and use it with any model. Janitor Value 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 Janitor Value in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/khendzel/skills-janitor/tree/main/skills/janitor-value. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Janitor Value?

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 Janitor Value?

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

Is the Janitor Value AI skill free?

Yes. It is published on GitHub by khendzel 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Skill Value Report

Overview

Prerequisites

Instructions

Step 1: Run the value script

Step 2: Present the results

Step 3: Suggest action when waste is high

Output

Error Handling

Examples

Example 1: Standard value check

Example 2: Longer lookback, custom budget

Example 3: Machine-readable output

MCP servers (v1.7)

Resources

Frequently asked questions

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