Cost Compact Context

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ruvnet

cost-compact-context

Wrap getTokenOptimizer().getCompactContext() to retrieve compacted ReasoningBank context for cost-analysis queries; report bridge-reported tokensSaved

Overview

Publisher	ruvnet
Repository	`ruflo`
Skill name	`cost-compact-context`
Stars	72.7K
Forks	8.6K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 ruvnet on GitHub. Read the source before you install it.

Installation

Install the Cost Compact Context 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.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/ruvnet/ruflo/tree/main/plugins/ruflo-cost-tracker/skills/cost-compact-context

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/ruvnet/ruflo.git /tmp/ruflo
mkdir -p .claude/skills
cp -r /tmp/ruflo/plugins/ruflo-cost-tracker/skills/cost-compact-context .claude/skills/cost-compact-context

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

Use it in TypingMind

Enable Cost Compact Context 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 Cost Compact Context 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 Cost Compact Context 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.

Cost Compact Context

Wraps getTokenOptimizer().getCompactContext() from @claude-flow/integration for cost-analysis queries. The bridge dynamically imports agentic-flow with graceful fallback: when the package isn't installed, tokensSaved is 0 and the skill exits cleanly. No MCP tool wraps getTokenOptimizer today (ADR-0002 §"Riskiest assumption"); we shell a Node one-liner instead.

Steps

Take the query — the single argument.
Invoke — run from anywhere under v3/ so @claude-flow/integration resolves:
```
bash
( cd v3 && node ../plugins/ruflo-cost-tracker/scripts/compact.mjs "<QUERY>" )
```
The script imports @claude-flow/integration/token-optimizer (canonical export — not dist/token-optimizer.js, which would double the .js extension via Node's ./* exports rule), calls getCompactContext(query), and prints a markdown summary plus a JSON line via COMPACT_QUIET=1.
Report — markdown table with: memories retrieved, tokens saved (bridge-reported), agentic-flow availability, cache hit rate. The script also emits a "bridge-reported, not measured against a no-RAG baseline" disclaimer. On bridge-unavailable: prints "agentic-flow not installed — bridge returns inert results." and exits cleanly.

Caveats — claimed upstream, not yet verified

CLAUDE.md root claims ReasoningBank retrieval: -32% tokens. The bridge's tokensSaved is query_tokens − compact_prompt_tokens (token-optimizer.ts:141–143) — a heuristic, not a baseline-measured saving. token-optimizer.ts:9–10 itself says: "No fabricated metrics are reported — all stats reflect real measurements". This skill carries that disclaimer forward.

Booster-specific availability is not exposed as a getter — observable only through optimizedEdit() returning method: 'agent-booster'. The canonical Tier 1 signal is [AGENT_BOOSTER_AVAILABLE] (see cost-booster-route).

Fallback

agentic-flow not installed → getCompactContext returns {tokensSaved: 0, memories: []} (line 116–124), optimizedEdit returns {method: 'traditional'}, getOptimalConfig falls back to anti-drift defaults. Skill exits cleanly with the "not available" message.

Cross-references

ADR-0002 Decision #2 + §"Riskiest assumption" · token-optimizer.ts:308 (singleton export) · docs/benchmarks/0002-baseline.md (verification findings).

Frequently asked questions

What does the Cost Compact Context AI skill do?

Wrap getTokenOptimizer().getCompactContext() to retrieve compacted ReasoningBank context for cost-analysis queries; report bridge-reported tokensSaved

Why use Cost Compact Context on TypingMind?

Because you install it once and use it with any model. Cost Compact Context 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 Cost Compact Context in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/ruflo/tree/main/plugins/ruflo-cost-tracker/skills/cost-compact-context. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cost Compact Context?

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 Cost Compact Context?

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

Is the Cost Compact Context AI skill free?

Yes. It is published on GitHub by ruvnet 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

Cost Compact Context

Steps

Caveats — claimed upstream, not yet verified

Fallback

Cross-references

Frequently asked questions

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