iceni 0.1.2

Auto-discovered, cross-model-calibrated, self-evolving prompt aliases for AI agents

ICENI Protocol

Save your best AI instructions once. Use them everywhere — in one word.

ICENI is a reusable-workflow system for AI assistants. You write an expert prompt once, give it a name (review, security-audit, refactor), and from then on that word is all you type. ICENI renders the right calibrated prompt for whichever model you're using — Claude, ChatGPT, or Kimi — and produces structured, consistent output every time.

It won't make the model smarter. It will save you from retyping the same 60-word instruction block a hundred times, get the answer right first time (no re-runs), and produce output that other tools and agents can parse reliably.

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Who is this for?

Person	What ICENI does for them
Developer	review, refactor, test-gen, security-audit in every project — same structured output every time
Writer / marketer	blog-outline, email-reply, summarize with your house style baked in
Analyst / researcher	research-brief, compare, decisions with consistent format to feed into pipelines
Team lead	Export a signed alias, the whole team imports it — one standard, signature-verified
Claude Code user	/iceni inside Claude Code runs your full workflow library in the terminal

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Which AI platforms are tested and working?

Platform	Integration	Status
Claude Desktop	MCP server — workflows appear under + → Connectors → iceni	✅ Tested
Claude Code	Skill (/iceni) + CLI via python -m iceni	✅ Tested
ChatGPT	CLI with --model gpt (OpenAI API key required)	✅ Tested
Kimi (Moonshot)	CLI with --model kimi (Moonshot API key required)	✅ Tested
Any OpenAI-compatible API	Set OPENAI_API_KEY + base URL	Works offline, render only
No AI at all	--preview mode renders the prompt without calling any model	✅ Works offline

The core features — create, list, show, export, import — work completely offline with no API keys.

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Quickstart (5 minutes, no API key needed)

Prerequisites

• Python 3.10+
• pip
• Claude Desktop (for the + → Connectors integration) or Claude Code (for /iceni)

Step 1 — Install

pip install iceni

That's it. To call live models (optional), install the extras:

pip install "iceni[all]"     # adds Anthropic + OpenAI SDKs and discovery

Verify it works:

iceni --version
iceni doctor

Install from source instead (for development)

git clone https://github.com/stevenjtobin/iceni-protocol.git
cd iceni-protocol
pip install -e ".[all]"

Step 2 — Initialise your library

iceni init

This creates a local store in ~/.iceni/ (never committed, never shared).

Your data stays local. ICENI makes no network calls unless you explicitly set an API key and run --execute. No telemetry, no cloud sync, no passive collection of your conversations. The auto-discovery command (iceni discover) is manual and opt-in — it reads your local Claude Code logs only when you ask it to, proposes candidates, and signs nothing until you approve. You can delete ~/.iceni/ at any time to reset completely.

Step 3 — Install a workflow pack

iceni pack list              # see all 19 packs (208 workflows)
iceni pack install code-quality-plus   # install one pack
iceni pack install all       # or install everything at once
iceni list                   # confirm they're there

Step 4 — Connect to Claude Desktop (optional)

iceni connect-desktop

Restart Claude Desktop → click + (bottom-left) → Connectors → iceni. Your workflows appear. Pick one, paste your content, done.

Can't find it? Make sure you restarted Claude Desktop after running connect-desktop. The + button is in the chat input bar, not the sidebar.

Step 5 — Try your first workflow

In the terminal (no AI key needed — preview only):

iceni run review examples/buggy_example.py --preview --model claude

In Claude Desktop: Click + → Connectors → iceni → choose security-audit → paste any code.

In Claude Code: Type /iceni and pick a workflow from the menu.

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The 208-workflow library

ICENI ships with 19 themed packs covering the most common AI tasks:

Code packs — code-quality-plus, testing, refactoring, documentation, debugging, git-workflow, architecture-design, devops-deploy, lang-tools

Chat / writing packs — writing-pro, email-comms, research-analysis, business-strategy, marketing-content, learning-explain, decisions-planning, document-data

See the full list: library/CATALOG.md

iceni pack list              # browse all packs
iceni pack install testing   # install one
iceni list                   # see your installed workflows
iceni show review            # inspect a workflow + signature

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Create your own workflow

iceni create my-brief \
  --goal "Write a one-page project brief from bullet points." \
  --input "{{notes}}" \
  --constraint "plain English, no jargon" \
  --output-format "Problem / Approach / Outcome / Next steps" \
  --hint "claude=use XML sections" \
  --hint "gpt=use markdown headers"

Each workflow gets an Ed25519 signature. When you share it, the recipient's iceni import verifies the signature before installing — tampered aliases are rejected.

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Share with your team

iceni export review            # → review.iceni  (signed, portable)
# send review.iceni to a colleague
iceni import review.iceni      # verified + installed on their machine

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Key commands

iceni list                     # all installed workflows
iceni show <name>              # prompt text + signature status
iceni run <name> <file>        # render prompt for a file (--preview skips the API call)
iceni compare <name>           # side-by-side Claude / GPT / Kimi renderings
iceni stats                    # your accumulated savings (words saved, re-runs avoided)
iceni pack list                # browse all 19 packs
iceni pack install <name>      # add a pack
iceni export <name>            # portable signed alias file
iceni import <name>.iceni      # verified install from a file
iceni connect-desktop          # wire into Claude Desktop automatically
iceni mcp                      # start the MCP stdio server manually (for debugging)
iceni doctor                   # check config + which model keys are set

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Using API keys (live model calls)

ICENI works without any API key in --preview mode. To call models directly:

# Windows PowerShell
$env:ANTHROPIC_API_KEY = "sk-ant-..."
$env:OPENAI_API_KEY    = "sk-..."
$env:MOONSHOT_API_KEY  = "..."

iceni run review examples/buggy_example.py --execute --model claude
iceni compare review --execute

# macOS / Linux
export ANTHROPIC_API_KEY="sk-ant-..."
iceni run review examples/buggy_example.py --execute --model claude

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How the trust chain works

Every workflow carries a cryptographic signature so you always know who created it and that it hasn't been modified:

"review"  →  local petname  →  aip:key:ed25519:…  →  signed intent (sha256)  →  per-model render
(human)      (anti-mimicry)     (identity)             (Ed25519)                  (Claude/GPT/Kimi)

The human-readable name is not the trust anchor. Trust rides on the Ed25519 key. A tampered alias will be rejected at iceni import.

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Benchmark results (honest)

We ran a 10-task offline benchmark against plain prompts. Key findings:

• 100% structured output (ICENI) vs 0% (plain prompts) on the Structure-Fidelity Score test
• +7 points functional quality on real code tasks (320–577 token inputs)
• −3 to −6 points on tiny inputs (<200 tokens) — ICENI's instruction overhead outweighs the benefit
• Average delta: +1.55 — the real value is consistency and re-runs avoided, not a quality leap

Full results: benchmarks/report-10task-offline.md

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Project layout

src/iceni/
  cli.py            all commands
  mcp_server.py     Claude Desktop / MCP integration
  calibration.py    per-model prompt renderer (Claude / GPT / Kimi)
  discovery.py      auto-discover recurring prompts from conversation logs
  feedback.py       outcome tracking + workflow evolution
  trust/            Ed25519 signing, identity, keystore
  store/            SQLite alias store + migrations
  providers/        Anthropic · OpenAI · Kimi (openai-compat)
  packs/            19 JSON packs, 208 workflows
benchmarks/         10-task benchmark, SFS test, offline results
examples/           intentionally-buggy demo code (for testing security-audit)
library/            CATALOG.md + pack builder
tests/              smoke, share, router, feedback, packs
site/               landing page (index.html)

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Roadmap

• Core CLI (init, create, list, show, run, compare, export, import)
• Trust chain (Ed25519 signatures, content-addressed intents)
• MCP server (Claude Desktop + → Connectors integration)
• Claude Code skill (/iceni)
• 208-workflow library (19 packs)
• Auto-discovery (cluster recurring prompts from conversation logs)
• Outcome tracking + usage stats
• PyPI release (pip install iceni)
• GPT / Kimi auto-calibration from live execution feedback
• Drift detection (alert when a workflow's output style shifts)
• Pack marketplace

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License

MIT — see LICENSE

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Contributing

Issues and PRs welcome. If you build a workflow pack worth sharing, open a PR against library/build_library.py.