806d402876 feat: chat onboarding and routine advisor (#927)
* feat: port NPA psychographic profiling system into IronClaw

Port the complete psychographic profiling system from NPA into IronClaw,
including enriched profile schema, conversational onboarding, profile
evolution, and three-tier prompt augmentation.

Personal onboarding moved from wizard Step 9 to first assistant
interaction per maintainer feedback — the First Contact system prompt
block now instructs the LLM to conduct a natural onboarding conversation
that builds the psychographic profile via memory_write.

Changes:
- Enrich profile.rs with 5 new structs, 9-dimension analysis framework,
  custom deserializers for backward compatibility, and rendering methods
- Add conversational onboarding engine with one-step-removed questioning
  technique, personality framework, and confidence-scored profile generation
- Add profile evolution with confidence gating, analysis metadata tracking,
  and weekly update routine
- Replace thin interaction style injection with three-tier system gated on
  confidence > 0.6 and profile recency
- Replace wizard Step 9 with First Contact system prompt block that drives
  conversational onboarding during the user's first interaction
- Add autonomy progression to SOUL.md seed and personality framework to
  AGENTS.md seed

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat: replace chat-based onboarding with bootstrap greeting and workspace seeds

Remove the interactive onboarding_chat.rs engine in favor of a simpler
bootstrap flow: fresh workspaces get a proactive LLM greeting that
naturally profiles the user. Identity files are now seeded from
src/workspace/seeds/ instead of being hardcoded. Also removes the
identity-file write protection (seeds are now managed), adds routine
advisor integration, and includes an e2e trace for bootstrap greeting.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat(safety): sanitize identity file writes via Sanitizer to prevent prompt injection

Identity files (SOUL.md, AGENTS.md, USER.md, IDENTITY.md) are injected into
every system prompt. Rather than hard-blocking writes (which broke onboarding),
scan content through the existing Sanitizer and reject writes with High/Critical
severity injection patterns. Medium/Low warnings are logged but allowed.

Also clarifies AGENTS.md identity file roles (USER.md = user info, IDENTITY.md =
agent identity) and adds IDENTITY.md setup as an explicit bootstrap step.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* docs: update profile_onboarding_completed comment to reflect current wiring

The field is now actively used by the agent loop to suppress BOOTSTRAP.md
injection — remove the stale "not yet wired" TODO.

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(setup): use env_or_override for NEARAI_API_KEY in model fetch config

When the user authenticates via NEAR AI Cloud API key (option 4),
api_key_login() stores the key via set_runtime_env(). But
build_nearai_model_fetch_config() was using std::env::var() which
doesn't check the runtime overlay — so model listing fell back to
session-token auth and re-triggered the interactive NEAR AI
authentication menu.

Switch to env_or_override() which checks both real env vars and the
runtime overlay.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(agent): correct channel/user_id in bootstrap greeting persist call

persist_assistant_response was called with channel="default",
user_id="system" but the assistant thread was created via
get_or_create_assistant_conversation("default", "gateway") which owns
the conversation as user_id="default", channel="gateway". The mismatch
caused ensure_writable_conversation to reject the write with:

  WARN Rejected write for unavailable thread id user=system channel=default

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(web): remove all inline event handlers for CSP compliance

The Content-Security-Policy header (added in f48fe95) blocks inline JS
via script-src 'self'. All onclick/onchange attributes in index.html
are replaced with getElementById().addEventListener() calls. Dynamic
inline handlers in app.js (jobs, routines, memory breadcrumb, code
blocks, TEE report) are replaced with data-action attributes and a
single delegated click handler on document.

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(agent): align bootstrap message user/channel and update fixture schema field

- Bootstrap IncomingMessage now uses ("default", "gateway") consistently
  with persist and session registration calls
- Update bootstrap_greeting.json fixture: schema_version → version to
  match current PROFILE_JSON_SCHEMA

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: cargo fmt

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(safety): address PR review — expand injection scanning and harden profile sync

- BOOTSTRAP.md: fix target "profile" → "context/profile.json" so the
  write hits the correct path and triggers profile sync
- IDENTITY_FILES: add context/assistant-directives.md to the scanned
  set since it is also injected into the system prompt
- sync_profile_documents(): scan derived USER.md and assistant-directives
  content through Sanitizer before writing, rejecting High/Critical
  injection patterns
- profile_evolution_prompt(): wrap recent_messages_summary in <user_data>
  delimiters with untrusted-data instruction to mitigate indirect
  prompt injection
- routine-advisor skill: update cron examples from 6-field to standard
  5-field format for consistency with routine_create tool docs

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: cargo fmt

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix(setup): detect env-provided LLM keys during quick-mode onboarding

Quick-mode wizard now checks LLM_BACKEND, NEARAI_API_KEY,
ANTHROPIC_API_KEY, and OPENAI_API_KEY env vars to pre-populate
the provider setting, so users aren't re-prompted for credentials
they already supplied. Also teaches setup_nearai() to recognize
NEARAI_API_KEY from env (previously only checked session tokens).

Includes web UI cleanup (remove duplicate event listeners) and
e2e test response count adjustment.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(test): update routine_create_list to expect 7-field normalized cron

The cron normalizer now always expands to 7-field format, so the
stored schedule is "0 0 9 * * * *" not "0 0 9 * * *".

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* feat(setup): skip LLM provider prompts when NEARAI_API_KEY is present

In quick mode, if NEARAI_API_KEY is set in the environment and the
backend was auto-detected as nearai, skip the interactive inference
provider and model selection steps. The API key is persisted to the
secrets store and a default model is set automatically.

Also simplify the static fallback model list for nearai to a single
default entry.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: unify default model, static bootstrap greeting, and web UI cleanup

- Add DEFAULT_MODEL const and default_models() fallback list in
  llm/nearai_chat.rs; use from config, wizard, and .env.example so the
  default model is defined in one place
- Restore multi-model fallback list in setup wizard (was reduced to 1)
- Move BOOTSTRAP_GREETING to module-level const (out of run() body)
- Replace LLM-based bootstrap with static greeting (persist to DB before
  channels start, then broadcast — eliminates startup LLM call and race)
- Fix double env::var read for NEARAI_API_KEY in quick setup path
- Move thread sidebar buttons into threads-section-header (web UI)
- Remove orphaned .thread-sidebar-header CSS and fix double blank line
- Update bootstrap e2e test for static greeting (no LLM trace needed)

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(safety): move prompt injection scanning into Workspace write/append

Addresses PR #927 review comments (#1, #3) — identity file write
protection and unsanitized profile fields in system prompt.

Instead of scanning at the tool layer (memory.rs) or the sync layer
(sync_profile_documents), injection scanning now lives in
Workspace::write() and Workspace::append() for all files that are
injected into the system prompt. This ensures every code path that
writes to these files is protected, including future ones.

- Add SYSTEM_PROMPT_FILES const and reject_if_injected() in workspace
- Add WorkspaceError::InjectionRejected variant
- Add map_write_err() in memory.rs to convert InjectionRejected to
  ToolError::NotAuthorized
- Remove redundant IDENTITY_FILES/Sanitizer from memory.rs
- Remove redundant sanitizer calls from sync_profile_documents()
- Move sanitization tests to workspace::tests
- Existing integration test (test_memory_write_rejects_injection)
  continues to pass through the new path

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style: cargo fmt

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: address Copilot review — merge marker order, orphan thread, stale fixture

- merge_profile_section: search for END marker after BEGIN position to
  avoid matching a stray END earlier in the file
- Bootstrap phase 2: use get_or_create_session + Thread::with_id instead
  of resolve_thread(None) to avoid creating an orphan thread
- setup_nearai: use env_or_override for NEARAI_API_KEY consistency with
  runtime overlay
- Delete orphaned bootstrap_greeting.json fixture (no test references it)
- Add test_merge_end_marker_must_follow_begin regression test

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style: cargo fmt

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style: fmt agent_loop.rs (CI stable rustfmt)

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: lazy-init sanitizer, check profile non-empty before skipping bootstrap

Address Copilot review:
- Use LazyLock<Sanitizer> to avoid rebuilding Aho-Corasick + regexes
  on every workspace write
- has_profile check now requires non-empty content, not just file
  existence, to prevent empty profile.json from suppressing onboarding
- Add seed_tests integration tests (libsql-backed) verifying:
  - Empty profile.json does not suppress BOOTSTRAP.md seeding
  - Non-empty profile.json correctly suppresses bootstrap for upgrades

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style: cargo fmt

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: duplicate language handler, empty LLM_BACKEND, test_rig style

Address Copilot review on PR #927:
- Remove duplicate language-option click listeners (delegated
  data-action handler already covers them)
- Guard LLM_BACKEND env prefill against empty string to prevent
  suppressing API-key-based auto-detection
- Use destructured local `keep_bootstrap` instead of `self.keep_bootstrap`
  in test_rig for consistency after destructure

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: update stale BOOTSTRAP.md write-protection comment [skip-regression-check]

BOOTSTRAP.md is now in SYSTEM_PROMPT_FILES and gets injection scanning
on write. The old comment incorrectly stated it was not write-protected.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: replace debug_assert panics with graceful error returns [skip-regression-check]

debug_assert! in execute_tool_with_safety and JobContext::transition_to
panicked in test builds before the graceful error path could run.
Existing tests (test_cancel_job_completed, test_execute_empty_tool_name_returns_not_found)
already cover these paths — they were the ones failing.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: address Copilot review — schema label, env var check, path normalization, profile validation

1. Label ANALYSIS_FRAMEWORK and PROFILE_JSON_SCHEMA sections separately
   in bootstrap prompt so the LLM knows which blob is the target structure.

2. Wizard quick-mode backend auto-detection now rejects empty env vars
   (std::env::var().is_ok_and(|v| !v.is_empty())) to avoid selecting the
   wrong backend when e.g. NEARAI_API_KEY="" is set.

3. Normalize the target path before comparing with paths::PROFILE in
   memory_write so non-canonical variants like "context//profile.json"
   still trigger profile sync.

4. seed_if_empty now requires valid JSON parse of context/profile.json
   before treating it as a populated profile. Corrupted content no longer
   permanently suppresses bootstrap seeding.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* style: cargo fmt

* fix: address Copilot review — append scan, profile validation, env_or_override

1. Workspace::append() now scans the combined content (existing + new)
   for prompt injection, not just the appended chunk. Prevents split-
   injection evasion across multiple appends.

2. seed_if_empty() now deserializes into PsychographicProfile instead of
   serde_json::Value for profile validation. Stray/legacy JSON that
   doesn't match the expected schema no longer suppresses bootstrap.

3. Wizard quick-mode backend auto-detection now uses env_or_override()
   to honor runtime overlays and injected secrets. LLM_BACKEND value
   is trimmed before storage.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* test: add bootstrap_onboarding_clears_bootstrap E2E trace test

Exercises the full onboarding flow end-to-end:
1. Bootstrap greeting fires automatically on fresh workspace
2. User converses for 3 turns (name, tools, work style)
3. Agent writes psychographic profile to context/profile.json
4. Profile sync generates USER.md and assistant-directives.md
5. Agent writes IDENTITY.md (chosen persona)
6. Agent clears BOOTSTRAP.md via memory_write(target: "bootstrap")

Verifies:
- BOOTSTRAP.md is non-empty before onboarding, empty after
- bootstrap_completed flag is set
- Profile contains expected user data (name, profession, interests)
- USER.md contains profile-derived content (name, tone, profession)
- Assistant-directives.md references user and communication style
- IDENTITY.md contains agent's chosen persona name
- All memory_write calls succeed

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix: address Copilot review — slash collapse, env_or_override, cron trim [skip-regression-check]

1. memory.rs path normalization now uses the same char-by-char loop as
   Workspace::normalize_path() to fully collapse consecutive slashes
   (e.g. "context///profile.json" → "context/profile.json").

2. Quick-mode NEARAI_API_KEY check (line 239) now uses env_or_override()
   consistently with the backend auto-detection block above it.

3. normalize_cron_expression() trims input before field counting so the
   passthrough branch (7+ fields) also strips whitespace.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

---------

Co-authored-by: Jay Zalowitz <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-03-19 22:20:34 -07:00
2026-02-04 22:09:52 -08:00
2026-02-11 08:31:25 +00:00
2026-02-09 03:00:35 +00:00
2026-03-16 21:39:47 -07:00
2026-03-16 21:39:47 -07:00
2026-03-16 21:39:47 -07:00
2026-02-22 19:08:43 +00:00
2026-02-22 19:08:43 +00:00
2026-02-21 15:14:57 -07:00
2026-03-18 11:34:19 -07:00
2026-03-18 11:34:19 -07:00
2026-03-18 11:34:19 -07:00

IronClaw

IronClaw

Your secure personal AI assistant, always on your side

License: MIT OR Apache-2.0 Telegram: @ironclawAI Reddit: r/ironclawAI

English | 简体中文 | Русский | 日本語

PhilosophyFeaturesInstallationConfigurationSecurityArchitecture


Philosophy

IronClaw is built on a simple principle: your AI assistant should work for you, not against you.

In a world where AI systems are increasingly opaque about data handling and aligned with corporate interests, IronClaw takes a different approach:

  • Your data stays yours - All information is stored locally, encrypted, and never leaves your control
  • Transparency by design - Open source, auditable, no hidden telemetry or data harvesting
  • Self-expanding capabilities - Build new tools on the fly without waiting for vendor updates
  • Defense in depth - Multiple security layers protect against prompt injection and data exfiltration

IronClaw is the AI assistant you can actually trust with your personal and professional life.

Features

Security First

  • WASM Sandbox - Untrusted tools run in isolated WebAssembly containers with capability-based permissions
  • Credential Protection - Secrets are never exposed to tools; injected at the host boundary with leak detection
  • Prompt Injection Defense - Pattern detection, content sanitization, and policy enforcement
  • Endpoint Allowlisting - HTTP requests only to explicitly approved hosts and paths

Always Available

  • Multi-channel - REPL, HTTP webhooks, WASM channels (Telegram, Slack), and web gateway
  • Docker Sandbox - Isolated container execution with per-job tokens and orchestrator/worker pattern
  • Web Gateway - Browser UI with real-time SSE/WebSocket streaming
  • Routines - Cron schedules, event triggers, webhook handlers for background automation
  • Heartbeat System - Proactive background execution for monitoring and maintenance tasks
  • Parallel Jobs - Handle multiple requests concurrently with isolated contexts
  • Self-repair - Automatic detection and recovery of stuck operations

Self-Expanding

  • Dynamic Tool Building - Describe what you need, and IronClaw builds it as a WASM tool
  • MCP Protocol - Connect to Model Context Protocol servers for additional capabilities
  • Plugin Architecture - Drop in new WASM tools and channels without restarting

Persistent Memory

  • Hybrid Search - Full-text + vector search using Reciprocal Rank Fusion
  • Workspace Filesystem - Flexible path-based storage for notes, logs, and context
  • Identity Files - Maintain consistent personality and preferences across sessions

Installation

Prerequisites

  • Rust 1.85+
  • PostgreSQL 15+ with pgvector extension
  • NEAR AI account (authentication handled via setup wizard)

Download or Build

Visit Releases page to see the latest updates.

Install via Windows Installer (Windows)

Download the Windows Installer and run it.

Install via powershell script (Windows)
irm https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.ps1 | iex
Install via shell script (macOS, Linux, Windows/WSL)
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.sh | sh
Install via Homebrew (macOS/Linux)
brew install ironclaw
Compile the source code (Cargo on Windows, Linux, macOS)

Install it with cargo, just make sure you have Rust installed on your computer.

# Clone the repository
git clone https://github.com/nearai/ironclaw.git
cd ironclaw

# Build
cargo build --release

# Run tests
cargo test

For full release (after modifying channel sources), run ./scripts/build-all.sh to rebuild channels first.

Database Setup

# Create database
createdb ironclaw

# Enable pgvector
psql ironclaw -c "CREATE EXTENSION IF NOT EXISTS vector;"

Configuration

Run the setup wizard to configure IronClaw:

ironclaw onboard

The wizard handles database connection, NEAR AI authentication (via browser OAuth), and secrets encryption (using your system keychain). Settings are persisted in the connected database; bootstrap variables (e.g. DATABASE_URL, LLM_BACKEND) are written to ~/.ironclaw/.env so they are available before the database connects.

Alternative LLM Providers

IronClaw defaults to NEAR AI but supports many LLM providers out of the box. Built-in providers include Anthropic, OpenAI, Google Gemini, MiniMax, Mistral, and Ollama (local). OpenAI-compatible services like OpenRouter (300+ models), Together AI, Fireworks AI, and self-hosted servers (vLLM, LiteLLM) are also supported.

Select your provider in the wizard, or set environment variables directly:

# Example: MiniMax (built-in, 204K context)
LLM_BACKEND=minimax
MINIMAX_API_KEY=...

# Example: OpenAI-compatible endpoint
LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_API_KEY=sk-or-...
LLM_MODEL=anthropic/claude-sonnet-4

See docs/LLM_PROVIDERS.md for a full provider guide.

Security

IronClaw implements defense in depth to protect your data and prevent misuse.

WASM Sandbox

All untrusted tools run in isolated WebAssembly containers:

  • Capability-based permissions - Explicit opt-in for HTTP, secrets, tool invocation
  • Endpoint allowlisting - HTTP requests only to approved hosts/paths
  • Credential injection - Secrets injected at host boundary, never exposed to WASM code
  • Leak detection - Scans requests and responses for secret exfiltration attempts
  • Rate limiting - Per-tool request limits to prevent abuse
  • Resource limits - Memory, CPU, and execution time constraints
WASM ──► Allowlist ──► Leak Scan ──► Credential ──► Execute ──► Leak Scan ──► WASM
         Validator     (request)     Injector       Request     (response)

Prompt Injection Defense

External content passes through multiple security layers:

  • Pattern-based detection of injection attempts
  • Content sanitization and escaping
  • Policy rules with severity levels (Block/Warn/Review/Sanitize)
  • Tool output wrapping for safe LLM context injection

Data Protection

  • All data stored locally in your PostgreSQL database
  • Secrets encrypted with AES-256-GCM
  • No telemetry, analytics, or data sharing
  • Full audit log of all tool executions

Architecture

┌────────────────────────────────────────────────────────────────┐
│                          Channels                              │
│  ┌──────┐  ┌──────┐   ┌─────────────┐  ┌─────────────┐         │
│  │ REPL │  │ HTTP │   │WASM Channels│  │ Web Gateway │         │
│  └──┬───┘  └──┬───┘   └──────┬──────┘  │ (SSE + WS)  │         │
│     │         │              │         └──────┬──────┘         │
│     └─────────┴──────────────┴────────────────┘                │
│                              │                                 │
│                    ┌─────────▼─────────┐                       │
│                    │    Agent Loop     │  Intent routing       │
│                    └────┬──────────┬───┘                       │
│                         │          │                           │
│              ┌──────────▼────┐  ┌──▼───────────────┐           │
│              │  Scheduler    │  │ Routines Engine  │           │
│              │(parallel jobs)│  │(cron, event, wh) │           │
│              └──────┬────────┘  └────────┬─────────┘           │
│                     │                    │                     │
│       ┌─────────────┼────────────────────┘                     │
│       │             │                                          │
│   ┌───▼─────┐  ┌────▼────────────────┐                         │
│   │ Local   │  │    Orchestrator     │                         │
│   │Workers  │  │  ┌───────────────┐  │                         │
│   │(in-proc)│  │  │ Docker Sandbox│  │                         │
│   └───┬─────┘  │  │   Containers  │  │                         │
│       │        │  │ ┌───────────┐ │  │                         │
│       │        │  │ │Worker / CC│ │  │                         │
│       │        │  │ └───────────┘ │  │                         │
│       │        │  └───────────────┘  │                         │
│       │        └─────────┬───────────┘                         │
│       └──────────────────┤                                     │
│                          │                                     │
│              ┌───────────▼──────────┐                          │
│              │    Tool Registry     │                          │
│              │  Built-in, MCP, WASM │                          │
│              └──────────────────────┘                          │
└────────────────────────────────────────────────────────────────┘

Core Components

Component Purpose
Agent Loop Main message handling and job coordination
Router Classifies user intent (command, query, task)
Scheduler Manages parallel job execution with priorities
Worker Executes jobs with LLM reasoning and tool calls
Orchestrator Container lifecycle, LLM proxying, per-job auth
Web Gateway Browser UI with chat, memory, jobs, logs, extensions, routines
Routines Engine Scheduled (cron) and reactive (event, webhook) background tasks
Workspace Persistent memory with hybrid search
Safety Layer Prompt injection defense and content sanitization

Usage

# First-time setup (configures database, auth, etc.)
ironclaw onboard

# Start interactive REPL
cargo run

# With debug logging
RUST_LOG=ironclaw=debug cargo run

Development

# Format code
cargo fmt

# Lint
cargo clippy --all --benches --tests --examples --all-features

# Run tests
createdb ironclaw_test
cargo test

# Run specific test
cargo test test_name
  • Telegram channel: See docs/TELEGRAM_SETUP.md for setup and DM pairing.
  • Changing channel sources: Run ./channels-src/telegram/build.sh before cargo build so the updated WASM is bundled.

OpenClaw Heritage

IronClaw is a Rust reimplementation inspired by OpenClaw. See FEATURE_PARITY.md for the complete tracking matrix.

Key differences:

  • Rust vs TypeScript - Native performance, memory safety, single binary
  • WASM sandbox vs Docker - Lightweight, capability-based security
  • PostgreSQL vs SQLite - Production-ready persistence
  • Security-first design - Multiple defense layers, credential protection

License

Licensed under either of:

at your option.

S
Description
IronClaw is OpenClaw inspired implementation in Rust focused on privacy and security
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