FF-Terminal Platform - 43 Tools for Enterprise AI

FF-Terminal runs 5,000+ tool operations per session, operates autonomously for 10+ hours, and achieves 94% task success through dual orchestration: simple parallel execution (90% of tasks) and hierarchical planning (10% of tasks).

Platform Overview

FF-Terminal runs autonomously for hours without human oversight through SQLite-backed state persistence and checkpoint-based recovery. When tasks fail, the system retries with corrections. When sessions crash, they resume from the last checkpoint.

Built on 43 core tools spanning file operations, code analysis, web search, media generation, and system control. Tools use natural language interfaces with maximum 3 parameters for simplicity.

Key Platform Capabilities

5,000+ Tool Capacity: Executes thousands of tool operations per session through parallel orchestration
10+ Hour Autonomy: Runs continuously through SQLite state machine and automatic checkpointing
94% Success Rate: Measured across manufacturing, healthcare, finance, and logistics deployments
8 AI Providers: OpenAI, OpenRouter, Groq, Ollama, LiteLLM, LM Studio, Z.ai, MiniMax
25+ Skills: Pre-built workflows for PDF generation, web artifacts, data analysis, etc.

43 Core Tools

File operations, code search, web interactions, media generation, and system control. Each tool uses natural language with max 3 parameters. All inherit from BaseTool class with standardized error handling and validation.

File I/O Tools

read_file

Read files with size limits, lazy loading, and format detection (text, images, PDFs, notebooks)

write_file

Create or overwrite files with safety checks and permission validation

edit_file

Precise string replacement edits with uniqueness validation

multi_edit_file

Batch edits across multiple locations in a single operation

glob

Fast file pattern matching with recursive directory search

grep

Powerful regex search across codebase with context lines

Execution Tools

run_command

Execute shell commands with sandboxing, timeouts, and output capture

Code Search & Analysis

search_code

Full-text semantic code search across entire codebase

semantic_search

AI-powered code understanding and similarity search

ast_grep

Structured code queries using abstract syntax trees

Skills System Tools

skill_loader

Discover and load available skills from skill directories

skill_documentation

Retrieve detailed skill specifications and usage guides

skill_import

Import external skill definitions into runtime

skill_draft

Create new skill templates with validation

skill_apply

Execute skills with parameter binding and error handling

skill_sequencer

Chain multiple skills into complex workflows

Web Tools

tavily_search

Comprehensive web search with relevance ranking

tavily_extract

Extract structured data from web pages

tavily_map

Map website structure and navigation paths

tavily_crawl

Deep crawl websites with rate limiting and respect for robots.txt

perplexity_search

Alternative search provider with AI summarization

browse_web

Lightweight URL fetching and content extraction

Data & Analysis

analyze_data

Statistical analysis, data processing, and insights generation

notebook_edit

Manipulate Jupyter notebooks programmatically

Media Generation

generate_image_gemini

Create images using Google Gemini models

analyze_image_gemini

Extract information and insights from images

edit_image_gemini

Modify existing images with AI-guided edits

generate_image_openai

Image generation via OpenAI DALL-E

analyze_image_openai

Vision analysis with GPT-4 Vision

generate_video_gemini

Create video content from prompts

analyze_video_gemini

Extract insights from video content

Automation & Control

macos_control

Control macOS system functions (Dock, Finder, applications)

workflow_automation

Define and execute complex task automation sequences

ask_oracle

Delegate complex decisions to specialized AI agents

System Tools

schedule_task

Create recurring tasks with cron-like scheduling

list_templates

Browse available project templates

project_template

Apply templates to bootstrap new projects

smart_cleanup

Intelligent code cleanup and optimization

Meta & Planning

think

Extended reasoning and problem decomposition

session_summary

Generate conversation summaries for long sessions

quick_update

Send status updates to users during execution

manage_task

Create and track todo lists for complex workflows

completion_validation

Validate tool promises were fulfilled correctly

Dual Orchestration Architecture

Two orchestration modes handle different task types. Simple orchestrator (90% of tasks) executes in parallel with 3-8 second response times. Hierarchical wrapper (10% of tasks) coordinates sequential steps with dependencies through master-agent planning.

Simple Orchestrator (90% of Tasks)

Fire-and-forget parallel execution. Creates fresh model instances per sub-agent, executes concurrently, aggregates results. Average 5.2 second response, 94% success rate, 3.2x speedup vs sequential execution.

Hierarchical Wrapper (10% of Tasks)

Sequential execution with state. Master agent plans steps, executes each with accumulated context, saves checkpoints after every operation. Used for multi-file refactoring, database migrations, long-running data pipelines.

Mode Selection

Simple mode triggers on: Single-step requests, independent tasks, no dependencies
Hierarchical mode triggers on: Multi-step with dependencies, conditional logic, long duration keywords
Complexity scoring: Analyzes keywords ("first", "then", "if", "unless") to calculate 0-1 score, threshold at 0.4
Automatic recovery: Both modes retry failed tool calls, hierarchical adds checkpointing for resume

8 AI Provider Integration

Unified ModelProvider interface supports OpenAI, OpenRouter, Groq, Ollama, LiteLLM, LM Studio, Z.ai, and MiniMax. All implement same chat_completion() method. Switch providers via environment variable without code changes.

Supported Providers

OpenAI

GPT-4, GPT-4 Turbo, GPT-3.5 for general-purpose tasks, code generation, and reasoning

Anthropic

Claude Opus, Sonnet, Haiku for complex analysis, long-context processing, and safe outputs

Google

Gemini Pro, Ultra for multimodal tasks, search integration, and data analysis

DeepSeek

Specialized code models for software engineering tasks and technical documentation

OpenRouter

Access to 100+ models through unified API with automatic failover

Z.ai

Chinese AI providers for global deployment and multilingual support

MiniMax

Efficient models for high-throughput, cost-sensitive applications

LM Studio (Local)

Run models locally for air-gapped environments and maximum data privacy

Skills System

On-demand loadable behaviors that extend agent capabilities without bloating the core system. Each skill is a directory with SKILL.md (instructions), tools.json (configurations), and optional examples. Currently includes 25+ skills for documents, web artifacts, art generation, and more.

Available Skills

Document Skills: PDF, DOCX, XLSX, PPTX generation with templates
Development Skills: MCP server creation, web artifacts, code-first responder
Design Skills: Award-winning designer, dashboard design, frontend design
Creative Skills: Algorithmic art, theme factory, Slack GIF creator
Research Skills: Rapid research, satellite OSINT

Skill Loading

Use skill_loader to discover available skills, skill_documentation to read specifications, skill_sequencer to chain multiple skills. Skills load SKILL.md content into agent context on-demand, keeping base system message small.

Completion Validation System

176+ NLP patterns detect when the AI promises to do something but doesn't execute the tool. Extracts promises from agent responses, matches against actual tool executions, calculates fulfillment rate. Triggers re-engagement if completion status is INCOMPLETE.

Pattern Types

TOOL_EXECUTION: "I'll run X", "Executing X", "Let me call X"
FILE_OPERATION: "I'll read/write/edit file Y"
ANALYSIS: "I'll analyze/examine/check Z"
CREATION: "I'll create/generate/build W"
MODIFICATION: "I'll update/modify/change V"

Validation Thresholds

COMPLETE: 100% of promises fulfilled
PARTIAL: 50-99% fulfilled, continues with warning
INCOMPLETE: <50% fulfilled, triggers re-engagement
Detection accuracy: 85% promise extraction, 92% fulfillment tracking

Integration & Deployment

FF-Terminal integrates seamlessly into existing enterprise infrastructure with flexible deployment options and comprehensive API access.

Deployment Options

Cloud: Managed deployment on AWS, GCP, or Azure with auto-scaling
On-Premises: Full control with private cloud or data center deployment
Hybrid: Mix cloud and on-prem for sensitive workloads
Edge: Deploy to Raspberry Pi or edge devices for IoT integration

Enterprise Features

SSO integration (SAML, OAuth, Active Directory)
Role-based access control (RBAC)
Audit logging and compliance reporting
API rate limiting and quota management
Multi-tenancy with data isolation
24/7 enterprise support with SLA guarantees

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