intelligent-do

name	intelligent-do
description	Context-aware task execution with Serena MCP backend. First time: Explores project, saves to Serena, runs spec if complex, executes waves. Returning: Loads from Serena (<1s), detects changes, executes with cached context. Intelligently decides when to research, when to spec, when to prime. One catch-all intelligent execution command. Use when: User wants task executed in any project (new or existing).
skill-type	PROTOCOL
shannon-version	>=5.0.0
complexity-triggers	["0.00-1.00"]
invoked-by-commands	["/shannon:do"]
related-commands	[{"/shannon:exec":"Structured execution with library discovery + validation"},{"/shannon:task":"Meta-command that orchestrates prime→spec→wave"},{"/shannon:wave":"Direct wave execution for parallel work"}]
command-orchestration	This skill is invoked by /shannon:do, which is the RECOMMENDED default for general task execution. WHEN TO USE /shannon:do (this skill): - General task execution in any project - Auto-detection of complexity, research needs, context - Both new and existing projects - Simple to complex tasks WHEN TO USE ALTERNATIVES: - /shannon:exec: When you want explicit library discovery + 3-tier validation + git commits - /shannon:task: When you want full automation (prime→spec→wave) from specification - /shannon:wave: When you already have spec analysis and just need parallel execution See docs/COMMAND_ORCHESTRATION.md for complete decision trees.
mcp-requirements	{"required":[{"name":"serena","version":">=2.0.0","purpose":"Persistent context backend for project memory","fallback":"ERROR - Cannot operate without Serena","degradation":"critical"}],"recommended":[{"name":"sequential","purpose":"Deep analysis for complex decisions"},{"name":"context7","purpose":"Framework documentation lookup"},{"name":"tavily","purpose":"Library and best practice research"}]}
required-sub-skills	["wave-orchestration","memory-coordination"]
optional-sub-skills	["spec-analysis","mcp-discovery","goal-management","context-preservation"]
allowed-tools	["Read","Write","Bash","TodoWrite","AskUserQuestion","Serena","SlashCommand","Sequential","Context7","Tavily"]

Intelligent Do

Purpose

Comprehensive intelligent task execution that automatically handles all scenarios: new projects, existing codebases, simple tasks, complex requirements, first-time work, and returning workflows - all with Serena MCP as the persistent context backend.

Core Innovation: One command that adapts to any scenario without configuration, learns from every execution, and gets faster on return visits.

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Workflow

Step 1: Context Detection Using Serena

Check if project exists in Serena memory:

1. Determine project ID from current working directory:

   • Get current path: Use Bash tool to run pwd
   • Extract project name: Last component of path
   • Sanitize for memory key: Replace special characters with underscores

2. Check Serena for existing project memory:

   • Use Serena tool: list_memories()
   • Search for key: "shannon_project_{project_id}"
   • If key found → RETURNING_WORKFLOW
   • If key not found → FIRST_TIME_WORKFLOW

Duration: < 1 second

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Step 2a: FIRST_TIME_WORKFLOW

For projects not yet in Serena:

Sub-Step 1: Determine Project Type

Count files in current directory to determine if new or existing project:

# Use Bash tool
find . -type f \( -name "*.py" -o -name "*.js" -o -name "*.tsx" -o -name "*.java" -o -name "*.go" \) | wc -l

• If count < 3: NEW_PROJECT (greenfield)
• If count >= 3: EXISTING_PROJECT (has codebase)

Sub-Step 2: NEW_PROJECT Path

For greenfield projects (empty or minimal files):

1. Assess Task Complexity:

   • Count words in task description
   • Count requirements (lines starting with -)
   • If task has 20+ words OR 3+ requirements → Complex task
   • If task mentions "system", "platform", "integrate" → Complex task

2. For Complex Tasks - Run Spec Analysis: