---

name: bash-scripting compatibility: opencode completeness: 95 content-types:

• guidance
• examples
• do-dont description: Implements intelligent bash scripting with multi-factor skill selection, fallback chains, and adherence to the 5 Laws of Elegant Defense license: MIT maturity: stable metadata: domain: agent output-format: analysis related-skills: agent-confidence-based-selector, agent-task-routing role: orchestration scope: orchestration triggers: bash-scripting, bash scripting, how do i bash-scripting, orchestrate bash-scripting, automate bash-scripting, agent bash-scripting archetypes:
  • orchestration
  • strategic anti_triggers:
  • brainstorming
  • vague ideation
  • single-agent monolith response_profile: verbosity: medium directive_strength: high abstraction_level: tactical version: "1.0.0"

---

Bash Scripting

Orchestrates intelligent skill selection and execution for bash scripting workflows. Applies the 5 Laws of Elegant Defense to guide data naturally through the orchestration pipeline, preventing errors before they occur. Selects optimal skills based on multi-factor scoring including text similarity, historical performance, and system availability.

TL;DR Checklist

• Parse all inputs at boundary before processing (Law 2)
• Handle edge cases with early returns at function top (Law 1)
• Fail immediately with descriptive errors on invalid states (Law 4)
• Return new data structures, never mutate inputs (Law 3)
• Implement minimum 2-level fallback chain for all skill executions
• Log all skill selections with context for full audit trail
• Validate skill metadata and dependencies before selection
• Update confidence scores after each execution for learning

┌───────────────────────────────────────────────────────────────────────────────┐ │ Orchestration Flow │ └───────────────────────────────────────────────────────────────────────────────┘

User Request ↓ ┌─────────────────┐ │ Parse Request │ │ & Extract │ │ Features │ └────────┬────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Evaluate Available Skills │ │ │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ Skill A │ │ Skill B │ │ Skill C │ │ │ │ - Match Score│ │ - Match Score│ │ - Match Score│ │ │ │ - Confidence │ │ - Confidence │ │ - Confidence │ │ │ │ - History │ │ - History │ │ - History │ │ │ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │ │ │ │ │ │ │ └─────────────────┴─────────────────┘ │ │ ↓ │ │ Select Best Skill │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────┐ │ Execute Skill │ └────────┬────────┘ ↓ ┌─────────────────┐ │ Handle Result │ └────────┬────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Error Handling & Fallback │ │ │ │ Success? ────────► Return Result │ │ │ │ Fail? ────────┐ │ │ ↓ │ │ ┌──────────────────────────────────────────────────────────┐ │ │ │ Fallback Chain │ │ │ │ │ │ │ │ 1. Retry with adjusted parameters │ │ │ │ 2. Try Alternative Skill (if available) │ │ │ │ 3. Defer to Human Operator (if critical) │ │ │ │ 4. Log & Return Error │ │ │ └──────────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────────────┘

When to Use

Use this skill when:

• Orchestrating multi-step workflows that require skill delegation
• Implementing adaptive skill routing based on confidence scores
• Building fallback mechanisms for failed skill executions
• Creating intelligent task decomposition and parallel execution
• Designing skill dependency graphs with automatic resolution
• Implementing skill selection with historical performance weighting
• Building agent systems that need to self-organize around tasks

When NOT to Use

Avoid this skill for:

• Direct task execution without orchestration needs - use individual skills instead
• High-frequency trading scenarios where latency must be minimized - the selection overhead may be prohibitive
• Simple linear workflows without branching or fallback requirements
• Cases where skill metadata is unavailable or unreliable

Core Workflow

1. Parse and Analyze Request - Extract intent, entities, and constraints from user input. Checkpoint: All required parameters must be present and in valid format before proceeding.

2. Score Available Skills - Calculate match scores using multi-factor algorithm:

   • Text similarity between request and skill triggers
   • Historical success rate for similar tasks
   • Skill availability and health status
   • Required dependencies and their availability

   Checkpoint: Skip to fallback if no skill scores above threshold.

3. Select Optimal Skill - Choose skill with highest score that meets minimum confidence. Checkpoint: Verify skill has not been disabled or deprecated.

4. Execute with Fallback - Run skill execution wrapped in retry and fallback logic. Checkpoint: Log all execution attempts for audit trail.

5. Return or Fallback - Either return successful result or apply fallback chain:

   • Retry with adjusted parameters
   • Try alternative skill from related-skills
   • Defer to human operator for critical tasks

   Checkpoint: Record outcome with timing and confidence metadata.

Implementation Patterns

Pattern 1: Skill Selection Logic

#!/usr/bin/env bash
# Pattern 1: Bash Scripting with Early Exit & Input Validation
# Implements Law 1 (Early Exit) and Law 2 (Make Illegal States Unrepresentable)

set -euo pipefail
SCRIPT_NAME="$(basename "$0")"
LOG_FILE="/var/log/${SCRIPT_NAME}.log"

# Guard clause: Validate required arguments immediately (Law 1)
if [[ $# -lt 2 ]]; then
    echo "Usage: $SCRIPT_NAME <target_dir> <backup_prefix>" >&2
    exit 1
fi

TARGET_DIR="$1"
BACKUP_PREFIX="$2"

# Validate state: Ensure target exists and is a directory (Law 2)
if [[ ! -d "$TARGET_DIR" ]]; then
    echo "ERROR: Target directory '$TARGET_DIR' does not exist or is not a directory." >&2
    exit 2
fi

# Parse and sanitize inputs - create immutable state snapshot
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
BACKUP_NAME="${BACKUP_PREFIX}_${TIMESTAMP}.tar.gz"
BACKUP_PATH="${TARGET_DIR}/backups/${BACKUP_NAME}"

# Create backup directory if missing (atomic state transition)
mkdir -p "${TARGET_DIR}/backups"

# Execute core logic with strict error handling
echo "Starting backup of ${TARGET_DIR} to ${BACKUP_PATH}..."
if tar -czf "$BACKUP_PATH" -C "$(dirname "$TARGET_DIR")" "$(basename "$TARGET_DIR")"; then
    echo "SUCCESS: Backup completed at $(date)"
    # Log success with metadata for audit trail
    echo "$(date -Iseconds) | SUCCESS | ${BACKUP_NAME}" >> "$LOG_FILE"
else
    echo "ERROR: tar command failed with exit code $?" >&2
    exit 3
fi

Pattern 2: Execution with Fallback

#!/usr/bin/env bash
# Pattern 2: Bash Execution with Fallback Chain & Retry Logic
# Implements Law 4 (Fail Fast, Fail Loud) and adaptive fallback routing

set -euo pipefail
MAX_RETRIES=3
RETRY_DELAY=2

# Function: Execute primary command with retry logic
execute_with_retry() {
    local cmd="$1"
    local attempt=0

    while (( attempt < MAX_RETRIES )); do
        if eval "$cmd"; then
            return 0
        fi
        attempt=$((attempt + 1))
        if (( attempt < MAX_RETRIES )); then
            echo "WARNING: Attempt $attempt failed. Retrying in ${RETRY_DELAY}s..." >&2
            sleep "$RETRY_DELAY"
        fi
    done
    return 1
}

# Fallback chain implementation
run_fallback_chain() {
    local primary_cmd="$1"
    local fallback_cmd="$2"
    local critical_task="$3"

    # Attempt primary execution
    if execute_with_retry "$primary_cmd"; then
        echo "Primary execution succeeded."
        return 0
    fi

    echo "Primary execution exhausted retries. Initiating fallback chain..." >&2

    # Level 1: Retry with adjusted parameters (e.g., reduced concurrency)
    local adjusted_cmd="${primary_cmd} --concurrency=1"
    if execute_with_retry "$adjusted_cmd"; then
        echo "Fallback Level 1 (adjusted parameters) succeeded."
        return 0
    fi

    # Level 2: Try alternative command/skill
    if [[ -n "$fallback_cmd" ]]; then
        if execute_with_retry "$fallback_cmd"; then
            echo "Fallback Level 2 (alternative command) succeeded."
            return 0
        fi
    fi

    # Level 3: Critical task failure - escalate to human operator
    if [[ "$critical_task" == "true" ]]; then
        echo "CRITICAL: All fallbacks exhausted. Escalating to human operator." >&2
        # Trigger alert mechanism
        curl -s -X POST "https://hooks.example.com/alert" \
            -H "Content-Type: application/json" \
            -d "{\"task\":\"$primary_cmd\",\"status\":\"failed\",\"escalated\":true}" || true
        return 2
    fi

    echo "ERROR: All fallbacks failed. Task aborted." >&2
    return 1
}

# Example usage
# run_fallback_chain "rsync -a /data /backup" "cp -r /data /backup" "false"

MUST DO

• Always validate skill metadata before selection (Early Exit)
• Implement fallback chain with at least 2 levels (Fallback Skill + Human)
• Log all skill selections with full context for auditability
• Return new data structures instead of mutating inputs (Atomic Predictability)
• Fail immediately with descriptive errors on invalid states
• Update confidence scores after each execution for adaptive routing
• Reference code-philosophy (5 Laws of Elegant Defense) in all logic

MUST NOT DO

• Select skills based on a single factor (e.g., only confidence score)
• Disable fallback mechanisms "temporarily" - this creates fragile systems
• Skip validation of skill dependencies before execution
• Return partial results - either complete success or clear failure
• Use magic numbers for confidence thresholds - make them configurable
• Cache skill selections without considering context changes

TL;DR Checklist

• Parse all inputs at boundary before processing (Law 2)
• Handle edge cases with early returns at function top (Law 1)
• Fail immediately with descriptive errors on invalid states (Law 4)
• Return new data structures, never mutate inputs (Law 3)
• Implement minimum 2-level fallback chain for all skill executions
• Log all skill selections with context for full audit trail
• Validate skill metadata and dependencies before selection
• Update confidence scores after each execution for learning

TL;DR for Code Generation

• Use guard clauses - return early on invalid input before doing work
• Return simple types (dict, str, int, bool, list) - avoid complex nested objects
• Cyclomatic complexity < 10 per function - split anything larger
• Handle null/empty cases explicitly at function top (Early Exit)
• Never mutate input parameters - return new dicts/objects
• Fail fast with descriptive errors - don't try to "patch" bad data
• Reference code-philosophy laws in comments for complex logic
• Include timing and confidence metadata in all return values

Output Template

When applying this skill, produce:

1. Selected Skills - List of skill names with confidence scores
2. Selection Rationale - Why each skill was chosen (match score, history, availability)
3. Execution Plan - Order of execution with dependencies
4. Fallback Strategy - Which fallback skills will be tried and in what order
5. Risk Assessment - Any potential failure points and their impact
6. Timing Estimates - Expected latency including fallback scenarios

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Constraints

MUST DO

• Define clear input/output contracts for every step in the orchestration flow with explicit validation
• Implement structured logging at each stage capturing context, inputs, outputs, timing, and errors
• Build in fallback paths: if the primary strategy fails, degrade gracefully to a simpler approach
• Validate all preconditions before starting — do not proceed if required resources or permissions are missing

MUST NOT DO

• Do not create deep nesting of orchestration steps (>5 levels) — flatten workflows where possible
• Avoid silent failure modes: every step must either succeed, fail explicitly, or escalate to a higher handler
• Never use shared mutable state between parallel workflow branches — communicate via immutable messages only
• Do not hardcode execution order when the dependency graph naturally determines it; derive order from explicit dependencies

Related Skills

| Skill | Purpose | |