mcp-code-execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

Jump to install

Repository: athola/claude-night-market
Last source activity: June 22, 2026 at 15:44
Detected SKILL.md language: English
Stars: 327
Forks: 35

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/athola/claude-night-market --skill mcp-code-execution

The command stays on one line. Scroll horizontally to inspect it before copying.

Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer

5 files

SKILL.md

Source instructions · Read-only preview

Back to search Back to installation

Skill(conserve:mcp-code-execution)

def classify_workflow_for_mecw(workflow):
    """Determine appropriate MCP modules and MECW strategy"""

    if has_tool_chains(workflow) and workflow.complexity == 'high':
        return {
            'modules': ['mcp-subagents', 'mcp-patterns'],
            'mecw_strategy': 'aggressive',
            'token_budget': 600
        }
    elif workflow.data_size > '10k_rows':
        return {
            'modules': ['mcp-patterns', 'mcp-validation'],
            'mecw_strategy': 'moderate',
            'token_budget': 400
        }
    else:
        return {
            'modules': ['mcp-patterns'],
            'mecw_strategy': 'conservative',
            'token_budget': 200
        }

def delegate_mecw_assessment(workflow):
    return mcp_validation_assess_mecw_risk(
        workflow,
        hub_allocated_tokens=self.token_budget * 0.5
    )

class MCPExecutionHub:
    def __init__(self):
        self.modules = {
            'mcp-subagents': MCPSubagentsModule(),
            'mcp-patterns': MCPatternsModule(),
            'mcp-validation': MCPValidationModule()
        }

    def execute_workflow(self, workflow, classification):
        results = []

        # Execute modules in optimal order
        for module_name in classification['modules']:
            module = self.modules[module_name]
            result = module.execute(
                workflow,
                mecw_budget=classification['token_budget'] //
                len(classification['modules'])
            )
            results.append(result)

        return self.synthesize_results(results)

def synthesize_module_results(module_results):
    """Combine module results into a single status dict."""

    return {
        'status': 'completed',
        'token_savings': calculate_savings(module_results),
        'mecw_compliance': verify_mecw_rules(module_results),
        'hallucination_risk': assess_hallucination_prevention(module_results),
        'results': consolidate_results(module_results)
    }

name	mcp-code-execution
description	Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
alwaysApply	false
progressive_loading	true
dependencies	{"hub":["context-optimization","token-conservation"],"modules":["mcp-subagents","mcp-patterns","mcp-validation"]}
model_hint	standard

name	mcp-code-execution
description	Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
alwaysApply	false
progressive_loading	true
dependencies	{"hub":["context-optimization","token-conservation"],"modules":["mcp-subagents","mcp-patterns","mcp-validation"]}
model_hint	standard

mcp-code-execution

Install options

Review the source files

Table of Contents

Table of Contents