skills-not-mcp

mcp
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SUMMARY

80-90% token savings with Skills+ shell vs MCP

README.md
terminal skills mcp

skills-not-mcp

80-90% fewer tokens with Skills(/) + shell vs MCP

Github


Table of Contents

    About
    Conversion
    Pattern
    How to build
    Usage
    Tools
    Contact

About

80-90% token savings by replacing MCP with Skills + Shell scripts.

18 MCP tools from pal-mcp-server converted to:

  • Claude Skills (commands/*.md) - slash command interface
  • Shell scripts (scripts/*.sh) - actual execution
approach tokens loaded savings
MCP (18 tools) ~12,500 always baseline
Skills + Shell ~50 per call 80-90%

MCP loads all 18 tool schemas (~700 tokens each) into context whether you use them or not.

Skills + Shell loads nothing until called - then only the output.

Conversion Table

# MCP (before) Skill (after) Shell (after)
1tools/chat.pycommands/chat.mdscripts/chat.sh
2tools/thinkdeep.pycommands/thinkdeep.mdscripts/thinkdeep.sh
3tools/consensus.pycommands/consensus.mdscripts/consensus.sh
4tools/codereview.pycommands/codereview.mdscripts/codereview.sh
5tools/debug.pycommands/debug.mdscripts/debug.sh
6tools/planner.pycommands/planner.mdscripts/planner.sh
7tools/analyze.pycommands/analyze.mdscripts/analyze.sh
8tools/refactor.pycommands/refactor.mdscripts/refactor.sh
9tools/testgen.pycommands/testgen.mdscripts/testgen.sh
10tools/secaudit.pycommands/secaudit.mdscripts/secaudit.sh
11tools/docgen.pycommands/docgen.mdscripts/docgen.sh
12tools/apilookup.pycommands/apilookup.mdscripts/apilookup.sh
13tools/challenge.pycommands/challenge.mdscripts/challenge.sh
14tools/tracer.pycommands/tracer.mdscripts/tracer.sh
15tools/clink.pycommands/clink.mdscripts/clink.sh
16tools/precommit.pycommands/precommit.mdscripts/precommit.sh
17tools/listmodels.pycommands/listmodels.mdscripts/listmodels.sh
18tools/version.pycommands/version.mdscripts/version.sh

Source: pal-mcp-server

Pattern

Deterministic Delegation - Skills orchestrate, Shell executes

┌─────────────────────────────────────────────────────────────┐
│                    MCP APPROACH                             │
│                                                             │
│  ┌────────┐ ┌────────┐ ┌────────┐ ┌────────┐              │
│  │ tool 1 │ │ tool 2 │ │ tool 3 │ │ ...18  │              │
│  │ ~700   │ │ ~700   │ │ ~700   │ │ tokens │              │
│  └────────┘ └────────┘ └────────┘ └────────┘              │
│                                                             │
│  COST: ~12,500 tokens ALWAYS LOADED                        │
│  SAVINGS: 0%                                                │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│            SKILLS + SHELL (Deterministic Delegation)        │
│                                                             │
│  ┌────────┐                                                 │
│  │ /skill │ ────> shell script ────> output                │
│  │ ~50 tok│       (external)         (only this)           │
│  └────────┘                                                 │
│                                                             │
│  COST: ~50 tokens + output only                            │
│  SAVINGS: 80-90%                                            │
└─────────────────────────────────────────────────────────────┘

flow:

USER                    AI                      SHELL
 │                       │                        │
 │  "/chat review this"  │                        │
 │ ───────────────────>  │                        │
 │                       │  exec chat.sh          │
 │                       │ ────────────────────>  │
 │                       │                        │
 │                       │      ┌─────────────────┤
 │                       │      │ - parse args    │
 │                       │      │ - detect model  │
 │                       │      │ - call API      │
 │                       │      │ - format output │
 │                       │      └─────────────────┤
 │                       │                        │
 │                       │  JSON result           │
 │                       │ <────────────────────  │
 │                       │                        │
 │  formatted response   │                        │
 │ <───────────────────  │                        │

layers:

┌────────────────────────────────────────────────┐
│  LAYER 1: SKILL (orchestrator)                 │
│  commands/*.md                                 │
│  - slash commands, routing, ~50 tokens each    │
└────────────────────────────────────────────────┘
                    │ delegates to
                    ▼
┌────────────────────────────────────────────────┐
│  LAYER 2: SHELL (execution)                    │
│  scripts/*.sh                                  │
│  - actual logic, 0 tokens til called           │
└────────────────────────────────────────────────┘
                    │ calls
                    ▼
┌────────────────────────────────────────────────┐
│  LAYER 3: PROVIDER (external)                  │
│  Anthropic / OpenAI / Ollama / etc             │
└────────────────────────────────────────────────┘
property MCP Skills + Shell
schema loading always (~12.5k) never
token savings 0% 80-90%
execution probabilistic deterministic
debugging opaque bash -x script.sh

How to build

git clone https://github.com/vdutts7/skills-not-mcp.git
cd skills-not-mcp/scripts

API keys:

export ANTHROPIC_API_KEY="sk-..."
export CEREBRAS_API_KEY="..."
# or local Ollama (no key)

Usage

# claude
./chat.sh -m claude-sonnet-4-20250514 "structure this API?"

# ollama (free/local)
./chat.sh -m qwen2.5-coder:7b "review this"

# file context
./chat.sh -f src/main.py -f src/utils.py "explain flow"

# multi-turn
./chat.sh -c sess1 "design cache"
./chat.sh -c sess1 "redis vs memcached?"

# code review
./codereview.sh -m llama-3.3-70b -f src/auth.py

# demo
./demo.sh
provider models env
Anthropic sonnet-4, opus-4 ANTHROPIC_API_KEY
Cerebras llama-3.3-70b, qwen-3-32b CEREBRAS_API_KEY
Ollama qwen2.5-coder, llama, mistral local
OpenAI gpt-4o, o1, o3 OPENAI_API_KEY
Gemini 2.0-flash GEMINI_API_KEY
OpenRouter any OPENROUTER_API_KEY

Tools

Zsh
jq
curl
Claude
MCP
SKILL.md

Contact

website
Twitter

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