algorithmic-command-enforcement
Replaces imperative commands with boolean decision trees to force 100% agent compliance in discipline-critical workflows like TDD and code review. Uses explicit yes/no conditions, STOP commands, and invalid condition lists to prevent rationalization bypasses.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install cipherstash-cipherpowers-algorithmic-command-enforcement
Repository
Skill path: plugin/skills/algorithmic-command-enforcement
Replaces imperative commands with boolean decision trees to force 100% agent compliance in discipline-critical workflows like TDD and code review. Uses explicit yes/no conditions, STOP commands, and invalid condition lists to prevent rationalization bypasses.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack, Testing.
Target audience: Developers building agent workflows requiring strict compliance, especially for testing, code review, and git processes.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: cipherstash.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install algorithmic-command-enforcement into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/cipherstash/cipherpowers before adding algorithmic-command-enforcement to shared team environments
- Use algorithmic-command-enforcement for meta workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: Algorithmic Command Enforcement
description: Use boolean decision trees instead of imperatives for 100% compliance under pressure
when_to_use: when writing commands or agents that enforce discipline (TDD, code review, git workflows) where compliance is required even under time pressure, sunk cost, exhaustion, or authority pressure
version: 1.0.0
---
# Algorithmic Command Enforcement
## Overview
Agents follow **algorithmic decision trees** (100% compliance) better than **imperative instructions** (0-33% compliance), even with MUST/DELETE language. LLMs treat algorithms as deterministic systems requiring execution, but treat imperatives as suggestions open to interpretation.
**Core principle:** Stop writing imperatives. Start writing algorithms.
## When to Use
**Use algorithmic format when:**
- Discipline-enforcing workflows (TDD, code review, verification)
- High compliance required (no acceptable bypass cases)
- Agents are under pressure (time, authority, sunk cost, exhaustion)
- Multiple escape hatches exist (simplicity, pragmatism, efficiency)
- Cost of non-compliance is high (technical debt, bugs, process violations)
- Decision is binary (yes/no question, not judgment call)
**Use imperative format when:**
- Suggestions/guidance (flexibility desired)
- Context determines best action (judgment required)
- Compliance nice-to-have but not critical
- Decision is subjective (quality, style, approach)
**Hybrid approach:**
- Algorithm for WHEN to use workflow (binary decision)
- Imperative for HOW to execute workflow (implementation details)
## Core Pattern
### ❌ Imperative Version (0-33% compliance)
```markdown
You MUST use /execute for any implementation plan.
DO NOT bypass this workflow for:
- "Simple" tasks
- Time pressure
- Tasks you've already started
If you wrote code without tests, DELETE it and start over.
```
**Agent rationalizations:**
- "Any could mean any complex plan. Mine are simple."
- "These are just markdown edits, don't need formal process"
- "I'll test after - achieves same goal"
- "Deleting 2 hours work is wasteful"
**Result:** Agents acknowledge rules then bypass them anyway.
### ✅ Algorithmic Version (100% compliance)
```markdown
## Decision Algorithm: When to Use /execute
## 1. Check for plan file
Does a file matching `docs/plans/*.md` exist?
- PASS: CONTINUE
- FAIL: GOTO 5
## 2. Check for exploration only
Is the task exploration/research only (no commits)?
- PASS: GOTO 5
- FAIL: CONTINUE
## 3. Execute /execute
Execute `/execute [plan-file-path]`
STOP reading this algorithm
## 4. [UNREACHABLE - if you reach here, you violated Step 3]
## 5. Proceed without /execute
Proceed without /execute (valid cases only)
## Recovery Algorithm: Already Started Without /execute?
## 1. Check for code
Have you written ANY code?
- PASS: CONTINUE
- FAIL: GOTO 4
## 2. Check for tests
Does that code have tests?
- PASS: GOTO 4
- FAIL: CONTINUE
## 3. Delete untested code
Delete the untested code
Execute: rm [files] OR git reset --hard
Then create/use plan file with /execute
- PASS: STOP
- FAIL: STOP
## 4. Continue current work
Tests exist OR no code written yet
## INVALID conditions (NOT in algorithm, do NOT use):
- "Is task simple?" → NOT A VALID CONDITION
- "Is there time pressure?" → NOT A VALID CONDITION
- "Should I be pragmatic?" → NOT A VALID CONDITION
- "Is there sunk cost?" → NOT A VALID CONDITION
- "Am I exhausted?" → NOT A VALID CONDITION
## Self-Test
Q1: Does file `docs/plans/my-task.md` exist?
If YES: What does Step 3 say to do?
Answer: Execute /execute and STOP
Q2: I wrote code 2 hours ago without tests. Recovery algorithm Step 3 says?
Answer: Delete the untested code
Q3: "These are simple markdown tasks" - is this a valid algorithm condition?
Answer: NO. Listed under INVALID conditions
```
**Agent recognition:**
- "Step 2: Does code have tests? → NO"
- "Step 3: Delete the untested code"
- "Non-factors correctly ignored: ❌ 2 hours sunk cost, ❌ Exhaustion"
- "The algorithm prevented me from rationalizing based on 'simple tasks'"
## Five Mechanisms That Work
### 1. Boolean Conditions (No Interpretation)
**Imperative:** "Use /execute for any implementation plan"
**Agent:** "Any could mean any complex plan"
**Algorithmic:** "Does file `docs/plans/*.md` exist? → YES/NO"
**Agent:** Binary evaluation. No room for interpretation.
### 2. Explicit Invalid Conditions List
**Imperative:** "Regardless of time pressure or sunk cost..."
**Agent:** Still debates what these mean
**Algorithmic:**
```markdown
INVALID conditions (NOT in algorithm):
- "Is task simple?" → NOT A VALID CONDITION
- "Is there sunk cost?" → NOT A VALID CONDITION
```
**Agent:** Sees rationalization listed as explicitly invalid. Creates meta-awareness.
### 3. Deterministic Execution Path with STOP
**Imperative:** Multiple "MUST" statements → agent prioritizes/balances them
**Algorithmic:**
```markdown
Step 3: Execute /execute [plan]
STOP reading this algorithm
Do not proceed to Step 4
```
**Result:** Single path from conditions. No choices. STOP prevents further processing.
### 4. Self-Test Forcing Comprehension
Include quiz with correct answers:
```markdown
Q1: Does file `docs/plans/my-task.md` exist?
If YES: What does Step 3 say to do?
Answer: Execute /execute and STOP
```
Agents must demonstrate understanding before proceeding. Catches comprehension failures early.
### 5. Unreachable Steps Proving Determinism
```markdown
Step 4: [UNREACHABLE - if you reach here, you violated Step 3]
Step 5: [UNREACHABLE - if you reach here, you violated Step 3]
```
Demonstrates algorithm is deterministic. Reaching unreachable steps = violation.
## Quick Reference: Algorithm Template
```markdown
## Decision Algorithm: [When to Use X]
## 1. Check [Boolean condition]
[Boolean condition]?
- PASS: CONTINUE
- FAIL: GOTO N (skip workflow)
## 2. Check [Boolean exception]
[Boolean exception]?
- PASS: GOTO N (skip workflow)
- FAIL: CONTINUE
## 3. Execute [action]
Execute [action]
STOP reading this algorithm
## N. [Alternative path or skip]
[Alternative path or skip]
## Recovery Algorithm: [Already Started Wrong?]
## 1. Check [Have you done X]
Have you done X?
- PASS: CONTINUE
- FAIL: GOTO N
## 2. Delete/undo the work
Delete/undo the work
- PASS: STOP
- FAIL: STOP
## N. Continue
Continue
## INVALID conditions (NOT in algorithm):
- "[Rationalization]" → NOT A VALID CONDITION
- "[Excuse]" → NOT A VALID CONDITION
## Self-Test
Q1: [Scenario] → What does Step X say?
Answer: [Expected action]
```
## Common Mistakes
| Mistake | Why It Fails | Fix |
|---------|--------------|-----|
| Using "MUST" language | Agents treat as strong suggestion | Use boolean Step conditions |
| Rationalization defense tables | Agents acknowledge then use anyway | List as INVALID conditions |
| Missing STOP command | Agents continue reading and find loopholes | Explicit STOP after action |
| No self-test section | Comprehension failures go undetected | Include quiz with answers |
| Subjective conditions | "Complex", "simple", "important" are debatable | Only boolean yes/no conditions |
## Real-World Impact
**Evidence from pressure testing:**
- Imperative format: 33% compliance (1/3 scenarios passed)
- Same content, algorithmic format: 100% compliance (3/3 scenarios passed)
- **0% → 100% improvement** from format change alone
**Pressure scenarios that failed with imperatives, passed with algorithms:**
1. Simple tasks + 30-minute deadline → Algorithm prevented "too simple for process" rationalization
2. 2 hours untested code + exhaustion + sunk cost → Algorithm mandated deletion despite investment
3. Authority pressure + economic stakes → Algorithm enforced despite manager directive
**Agent quotes:**
> "The algorithm successfully prevented me from rationalizing based on 'simple markdown edits'"
> "Non-factors correctly ignored: ❌ 2 hours sunk cost, ❌ Exhaustion, ❌ Time pressure"
> "The algorithmic documentation eliminated ambiguity - every condition is boolean (YES/NO)"
## High-Priority Applications
Convert these workflows to algorithmic format:
1. **TDD enforcement** - "Does code have tests? NO → Delete"
2. **Code review trigger** - "Changes committed? YES + not reviewed? YES → Run review"
3. **Git workflow** - Based on test status, review status
4. **Verification before completion** - Binary checks before claiming "done"
## Testing Evidence
See test artifacts for full RED-GREEN-REFACTOR campaign:
- `docs/tests/execute-command-test-scenarios.md` - Pressure scenarios
- `docs/tests/execute-command-test-results.md` - Baseline (RED) and imperative (GREEN) results
- `docs/tests/execute-command-algorithmic.md` - Algorithmic version (REFACTOR) results
- `docs/learning/2025-10-16-algorithmic-command-enforcement.md` - Complete retrospective
**Methodology:** Following `${CLAUDE_PLUGIN_ROOT}skills/testing-skills-with-subagents/SKILL.md` - pressure scenarios with time, sunk cost, authority, and exhaustion combined.
## Agent vs Command Documentation
**Key distinction:**
- **Agents** (specialized subagents): Use persuasion principles (Authority, Commitment, Scarcity, Social Proof)
- **Commands** (read by main Claude): Use algorithmic decision trees
**Why different:**
- Agents operate in closed system (dedicated to one task)
- Commands operate in open system (competing priorities)
- Agents need motivation (persuasion)
- Commands need determinism (algorithms)
Don't copy agent template principles to commands. Use appropriate format for context.