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spec-discipline

Enforce falsifiable hypotheses and data audits in bug resolution workflows.

Updated Jun 4, 2026
Search Tags:#root cause analysis#bug diagnosis#cross-validation#multi-agent orchestration#spec discipline#state audit
One-click install
npx skills add https://github.com/rp4ri/orchestration-studio --skill spec-discipline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: spec-discipline
Source: https://github.com/rp4ri/orchestration-studio/tree/main/skills/spec-discipline
Command: npx skills add https://github.com/rp4ri/orchestration-studio --skill spec-discipline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the costly waste of parallel workers executing correct code for incorrect bug diagnoses, which leads to multiple shipped fixes that pass all tests but fail to resolve the user's actual reported symptom, a pattern that has caused production sagas lasting 5+ releases.

Core Features & Use Cases

  • Falsifiable Hypothesis Specs: Enforces bug specifications that list ranked, testable hypotheses instead of unproven conclusions, allowing workers to challenge the director's framing before writing code.
  • Mandatory Phase-0 Data Audits: Requires a physical data location check for all state, persistence, and sync bugs before any fix work is delegated, preventing fixes based on incorrect assumptions about where data lives.
  • Two-Fix Stop Rule & Task Force Protocol: Freezes incremental fixes when a bug survives two shipped releases, dispatching a cross-functional team to audit data, deployment, end-to-end traces, and live reproductions to find the real root cause.
  • Premise-Challenger Cross-Validation: Assigns one reviewer per cross-validation cycle to attack unverified assumptions in the bug spec, preventing "CLEAN theater" where PRs pass review but are built on false premises.
  • Use Case: Use this Skill when a user-reported bug has had multiple CLEAN PRs that do not fix the symptom, when writing bug specs for worker dispatch, or when reviews keep passing but the user still sees the issue.

Quick Start

Use the spec-discipline skill to restructure your current bug spec for the unresolved recurring user symptom to include falsifiable hypotheses, a mandatory phase-0 data audit step, and a premise-challenger review requirement.

Frequently Asked Questions about spec-discipline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Fixes pass cross-validation but fail to resolve user symptoms when bug specs contain unverified inherited assumptions. Assigning a dedicated premise-challenger reviewer to attack the bug spec framing prevents PRs built on false premises from passing review.▼

Fixes pass cross-validation but fail to resolve user symptoms when bug specs contain unverified inherited assumptions. Assigning a dedicated premise-challenger reviewer to attack the bug spec framing prevents PRs built on false premises from passing review.

How do I write a bug spec for multi-agent worker dispatch?▼

Write a bug spec for multi-agent worker dispatch by listing ranked, falsifiable hypotheses instead of unproven conclusions. This allows parallel workers to challenge the director's framing before writing code, preventing incorrect diagnoses from scaling.

When should I stop shipping incremental fixes for a recurring bug?▼

Stop shipping incremental fixes for a recurring bug after it survives two shipped releases. Freeze further fixes and dispatch a cross-functional task force to audit data, deployment, end-to-end traces, and live reproductions to find the root cause.

How do I diagnose state and persistence bugs that keep recurring across releases?▼

Diagnose recurring state and persistence bugs by performing a mandatory phase-0 data audit to physically verify data locations before delegating fix work. This prevents workers from writing fixes based on incorrect assumptions about where data lives.

How to prevent parallel workers from executing correct code for the wrong bug diagnosis?▼

Prevent parallel workers from executing correct code for the wrong diagnosis by enforcing falsifiable hypothesis formatting in bug specifications. This stops wasted effort on fixes that do not resolve the actual user-reported symptom.

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