Enforces disciplined, complete, step-by-step execution that prevents the LLM failure modes of scope reduction, finding filtering, step skipping, assumed verification, and sycophantic output compression. Provides the explanatory model for WHY agents fail at completeness (RLHF training rewards shorter, cleaner, more positive outputs — 58% sycophancy rate measured in frontier models) and the structural countermeasures: pre-task declarations, step-level evidence receipts, generation/criticism separation, explicit completeness claims, and anti-pattern detection. Use when executing audits, producing reports, creating Linear tasks from findings, verifying acceptance criteria, or any task where completeness and honesty matter more than brevity. Do NOT use for task workflow sequencing (use task-execution), quality definitions per artifact type (use quality-doctrine), or the generate-critique-revise loop mechanics (use self-review-pattern).
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryGeneralStars0
About this skill
Enforces disciplined, complete, step-by-step execution that prevents the LLM failure modes of scope reduction, finding filtering, step skipping, assumed verification, and sycophantic output compression. Provides the explanatory model for WHY agents fail at completeness (RLHF training rewards shorter, cleaner, more positive outputs — 58% sycophancy rate measured in frontier models) and the structural countermeasures: pre-task declarations, step-level evidence receipts, generation/criticism separation, explicit completeness claims, and anti-pattern detection. Use when executing audits, producing reports, creating Linear tasks from findings, verifying acceptance criteria, or any task where completeness and honesty matter more than brevity. Do NOT use for task workflow sequencing (use task-execution), quality definitions per artifact type (use quality-doctrine), or the generate-critique-revise loop mechanics (use self-review-pattern).
Quick start
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Enforces disciplined, complete, step-by-step execution that prevents the LLM failure modes of scope reduction, finding filtering, step skipping, assumed verification, and sycophantic output compression. Provides the explanatory model for WHY agents fail at completeness (RLHF training rewards shorter, cleaner, more positive outputs — 58% sycophancy rate measured in frontier models) and the structural countermeasures: pre-task declarations, step-level evidence receipts, generation/criticism separation, explicit completeness claims, and anti-pattern detection. Use when executing audits, producing reports, creating Linear tasks from findings, verifying acceptance criteria, or any task where completeness and honesty matter more than brevity. Do NOT use for task workflow sequencing (use task-execution), quality definitions per artifact type (use quality-doctrine), or the generate-critique-revise loop mechanics (use self-review-pattern).
About this listing
Category
General
Reported license
CC-BY-4.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI