Borrowing it
Nothing to install: this file belongs to TheSmokeDev/taskchad-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TheSmokeDev/taskchad-os/master/.claude/commands/validation/system-review.mdgit clone --depth 1 https://github.com/TheSmokeDev/taskchad-osWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/thesmokedev/taskchad-os/system-review)<a href="https://agentmods.dev/commands/thesmokedev/taskchad-os/system-review"><img src="https://agentmods.dev/badge/commands/thesmokedev/taskchad-os/system-review.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00007 | $0.01111 |
| Opus 5 | $0.00003 | $0.00556 |
| Sonnet 5 | $0.00001 | $0.00222 |
| Haiku 4.5 | $0.00001 | $0.00111 |
Grade A, and why
system-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to system-review — 25 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Review
Perform a meta-level analysis of how well the implementation followed the plan and identify process improvements.
Purpose
System review is NOT code review. You're not looking for bugs in the code - you're looking for bugs in the process.
Your job:
- Analyze plan adherence and divergence patterns
- Identify which divergences were justified vs problematic
- Surface process improvements that prevent future issues
- Suggest updates to Layer 1 assets (CLAUDE.md, plan templates, commands)
Philosophy:
- Good divergence reveals plan limitations → improve planning
- Bad divergence reveals unclear requirements → improve communication
- Repeated issues reveal missing automation → create commands
Context & Inputs
You will analyze four key artifacts:
Plan Command: Read this to understand the planning process and what instructions guide plan creation. .claude/commands/plan-feature.md
Generated Plan: Read this to understand what the agent was SUPPOSED to do. Plan file: $1
Execute Command: Read this to understand the execution process and what instructions guide implementation. .claude/commands/execute.md
Execution Report: Read this to understand what the agent ACTUALLY did and why. Execution report: $2
Analysis Workflow
Step 1: Understand the Planned Approach
Read the generated plan ($1) and extract:
- What features were planned?
- What architecture was specified?
- What validation steps were defined?
- What patterns were referenced?
Step 2: Understand the Actual Implementation
Read the execution report ($2) and extract:
- What was implemented?
- What diverged from the plan?
- What challenges were encountered?
- What was skipped and why?
Step 3: Classify Each Divergence
For each divergence identified in the execution report, classify as:
Good Divergence ✅ (Justified):
- Plan assumed something that didn't exist in the codebase
- Better pattern discovered during implementation
- Performance optimization needed
- Security issue discovered that required different approach
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 189 lines · 7 tokens per session scan A dca6e961d49d
system-review is a command published in the GitHub repository TheSmokeDev/taskchad-os (23 stars, last pushed yesterday), licensed MIT. It adds 7 tokens to every session and 1,111 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to system-review, differing in 25 lines, and is treated as a copy.
Other commands, from other repositories
review
Manage AO code reviews of a worker's PR.
cc-council
Comprehensive multi-agent council review with 6 protocols, 10 specialists, scoped scoring (per-scope thresholds and weights), state machine orchestration, auto-fix, and 50+ configuration flags.
cierre
A sales call just ended: turn its transcript into the full follow-up (CRM, tasks, email draft, reminder, coaching).
deconstruct
First-principles analyst: surface hidden assumptions, find foundational truths, rebuild from scratch.
evolve
Cluster hardened instincts into a proposed Command / Skill / Agent (Instinct Engine).
instinct-export
Export this project's instinct library to a portable YAML pack (Instinct Engine).