Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add DDS-Solutions/AI-TadPole-OS --skill code-review-checklistgit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-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/skills/dds-solutions/ai-tadpole-os/code-review-checklist)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/code-review-checklist"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/code-review-checklist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/code-review-checklist"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/code-review-checklist.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00031 | $0.01517 |
| Opus 5.5 | $0.00012 | $0.00607 |
| Sonnet 5.5 | $0.00006 | $0.00303 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
code-review-checklist 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / code-review-checklist
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Inconsistent review standards, missed security vulnerabilities, ungrounded nitpicking.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
🛡️ Code Review Audit Engine
This skill serves as the Audit Engine for the REVIEW operational mode. It ensures that all code entering the deployment pipeline meets the Sovereign standard of architectural excellence and security hardening.
📚 Progressive Disclosure & L3 Reference Index
Consult deep L3 Reference Guides and verification tools on demand:
- Audit Rubric & Security Guide: audit_rubric_and_security_guide.md
- Deterministic Rubric Evaluator: audit_rubric_evaluator.py
⛓️ Pipeline Integration
This skill acts as the automated "Judge" in the Plan-Execute-Critic (PEC) loop:
IMPLEMENT $\rightarrow$ REVIEW (This Skill) $\rightarrow$ DEBUG (If flaws found) $\rightarrow$ SHIP
📏 Contextual Auditing Standards
Calibrate audit severity according to the codebase context:
| Context | Review Rigor | Primary Goal | Rule |
|---|---|---|---|
| Greenfield (New Code) | 🔴 Ruthless | Flawless Architecture | Zero tolerance for architectural drift, smells, or missing tests. |
| Feature Update | 🟡 Strict | Stability & Parity | New code must be clean; existing behavior and API contracts must not regress. |
| Legacy Fix | 🟢 Pragmatic | Risk Mitigation | Boy Scout Rule: Leave it cleaner than found; avoid uncontrolled scope creep. |
📋 The Master Audit Rubric (5 Pillars)
1. Correctness & Logic
- Functional Parity: Does the code faithfully solve the problem declared in the specification?
- Edge-Case Resilience: Are empty lists, null/None states, divide-by-zero, and connection timeouts handled?
- Aletheia Validation: Is logical execution verifiable and deterministic without wishful assumptions?
- Error Handling: Are errors wrapped in contextual domain types rather than logged and dropped?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago Changed · -10 lines · +14 tokens per session 6d5b684c7929
- 1mo ago First seen · 136 lines · 17 tokens per session scan A 812aa73e6eee
code-review-checklist is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed 5d ago), licensed MIT. It adds 31 tokens to every session and 1,517 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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