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 mikeparcewski/wicked-garden --skill review-methodologygit clone --depth 1 https://github.com/mikeparcewski/wicked-gardenWrote 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/mikeparcewski/wicked-garden/review-methodology)<a href="https://agentmods.dev/skills/mikeparcewski/wicked-garden/review-methodology"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/review-methodology/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/mikeparcewski/wicked-garden/review-methodology"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/review-methodology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 115 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00101 | $0.01257 |
| Opus 5.5 | $0.00040 | $0.00503 |
| Sonnet 5.5 | $0.00020 | $0.00251 |
| Haiku 4.5 | $0.00010 | $0.00126 |
Grade A, and why
wicked-garden-agentic-review-methodology 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 1mo 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Review Methodology
Systematic approach to reviewing agentic systems and codebases for issues, risks, and improvement opportunities.
Four-Phase Review Process
Phase 1: Detect (Discovery)
Goal: Identify all potential issues
Activities:
- Code analysis (static analysis, anti-patterns)
- Configuration review (prompts, secrets, limits)
- Runtime analysis (logs, traces, metrics)
- Documentation review
Tools:
- Static analyzers (pylint, mypy, eslint)
- Custom grep patterns for agentic anti-patterns
- Log aggregation tools
Deliverable: Raw issue inventory
Phase 2: Analyze (Assessment)
Goal: Understand each issue's impact and root cause
For Each Issue:
- Classify type (see
refs/issue-taxonomy-reliability-safety.mdandrefs/issue-taxonomy-quality-testing.md) - Determine severity (Critical/High/Medium/Low)
- Assess impact (Reliability/Security/Cost/Performance)
- Identify root cause
- Estimate fix effort
Analysis Framework:
- What is the issue?
- Why is it a problem?
- What are the consequences?
- What is the root cause?
- How should it be fixed?
Deliverable: Analyzed issue list with severity and impact
Phase 3: Score (Prioritization)
Goal: Prioritize issues for remediation
Severity Levels:
Critical (P0): Security vulnerabilities, data loss risks, system crashes, compliance violations. Fix immediately.
High (P1): Reliability issues, performance problems, cost inefficiencies, safety gaps. Fix within 1 week.
Medium (P2): Code quality issues, minor performance issues, missing observability. Fix within 1 month.
Low (P3): Style issues, optimization opportunities, nice-to-have features. Backlog.
Prioritization Matrix:
Impact vs Effort:
Low Effort High Effort
High Quick Wins Major Projects
Impact (Do First) (Plan)
Low Easy Wins Avoid
Impact (Do Later) (Skip)
Deliverable: Prioritized roadmap
Phase 4: Report (Communication)
What ships with it
3 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.
- 1mo ago Changed · +1 lines · +6 tokens per session 01e918031fc5
- 1mo ago First seen · 187 lines · 95 tokens per session scan A f919bcca9c72
wicked-garden-agentic-review-methodology is a skill published in the GitHub repository mikeparcewski/wicked-garden (9 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 1,257 once invoked, about $0.0004 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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