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.
git clone --depth 1 https://github.com/el-feo/ai-contextWrote 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/el-feo/ai-context/fowler)<a href="https://agentmods.dev/commands/el-feo/ai-context/fowler"><img src="https://agentmods.dev/badge/commands/el-feo/ai-context/fowler/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/commands/el-feo/ai-context/fowler"><img src="https://agentmods.dev/badge/commands/el-feo/ai-context/fowler.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 | $0.00000 | $0.00202 |
| Opus 5.5 | $0.00000 | $0.00081 |
| Sonnet 5.5 | $0.00000 | $0.00040 |
| Haiku 4.5 | $0.00000 | $0.00020 |
Grade A, and why
fowler 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.
What it actually says
Engage the fowler skill and follow its SKILL.md.
Auto-detect the mode from the request (or honor an explicit leading keyword):
- diagnose — review the given code for Fowler's code smells and prescribe the catalog refactorings that cure them.
- refactor — apply a refactoring (named by the user, or chosen from a diagnosis) following the catalog mechanics: small behavior-preserving steps, tests run between steps.
- advise — answer design questions, compare techniques, or teach a smell or refactoring with examples in the user's language.
$ARGUMENTS
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 19 lines · 0 tokens per session scan A a28e184467ff
fowler is a command published in the GitHub repository el-feo/ai-context (12 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 202 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
refactor
Systematic code refactoring with smart scope detection.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.