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 luiseiman/dotforge --skill rule-effectivenessgit clone --depth 1 https://github.com/luiseiman/dotforgeWrote 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/luiseiman/dotforge/rule-effectiveness)<a href="https://agentmods.dev/skills/luiseiman/dotforge/rule-effectiveness"><img src="https://agentmods.dev/badge/skills/luiseiman/dotforge/rule-effectiveness/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/luiseiman/dotforge/rule-effectiveness"><img src="https://agentmods.dev/badge/skills/luiseiman/dotforge/rule-effectiveness.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 | $0.00047 | $0.01455 |
| Opus 5.5 | $0.00019 | $0.00582 |
| Sonnet 5.5 | $0.00009 | $0.00291 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
rule-effectiveness 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rule Effectiveness Analysis
Analyze the effectiveness of .claude/rules/ in the current project by cross-referencing rule globs against actual file activity from git history.
Scope (native-first boundary, v4.7.0): this skill owns the one measurement Claude Code has no native equivalent for — does each rule's glob match files the project actually touches. Everything else is native:
/doctor prompt-audit [path](v2.1.283+) flags rules/CLAUDE.md written for older models, references to files or commands that no longer exist, and contradictions between files — run it for content quality./skill-doctor(v2.1.252+) and/doctorreport per-skill/MCP context cost and unused skills — run them for token budget. Do not re-implement either here.
Step 1: Collect rules inventory
Read all .md files in .claude/rules/. For each:
- Extract
globs:value from YAML frontmatter - Count lines of content (excluding frontmatter)
- Record filename and glob pattern
If a rule has no globs: or paths: frontmatter, classify as always-loaded (loads every session regardless of files touched).
Rules with globs: load eagerly at session start. Rules with paths: + alwaysApply: false load lazily (only when a matching file is touched). Note: paths: must be unquoted CSV — YAML arrays and quoted strings fail silently.
Step 2: Collect file activity from git history
Run: git log --name-only --pretty=format:'' --since='3 months ago' (or configurable period).
Parse output to build:
- session_files: group files by commit date (approximate 1 day = 1 session)
- total_sessions: count distinct dates with commits
- all_files_touched: unique set of all files modified
If fewer than 5 sessions available, warn that results may not be representative and extend to --since='6 months ago'.
Step 3: Cross-reference rules vs activity
For each rule with a glob pattern:
- Match glob against all_files_touched using bash glob expansion or fnmatch logic
- Calculate:
matched_files: count of unique files that match the globmatch_rate: % of sessions where at least 1 file matched the globtoken_cost: lines of rule content (proxy for context consumption)
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 · -4 lines · +23 tokens per session f0737144985f
- 1mo ago First seen · 133 lines · 24 tokens per session scan A 40e8e8a24174
rule-effectiveness is a skill published in the GitHub repository luiseiman/dotforge (8 stars, last pushed 10d ago), licensed MIT. It adds 47 tokens to every session and 1,455 once invoked, about $0.0002 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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