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 sfc-gh-myoung/ai_coding_rules --skill rule-loadergit clone --depth 1 https://github.com/sfc-gh-myoung/ai_coding_rulesWrote 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/sfc-gh-myoung/ai_coding_rules/rule-loader)<a href="https://agentmods.dev/skills/sfc-gh-myoung/ai_coding_rules/rule-loader"><img src="https://agentmods.dev/badge/skills/sfc-gh-myoung/ai_coding_rules/rule-loader.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 | $0.00072 | $0.01203 |
| Opus 5 | $0.00036 | $0.00602 |
| Sonnet 5 | $0.00014 | $0.00241 |
| Haiku 4.5 | $0.00007 | $0.00120 |
Grade A, and why
rule-loader 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 7d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rule Loader
Selects and loads the correct set of rule files for any user request, ensuring consistent rule discovery across agents and sessions.
Purpose
Given a user request, determine which rules to load, in what order, respecting dependencies and token budgets. This skill formalizes the rule-loading algorithm defined in AGENTS.md Steps 1-3 into a reusable, progressively-disclosed workflow.
Use this skill when
- Loading rules for a new user request (first response or task switch)
- Resolving which domain rules match a file extension
- Determining activity rules from request keywords
- Managing token budgets when multiple rules are candidates
- Debugging why a rule was or was not loaded
- Building rule-loading logic into new agent configurations
Inputs
Required
user_request:string- The user's message text to analyze for keywords, extensions, and technologies
Optional
rules_path:string(default:rules/) - Path to the rules directorytoken_budget_limit:number(default:20000) - Hard maximum token budget for loaded rules. A soft warning triggers at 75% of this value (default: 15,000) to begin evaluating Low-tier deferrals.context_tier_filter:string(default:all) - Filter by ContextTier:all,critical,critical+high,critical+high+medium
Input Validation
Before executing Phase 1:
user_requestmust be a non-empty string. If empty or whitespace-only: STOP with "No user request provided."token_budget_limitmust be a positive integer >= 5000. If below 5000: WARN "Token budget too low for foundation + any domain rule. Minimum recommended: 5000."context_tier_filtermust be one of:all,critical,critical+high,critical+high+medium. If invalid: WARN and default toall.
Output (required)
A ## Rules Loaded section listing all selected rules with loading reasons, formatted per AGENTS.md Step 4.
Example output:
## Rules Loaded
- rules/000-global-core.md (foundation)
- rules/200-python-core.md (file extension: .py)
- rules/100-snowflake-core.md (dependency of 101)
- rules/101-snowflake-streamlit-core.md (keyword: Streamlit)
- rules/206-python-pytest.md (keyword: test)
- [Deferred: 204-python-docs.md - Low tier, not required for task]
What ships with it
11 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.
- CHANGELOG.md 274 B
- examples/multi-domain.md 2.9 KB
- examples/python-api.md 2.0 KB
- examples/streamlit-dashboard.md 2.1 KB
- examples/token-budget-deferral.md 4.0 KB
- tests/test-scenarios.md 7.3 KB
- workflows/activity-matching.md 3.7 KB
- workflows/dependency-resolution.md 2.5 KB
- workflows/domain-matching.md 3.6 KB
- workflows/foundation-loading.md 1.1 KB
- workflows/token-budget.md 2.8 KB
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.
- 7d ago First seen · 133 lines · 72 tokens per session scan A 602ffcb8f2c2
rule-loader is a skill published in the GitHub repository sfc-gh-myoung/ai_coding_rules (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 1,203 once invoked, about $0.0004 per session on Opus 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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