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 cxcscmu/SkillLearnBench --skill qiyan-lvshigit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/qiyan-lvshi)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/qiyan-lvshi"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/qiyan-lvshi/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/cxcscmu/skilllearnbench/qiyan-lvshi"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/qiyan-lvshi.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 | $0.00020 | $0.00405 |
| Opus 5 | $0.00010 | $0.00202 |
| Sonnet 5 | $0.00004 | $0.00081 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
qiyan-lvshi 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 5d 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
Seven-Character Regulated Verse (七言律诗)
The seven-character regulated verse (七言律诗) is a form of traditional Chinese poetry. It consists of 8 lines with 7 characters each.
1. Structure
- Length: 8 lines (4 couplets/联).
- Couplet 1 (首联): Lines 1-2. Introduction.
- Couplet 2 (颔联): Lines 3-4. Development. Must be antithetical (对仗).
- Couplet 3 (颈联): Lines 5-6. Shift/Turning. Must be antithetical (对仗).
- Couplet 4 (尾联): Lines 7-8. Conclusion.
- Total Characters: 56 (excluding title).
2. Tonal Patterns (Ping-Ze - 平仄)
Traditional poetry uses "Even" (平) and "Deflected" (仄) tones.
- Line 1: Generally rhymes (平声起韵).
- Line 2, 4, 6, 8: Must rhyme (押韵).
3. Antithesis (对仗 - Parallelism)
Couplets 2 (lines 3-4) and 3 (lines 5-6) must use strict parallelism:
- Grammatical: Noun vs Noun, Verb vs Verb, Adjective vs Adjective.
- Semantic: Mountains vs Rivers, Blue vs Red.
4. Usage in Task
When writing for a modern audience using Mandarin rhyme:
- Focus on the content flow: Intro -> Development (Antithesis) -> Shift (Antithesis) -> Conclusion.
- Ensure the middle four lines are parallel.
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.
- 5d ago First seen · 32 lines · 20 tokens per session scan A 8185168ae5e0
qiyan-lvshi is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 405 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
ceo-setup
One-time onboarding for the executive/manager commitment workflow — delegation-heavy, meeting prep, decision capture, morning and evening digests. Creates a commitments project and installs two dashboard widgets. After successful setup this skill is excluded from selection until the marker file is deleted.
content-creator-setup
One-time onboarding for the content creator workflow — content pipeline stages, trend expiration, cross-platform cascades, heavy idea parking. After successful setup this skill is excluded from selection until the marker file is deleted.
github
GitHub API integration via HTTP tool with automatic credential injection.
idea-parking
Park interesting ideas for later consideration, resurface them periodically, and promote to commitments when ready.
agentsop-llamaindex
Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework. Activate when the calling agent must build, debug, harden, or evaluate a Retrieval-Augmented Generation pipeline over unstructured/private data, decide between RAG primitives (Index types, retrievers, query engines, routers…
agentsop-llm-artifact-versioning
Enhancement overlay — version the WHOLE deployable LLM-app artifact as one bundle: prompts + compiled programs + model snapshot pins + retrieval config + eval-set version, versioned together so a deploy is reproducible and rollback is atomic. Activate when preparing to deploy an LLM app, when asking "what exactly is…