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 agentmods add skills/ctrlcakepro/chilon-recall/textbook-qanpx skills add ctrlcakepro/chilon-recall --skill textbook-qagit clone --depth 1 https://github.com/ctrlcakepro/chilon-recallWhat 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 | $0.00053 | $0.00154 |
| Opus 5 | $0.00026 | $0.00077 |
| Sonnet 5 | $0.00011 | $0.00031 |
| Haiku 4.5 | $0.00005 | $0.00015 |
Grade A, and why
textbook-qa 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 yesterday.
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
Textbook QA
- Call
rag_statuswhen source scope or index readiness is not already established. - Call
textbook_qawith the user's exact question and the requested answer depth. - Lead with a direct answer, then cite the returned relative source paths and headings.
- Separate retrieved source claims from your explanation or outside knowledge.
- State what the evidence does not establish; do not treat a high retrieval score as proof of completeness.
What ships with it
1 file 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.
- yesterday First seen · 14 lines · 53 tokens per session scan A 4ab644435f57
textbook-qa is a skill published in the GitHub repository ctrlcakepro/chilon-recall (1 stars, last pushed 2d ago), licensed MIT. It adds 53 tokens to every session and 154 once invoked, about $0.0003 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.
Other skills, from other repositories
shodh-memory
Persistent memory system for AI agents. Use this skill to remember context across conversations, recall relevant information, and build long-term knowledge. Activate when you need to store decisions, learnings, errors, or context that should persist beyond the current session.
guideline-learning-diagnosis
当用户要求评估自己对某份指南的掌握情况、制定指南学习/备考计划、梳理薄弱章节、 做教育性小测，或学习指南中的诊断标准、鉴别框架和流程关系时使用。 本技能只做学习诊断与诊断标准教学，不对具体患者作疾病诊断、治疗、处方、剂量、 急诊处置或医保报销判断。.
guideline-learning
指南学习流程约束。判断请求类型→读取状态→按流程创建轨道/预览/投递/排查迁移；操作命令与细则见 references/learning-operations.md。选题用权威信源，输出前经 output-format 校验。不生成诊疗/处方/急诊SOP/个体患者建议。.
skill-sublation
技能扬弃 Sublation V5.0 完整版。把执行经验沉淀为观测、候选、验证、多 Agent 协作面板、默认关闭的受控唤醒意图、Skill 分类与 shadow 精准建议、用户批准、晋升和观察窗的可审计治理链路；仅在用户明确说出 sublation 或扬弃技能时触发。.
plur-memory
Persistent learning for AI agents. Open engram format. Your agent learns from corrections, remembers across sessions, and transfers knowledge across domains.
autobrowse
Learn a reliable browser workflow by iterating on a real web task, recording strategy, and proposing a reusable skill.