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/monarchjuno/tradingcodex/tcx-artifactnpx skills add monarchjuno/tradingcodex --skill tcx-artifactgit clone --depth 1 https://github.com/monarchjuno/tradingcodexWrote 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/monarchjuno/tradingcodex/tcx-artifact)<a href="https://agentmods.dev/skills/monarchjuno/tradingcodex/tcx-artifact"><img src="https://agentmods.dev/badge/skills/monarchjuno/tradingcodex/tcx-artifact.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 | $0.00029 | $0.00702 |
| Opus 5 | $0.00015 | $0.00351 |
| Sonnet 5 | $0.00006 | $0.00140 |
| Haiku 4.5 | $0.00003 | $0.00070 |
Grade A, and why
tcx-artifact 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persist An Artifact
Use the authoritative MCP schema for create_research_artifact,
append_research_artifact_version, or issue_forecast. Never approximate a
tool name or write canonical records directly.
Quality Floor
- Answer the assigned question and distinguish facts, analysis, and assumptions in natural prose where material.
- Preserve source/as-of posture, conflicts, uncertainty, confidence and its basis, gaps, blocked actions, and handoff state.
- Use only real service IDs. The service derives hashes, versions, role, identity where applicable, paths, receipt provenance, and recorded time.
- Use
acceptedonly when ready for Head Manager review. Acceptance is completeness, not action authority.
V2 Write Contract
- Record source snapshots before citing them and use only returned IDs.
- Put type, title, universe, optional symbol, Markdown, and one non-empty
summaryat top level. - Put
handoff,evidence_readiness,action_readiness,confidence,confidence_basis, missing evidence, and blocked actions instatus. - Put the run, timezone-qualified cutoff, and every consumed Artifact,
Snapshot, Dataset, and Calculation ID in
lineage. The receipt owns hashes and exact input versions. - Use only
factual,screen,decision-grade, orinsufficientevidence readiness andresearch-only,portfolio-review,draft-eligible, orblockedaction readiness. Portfolio review and draft eligibility require decision-grade evidence. - Include only applicable
requirements:decision_quality,forecast,investor_context, oranti_overfit. Inherited requirements cannot be removed. Omit empty optional blocks. - Put detailed scenarios, contrary evidence, trust explanation, and domain analysis in Markdown. Actual forecast probability, base rate, horizon, and resolution belong only in the Forecast ledger. Improvements belong only in Judgment Review or Postmortem.
- On success, stop and return
ARTIFACT <artifact-id> <path> <handoff>using values from the response. Never reconstruct them.
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.
- 5d ago First seen · 68 lines · 29 tokens per session scan A 3346543510f7
tcx-artifact is a skill published in the GitHub repository monarchjuno/tradingcodex (366 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 702 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 2026-08-30.
Other skills, from other repositories
agent-agentic-payments
Agent skill for agentic-payments - invoke with $agent-agentic-payments.
agent-payments
Agent skill for payments - invoke with $agent-payments.
company-research
A 股个股研究六阶段 SOP(profile → financials → estimates → valuation → risk → report),Phase 0 范围 = 财务估值闭环。当任务是研究 / 分析 / 评估一只或多只已指定代码的 A 股个股时使用;规定每阶段取哪些数据、调哪些 calc 函数、必须落盘什么产物、过什么 Gate。不用于:从市场中筛选标的、泛行业讨论、概念解释、给投资动作建议。.
data-access
A 股零鉴权取数手册。当需要真实的行情 / 市值 / 估值快照、季度报告期累计财务数据、机构一致预期 EPS、PE 历史序列、公告标题、日 K 线、交易日历时使用;只允许运行本 skill 登记的脚本取数(腾讯 / 新浪 / 同花顺 / baostock / 深交所 / 东财),禁止凭模型记忆给数,禁止自造爬虫。概念解释、观点讨论等不需要取数的话题不要加载。.
industry-chain
产业链下钻与不可替代性判定方法:以龙头为"需求入口"沿供应链逐层下钻(整机 / 龙头 → 部件 → 核心器件 → 材料 → 衬底与设备),用物理 / 材料约束(扩产周期、良率、认证周期、有无替代)当筛子找供给刚性的卡口;给每个标的贴不可替代性标签(techmoat / capacitymoat / both / 待补)并列证据;含"卡口越硬越贵"与预期差四问的校准。当任务涉及产业链位置、上下游、护城河、不可替代性、供给瓶颈、竞争格局时加载;单纯取数、估值计算、财报拆分等不涉及产业链结构的任务不要加载。只产出框架与证据表,不给投资动作建议。.
catalyst-risk
催化剂与风险的反证式写法:每个强结论必须先找反证;催化剂按"兑现型 / 预期型 / 周期型"分类并要求可验证的数据时点;风险按技术路线断层、客户集中、产能过剩与价格战、周期顶、预期透支(假便宜 PEG)、一致预期下修、治理与流动性、数据源冲突分类;裁决点的标准写法(什么数据出来会改变判断 + 下一个公开数据时点);知识档案旧结论的反证处理。当任务涉及风险、反证、催化剂、裁决点、预期兑现、什么会推翻结论时加载;单纯取数、估值计算、财报拆分等不需要反证框架的任务不要加载。只产出框架、概率与裁决点,不给投资动作建议。.