Agent skill

Macro Economic Analysis

by byteseek in byteseek/Mira

Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite.

Apache-2.0Auto-check passedMarketing & SEO

Install Macro Economic Analysis

skills CLI
$ npx skills add byteseek/Mira --skill macro-economic-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install byteseek/Mira macro-economic-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/macro-economic-analysis .claude/skills/macro-economic-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
macro-economic-analysis
GitHub stars
275
Token cost
~1.9k tokens
SKILL.md length
699 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
Apache-2.0

At a glance

Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite.

  • Works in 8 steps: Growth → Inflation → Policy → …
  • Marketing & SEO work in your project
  • SKILL.md covers Use When, Required Inputs, Macro Regime Map and Transmission Chains, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Macro Economic Analysis is an agent skill from byteseek/Mira. Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO. The repository describes itself as: Agent-native investment research workspace for evidence-tracked, refreshable investment theses across equities, earnings, macro, and portfolio review. The licence is Apache-2.0.

When your agent uses it

  • Marketing & SEO work in your project

Example prompts

  • “/macro-economic-analysis”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Growth
  2. Inflation
  3. Policy
  4. Liquidity And Financial Conditions
  5. Credit
  6. FX And Rates
  7. Risk Appetite And Positioning
  8. Market Pricing

What it can do on your machine

Read from SKILL.md and the folder at commit adddce7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Macro Economic Analysis loads about 1.9k tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 699 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from byteseek/Mira at commit adddce7, republished under its Apache-2.0 licence (© byteseek). 699 words, ~1,928 tokens.

Download SKILL.mdSave it as .claude/skills/macro-economic-analysis/SKILL.md (or your agent's skills folder).
name
macro-economic-analysis
description
Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite.

Macro Economic Analysis Skill

这个 skill 用于把宏观经济分析转成可执行的资产定价判断。

它不是宏观背景介绍,也不是经济学教材式综述。它服务于一个核心问题:

当前宏观状态是否正在改变目标资产的盈利路径、贴现率、风险溢价、流动性、仓位或催化剂时间表?

Use When

  • 研究对象是指数、宏观敏感资产、周期股、资源品、银行、地产、出口链、黄金、美债、美元或高估值成长股。
  • 单票研究中,价格波动明显由利率、通胀、增长、政策、美元、信用、资金流或风险偏好解释。
  • 财报或公司事件本身不足以解释价格,必须判断市场在交易 growth scare、reflation、policy pivot、liquidity easing/tightening 或 risk-off/risk-on。
  • 用户明确要求宏观、利率、经济周期、央行、财政、流动性或市场风险偏好分析。

如果研究对象是具体商品、商品期货曲线、库存、供需平衡或成本曲线,先使用 skills/commodity-cycle-analysis/SKILL.md。只有当商品冲击传导到通胀、利率、财政、外部账户、美元、信用或风险偏好时,才升级为本 macro skill 或叠加 macro overlay。

Required Inputs

  • asset_or_ticker
  • market_scope
  • research_question
  • research_cutoff_date
  • thesis_horizon
  • current_market_pricing 例如收益率曲线、Fed funds futures、美元、信用利差、指数走势、行业相对强弱、估值倍数。
  • macro_sources 至少覆盖官方数据、央行/财政/国际组织材料、市场定价数据,以及机构或 practitioner 观点中的两类。

Macro Regime Map

先用以下维度判断当前 regime。不要机械打分,要写清楚哪些变量真正影响本次研究对象。

1. Growth

关注:

  • GDP、工业生产、PMI、零售、消费、就业、收入、企业投资、库存周期。
  • 需求是加速、减速、韧性还是断裂。
  • 增长变化是 broad-based,还是只集中在少数行业或 capex 主题。

核心问题:

  • 增长变化影响的是收入 beta、盈利弹性、信用质量,还是风险偏好?
2. Inflation

关注:

  • CPI、PCE、PPI、工资、租金、商品、能源、进口价格、通胀预期。
  • 通胀是需求拉动、供给冲击、工资粘性,还是政策/关税/汇率传导。

核心问题:

  • 通胀变化是否改变央行反应函数、实际利率、利润率或估值倍数?
3. Policy

关注:

  • 央行政策路径、forward guidance、财政脉冲、税收、产业政策、监管政策、贸易政策。
  • 市场预期路径与政策制定者反应函数是否偏离。

核心问题:

  • 政策是提供 liquidity cushion,还是制造 discount-rate / margin / demand shock?
4. Liquidity And Financial Conditions

关注:

  • 实际利率、收益率曲线、期限溢价、美元流动性、QT/QE、准备金、TGA、回购市场、信用利差、银行信贷、融资成本。
  • 金融条件内部是否分裂,例如利率收紧但信用利差和股票估值仍宽松。

核心问题:

  • 当前融资环境会放大还是压制风险资产估值、企业融资、回购、并购和 capex?
5. Credit

关注:

  • 投资级与高收益利差、违约率、贷款标准、银行放贷、私募信用、再融资墙、杠杆水平。

核心问题:

  • 信用条件是否正在改变企业生存性、投资能力、估值下限或尾部风险?
6. FX And Rates

关注:

  • 美元指数、实际利率、名义利率、曲线形态、期限溢价、跨币种套保成本、资本流向。

核心问题:

  • 汇率和利率通过收入换算、进口成本、资金流、估值贴现或外债压力传导到资产了吗?
7. Risk Appetite And Positioning

关注:

  • VIX、信用利差、股债相关性、市场宽度、资金流、CTA/vol-control、期权偏度、拥挤度、主题集中度。

核心问题:

  • 价格变化来自基本面 revision,还是来自仓位、杠杆、流动性和风险预算变化?
8. Market Pricing

这是必须单独写的一层。

关注:

  • 市场已经 price in 什么。
  • 数据或政策相对预期是 surprise 还是 confirmation。
  • 当前价格隐含的是 soft landing、recession、reflation、stagflation、AI productivity boom,还是 liquidity rally。

核心问题:

  • 哪个宏观变量的边际变化最可能触发重定价?

Transmission Chains

宏观结论必须落到至少一条传导链。常用链条:

  • growth -> revenue beta -> operating leverage -> earnings revision -> multiple
  • inflation -> policy path -> real rates -> duration multiple -> equity valuation
  • inflation -> input cost -> gross margin -> pricing power test
  • policy -> liquidity -> risk appetite -> positioning -> valuation
  • rates -> mortgage/credit demand -> housing/banks/consumer
  • dollar -> translation/import cost/EM liquidity -> earnings and flows
  • credit spread -> financing access -> default risk -> equity risk premium
  • commodity shock -> inflation + margins + fiscal/external balance
  • fiscal impulse -> nominal demand -> sector revenue -> rates/term premium offset

If no credible transmission chain exists, macro should stay as context and not enter the core thesis.

如果传导链的第一变量是具体商品供需、库存、期货曲线或成本曲线,先运行 commodity-cycle-analysis,再把结论压缩成 macro transmission input。

Gold And Precious-Metals Transmission

When the object is gold, silver, precious-metals ETFs or gold miners, do not stop at broad labels such as risk-off, real rates or weak dollar. If the price move is large or poorly explained by the usual variables, consider the gold-residual-regime-lens as a macro-specific sub-lens.

Record:

  • gold_residual_lens: not_used, qualitative_only, recomputed, or calculation_gap
  • factor_stack: dollar, real-rate / purchasing-power, inflation / commodity, crisis-optionality proxies
  • residual_state: explained, mild_divergence, large_divergence, mean_reverting, new_plateau_candidate, or source_gap
  • dominant_macro_chain
  • market_pricing
  • must_refresh_if

Use templates/gold-residual-regime-check.csv for compact cases. Treat residual state as an input to macro regime and top/bottom risk, not as an independent buy/sell signal.

Data Release Triage

当用户问单次宏观数据发布,例如 CPI、PPI、PCE、NFP、ISM、retail sales 或 GDP 时,先运行 macro-data-release-triage,再决定是否升级为完整 macro-regime-analysis。

最低流程:

  1. 确认官方发布时间、数据期和修正项。
  2. 比较 headline 与 consensus / market pricing,判断 surprise 是确认还是反转。
  3. 从 headline 拆到核心子项,定位问题来自 level、change、revision、breadth 还是 composition。
  4. 区分一次性噪音与可持续传导,例如能源、食品、工资、租金、运费、库存、信贷或利润率。
  5. 做历史类比,但必须写出相似点、不同点和政策环境差异。
  6. 推演数据继续恶化或转好的上游条件。
  7. 映射到资产传导链、市场已计价路径、stale_after 和 must_refresh_if。

输出字段:

  • release_context
  • headline_surprise
  • component_problem
  • historical_analogue
  • upstream_conditions
  • market_pricing
  • asset_transmission
  • what_is_already_priced
  • must_refresh_if

相关方法卡:memory/methodologies/macro-data-release-triage.md。

Output Requirements

For a standalone macro note, output:

  • macro_regime
  • dominant_macro_variable
  • market_pricing
  • transmission_chain
  • asset_impact
  • what_is_already_priced
  • what_would_change_the_view
  • stale_after
  • must_refresh_if

For an equity research package, add these fields to case notes or memo:

  • macro_weight one of none, context, secondary, primary
  • macro_overlay_basis
  • dominant_macro_chain
  • macro_mismatch_risk
  • macro_refresh_triggers

For gold or precious-metals work where the residual lens is used, also add:

  • gold_residual_lens
  • residual_state
  • calculation_status
Show full SKILL.md (264 more words)Show less

Practical Checks

  • Do not ask whether the economy is good or bad. Ask whether the macro path is changing relative to market expectations.
  • Do not ask whether rate cuts are bullish or bearish. Ask whether cuts mean liquidity support, growth scare, or disinflation relief.
  • Do not ask whether CPI is high or low. Ask whether the print changes the policy path, real rates, margins, or inflation expectations.
  • Do not use broad macro labels unless they change the target asset's earnings path, discount rate, risk premium, liquidity, or positioning.
  • Always separate official data, market pricing, institutional interpretation, practitioner signal, and Mira-derived inference.

Failure Modes

  • Turning every memo into a generic macro chapter.
  • Treating commodity-specific inventory, curve or trade-flow signals as generic macro.
  • Treating lagging macro data as if it were a forward signal.
  • Ignoring what the market already priced.
  • Confusing level with change, and change with surprise.
  • Using one macro regime for every asset even when transmission differs.
  • Explaining price action after the fact without predefining falsification triggers.
  • For gold, using residual or bubble language without stating the factor stack, market pricing and calculation status.

Source Quality Guidance

  • Official data and central bank materials are best for facts and policy language.
  • BIS, IMF and similar institutions are useful for macro-financial structure and cross-border transmission.
  • T0/T1 sell-side and asset-manager outlooks are useful for how professionals connect macro variables to asset allocation, but they remain interpretation rather than fact.
  • Practitioner material is useful for high-frequency signals, positioning and market sensitivity, but must be downgraded if not cross-checkable.

Current Status

  • methodology_status: trial
  • related_methodology_card: memory/methodologies/macro-regime-analysis.md
  • related_overlay: skills/equity-research-core/references/macro-overlay.md
  • related_precious_metals_lens: memory/methodologies/gold-residual-regime-lens.md

© byteseek, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/macro-economic-analysis of byteseek/Mira.

Open the folder on GitHubat commit adddce7

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Categories

Questions about Macro Economic Analysis

What does Macro Economic Analysis do?

Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite. Macro Economic Analysis is an agent skill from byteseek/Mira. Convert macroeconomic evidence into asset-pricing implications across growth, inflation, policy, rates, dollar, credit, liquidity, and risk appetite.

When should I use Macro Economic Analysis?

Macro Economic Analysis fits situations like: marketing & SEO work in your project.

How do I install Macro Economic Analysis in Claude Code?

Run `npx skills add byteseek/Mira --skill macro-economic-analysis -a claude-code`. Or copy the skill folder (skills/macro-economic-analysis in byteseek/Mira) into .claude/skills/macro-economic-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Macro Economic Analysis in Codex?

Run `npx skills add byteseek/Mira --skill macro-economic-analysis -a codex`. Or copy the skill folder (skills/macro-economic-analysis in byteseek/Mira) into .agents/skills/macro-economic-analysis in your project. Codex loads it when a task matches its description.

Can I use Macro Economic Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add byteseek/Mira --skill macro-economic-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/macro-economic-analysis, .gemini/skills/macro-economic-analysis, .github/skills/macro-economic-analysis and .opencode/skills/macro-economic-analysis in your project.

What does Macro Economic Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Macro Economic Analysis is instructions for the agent only.

Does Macro Economic Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Macro Economic Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Macro Economic Analysis use?

Macro Economic Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Macro Economic Analysis use?

About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Macro Economic Analysis?

Skills that share tags, products or a category with Macro Economic Analysis: Geo Fundamentals (wasp-lang/wasp, 19k stars), Ab Testing (coreyhaines31/marketingskills, 54k stars), Hreflang and International SEO (AgriciDaniel/claude-seo, 19k stars) and Referrals (coreyhaines31/marketingskills, 54k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Macro Economic Analysis?

byteseek (a GitHub organization) maintains it in byteseek/Mira, which has 275 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 8, 2026.

Source: byteseek/Mira on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.