What does this skill do, and when should you use it?
Macro & Rates Monitor is designed for macro strategists and rates analysts. It combines economic indicators, government and swap curves, inflation breakevens, real yields, swap spreads, and historical pricing context through LSEG MCP tools. The workflow evaluates cycle position, central-bank policy signals, curve shape, real-rate conditions, and financial conditions. It produces a structured dashboard followed by an overall macro-rates assessment.
Calls qa_macroeconomic for GDP, CPI/PCE, unemployment, payrolls, PMI, and retail-sales data; uses interest_rate_curve to analyze government and swap curves; uses inflation_curve to decompose nominal yields, breakevens, and real rates; uses ir_swap to calculate 2Y, 5Y, and 10Y swap spreads; uses tscc_historical_pricing_summaries for historical benchmark-yield context; and synthesizes the results into a macro summary, yield-curve snapshot, real-rate decomposition, swap-spread table, and overall assessment.
- A macro strategy team assessing a country's cycle position using GDP, inflation, unemployment, and PMI data.
- A rates trader studying curve shape through 3M, 2Y, 5Y, 10Y, and 30Y yields plus 2s10s and 3M-10Y slopes.
- A fixed-income researcher decomposing nominal yields into inflation expectations and real rates.
- A risk team monitoring financial conditions through government yields and 2Y, 5Y, and 10Y swap spreads.
How do you install this skill?
- Core functionality depends on external LSEG MCP tools, credentials, and subscription access; verify reachability and data entitlements in the target environment first.
- Review series identifiers, units, observation dates, time zones, missing values, tenor matching, and real-rate and swap-spread calculations before using the output.
- The skill does not define stop conditions or feedback formats for service failures, conflicting data, stale data, or insufficient series; do not treat the generated macro narrative as investment advice.
- Network access
- MCP Server
LSEG MCP tools
The README documents installation through Cowork: open Settings → Plugins → Add plugin, paste https://github.com/anthropics/financial-services, and select the relevant agents or vertical plugins. A directory under plugins/ may also be zipped and uploaded. The source does not document a standalone installation command for this skill.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/anthropics/financial-services.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/plugins/partner-built/lseg/skills/macro-rates-monitor" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Build a US macro-rates dashboard with the latest GDP, core inflation, unemployment, PMI, 3M/2Y/5Y/10Y/30Y Treasury yields, 5Y and 10Y real rates, and 2Y/5Y/10Y swap spreads, then provide an overall assessment.
After installing the LSEG vertical plugin that contains the skill, use a prompt such as: "Build a US macro-rates dashboard with the latest GDP, core inflation, unemployment, PMI, 3M/2Y/5Y/10Y/30Y Treasury yields, 5Y and 10Y real rates, and 2Y/5Y/10Y swap spreads, then provide an overall assessment." Appropriate MCP data access is required.
What are this skill's strengths and limitations?
- Covers macro indicators, yield curves, inflation expectations, real rates, swap spreads, and historical context.
- Defines a clear multi-stage tool-chaining workflow and structured output format.
- Supports macroeconomic series across multiple countries and frequencies.
- Requires LSEG MCP tools and associated data access; the README notes that provider subscriptions or API keys may be required.
- Specifies an analytical workflow but provides no sample dataset or validation results.
- The source provides no test-suite or platform-testing evidence for this individual skill.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Macro & Rates Monitor this page ✓ Anthropic · Official | 45 · Not recommended | ★ 40k | 1mo ago | Apache-2.0 |
| Swap Curve Strategy Analyst ✓ Anthropic · Official | 42 · Not recommended | ★ 40k | 1mo ago | Apache-2.0 |
| Equity Research Snapshot ✓ Anthropic · Official | 46 · Use with care | ★ 40k | 1mo ago | Apache-2.0 |
| Bond Relative Value Analyst ✓ Anthropic · Official | 41 · Not recommended | ★ 40k | 1mo ago | Apache-2.0 |
| FX Carry Trade Analyst ✓ Anthropic · Official | 40 · Not recommended | ★ 40k | 1mo ago | Apache-2.0 |
How did FollowSkills review this skill?
The skill describes read-oriented retrieval of macro and rates data followed by synthesis, with no evidence of malware, credential theft, or destructive actions, supporting a baseline score. It does not specify least privilege, user confirmation, sensitive-data handling, data-flow boundaries, rollback, or result attribution, and it depends on external MCP services, so substantial points are deducted.
The workflow is internally coherent and identifies two-phase calls for several tools, making the happy path plausible. However, it lacks parameter schemas, reproducible examples, abnormal-input handling, diagnosable failure feedback for unavailable services, and key-path test evidence, so the static score remains moderate and below the execution-based ceiling.
The intended audience and scenarios—cycle analysis, curve shape, real rates, policy expectations, and financial conditions—are clear, and patterns are provided for the US, Eurozone, and UK. Non-fit boundaries, exclusion triggers, broader country coverage, Chinese-language support, and mainland-China reachability are unspecified; LSEG access may also require a subscription, so points are deducted.
The skill has clear sections for principles, tools, workflow, search patterns, and output templates. The README adds installation guidance, an MCP subscription caveat, Apache-2.0 licensing, and repository maintenance checks, but the skill lacks its own versioning, changelog, ownership, update path, troubleshooting, and known-limitations disclosure.
The skill covers the core path from data retrieval to a macro-rates dashboard and defines directly usable tables and an assessment format. Static source review provides no real outputs or execution verification, while series matching, units, timestamps, missing data, and calculation correctness still require manual review, limiting evidence of marginal benefit.
The selected skill, README, license, and repository CI are auditable primary materials, and CI includes plugin validation and secret scanning. Those checks do not exercise the skill's MCP data paths, and there is no committed test suite, third-party execution record, or corroborating source evidence, so only limited points are justified.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →