/analyze-bond-rv
Analyze a bond's relative value vs yield curves and credit spreads with scenario stress testing
> /plugin marketplace add anthropics/financial-servicesHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/analyze-bond-rv
Context preview
What this command does when you run it.
Analyze a bond's relative value vs yield curves and credit spreads with scenario stress testing
Command definition
analyze-bond-rv.mddescription: Analyze a bond's relative value vs yield curves and credit spreads with scenario stress testing
argument-hint: "<ISIN, RIC, or CUSIP> [vs benchmark]"
Analyze Bond Relative Value
> This command uses LSEG bond pricing, yield curves, credit curves, and scenario analysis tools. See [CONNECTORS.md](../CONNECTORS.md) for available tools.
Perform relative value analysis on one or more bonds by combining pricing analytics, yield curve context, credit spread decomposition, and rate shock scenarios.
See the **bond-relative-value** skill for domain knowledge on spread frameworks and rich/cheap assessment.
Workflow
1. Gather Bond Identifiers
Ask the user for:
- Bond identifier(s) — ISIN, RIC, or CUSIP (required)
- Optional benchmark bond for comparison
- Valuation date (optional, defaults to today)
2. Price the Bond(s)
Call `bond_price` with the identifier(s).
Extract: clean/dirty price, yield, duration, convexity, DV01, currency.
If benchmark provided, price that too.
3. Get the Risk-Free Yield Curve
Call `interest_rate_curve` (list then calculate) for the bond's currency.
Interpolate at the bond's maturity to compute G-spread.
4. Get the Credit Spread Curve
Call `credit_curve` (search by country/issuerType, then calculate).
Compute residual spread = bond G-spread minus credit curve spread at matching maturity. Positive residual = cheap; negative = rich.
5. Run Scenario Analysis
Call `yieldbook_scenario` with parallel rate shifts: -100bp, -50bp, 0bp, +50bp, +100bp.
Extract price change and P&L under each scenario.
6. Synthesize the Report
Present: bond summary table, spread decomposition (G-spread, credit spread, residual), scenario P&L table, and rich/cheap assessment.
If benchmark provided, include side-by-side comparison.
Output Format
Lead with the rich/cheap assessment and supporting evidence. Follow with spread decomposition and scenario tables.
Read more
description: Analyze a bond's relative value vs yield curves and credit spreads with scenario stress testing argument-hint: "<ISIN, RIC, or CUSIP> [vs benchmark]"
Analyze Bond Relative Value
> This command uses LSEG bond pricing, yield curves, credit curves, and scenario analysis tools. See [CONNECTORS.md](../CONNECTORS.md) for available tools.
Perform relative value analysis on one or more bonds by combining pricing analytics, yield curve context, credit spread decomposition, and rate shock scenarios.
See the **bond-relative-value** skill for domain knowledge on spread frameworks and rich/cheap assessment.
Workflow
1. Gather Bond Identifiers
Ask the user for:
- Bond identifier(s) — ISIN, RIC, or CUSIP (required)
- Optional benchmark bond for comparison
- Valuation date (optional, defaults to today)
2. Price the Bond(s)
Call `bond_price` with the identifier(s).
Extract: clean/dirty price, yield, duration, convexity, DV01, currency.
If benchmark provided, price that too.
3. Get the Risk-Free Yield Curve
Call `interest_rate_curve` (list then calculate) for the bond's currency.
Interpolate at the bond's maturity to compute G-spread.
4. Get the Credit Spread Curve
Call `credit_curve` (search by country/issuerType, then calculate).
Compute residual spread = bond G-spread minus credit curve spread at matching maturity. Positive residual = cheap; negative = rich.
5. Run Scenario Analysis
Call `yieldbook_scenario` with parallel rate shifts: -100bp, -50bp, 0bp, +50bp, +100bp.
Extract price change and P&L under each scenario.
6. Synthesize the Report
Present: bond summary table, spread decomposition (G-spread, credit spread, residual), scenario P&L table, and rich/cheap assessment.
If benchmark provided, include side-by-side comparison.
Output Format
Lead with the rich/cheap assessment and supporting evidence. Follow with spread decomposition and scenario tables.
Reference agents, skills, and data connectors for the financial-services workflows we see most — investment banking, equity research, private equity, and wealth management.
Other commands on financial-services.
- /access-policies
Build the access_policies value — the granular, IAM-shaped way to allow or deny add-in features
Open command - /bootstrap
Build the bootstrap endpoint — per-user MCP servers, skills, dynamic config
Open command - /consent
Azure admin consent URLs — one-time tenant approval for Entra SSO and Outlook Graph access
Open command - /debug
Diagnose deployment issues (stale config, connect failures, missing add-in)
Open command - /entra-app
Several manifest configurations require an Entra (Azure AD) app registration in **your** tenant rather than Anthropic's default multi-tenant app — because the token's `aud` must match a resource you control, or because your tenant is in a sovereign cloud where Anthropic's app
Open command - /export-data
Export a copy of a user's add-in chat history, skills, MCP registrations, and settings before a machine is rebuilt
Open command

