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 commands/yuping322/financial-services-plugins-new/compsgit clone --depth 1 https://github.com/yuping322/financial-services-plugins-newWrote 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/commands/yuping322/financial-services-plugins-new/comps)<a href="https://agentmods.dev/commands/yuping322/financial-services-plugins-new/comps"><img src="https://agentmods.dev/badge/commands/yuping322/financial-services-plugins-new/comps.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 | $0.00008 | $0.01118 |
| Opus 5 | $0.00004 | $0.00559 |
| Sonnet 5 | $0.00002 | $0.00224 |
| Haiku 4.5 | $0.00001 | $0.00112 |
Grade A, and why
comps 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparable Company Analysis Command
Build an institutional-grade comparable company analysis with operating metrics, valuation multiples, and statistical benchmarking.
Workflow
Step 1: Gather Company Information
If a company name or ticker is provided, use it. Otherwise ask:
- "What company would you like to analyze?"
Step 2: Load Comps Analysis Skill
Use skill: "comps-analysis" to build the analysis:
-
Clarify the analysis purpose:
- "What's the key question?" (valuation, efficiency, growth comparison)
- "Who is the audience?" (IC, board, quick reference)
- "Do you have a preferred format or template?"
-
Identify peer group (4-6 comparable companies):
- Similar business model
- Similar scale/market cap range
- Same industry/sector
- Geographic comparability
-
Gather data (prioritize MCP sources if available):
- Operating metrics: Revenue, Growth, Gross Margin, EBITDA, EBITDA Margin
- Valuation: Market Cap, Enterprise Value, EV/Revenue, EV/EBITDA, P/E
- Additional metrics based on industry (Rule of 40 for SaaS, etc.)
-
Build the analysis:
- Operating Statistics section with company data + statistics (Max, 75th, Median, 25th, Min)
- Valuation Multiples section with same statistical summary
- Notes & Methodology documentation
Step 3: Create Excel Output
Generate Excel file with:
- Header block (analysis title, companies, date, units)
- Operating Statistics & Financial Metrics section
- Valuation Multiples section
- Statistical summary for each metric
- Notes section documenting sources and methodology
Step 4: Deliver Output
Provide:
- Excel file (.xlsx) - the comps analysis
- Summary highlighting:
- Peer group selection rationale
- Key insights (who trades at premium/discount)
- Median multiples for reference
Output Format Reference
┌─────────────────────────────────────────────────────────────────┐
│ [SECTOR] - COMPARABLE COMPANY ANALYSIS │
│ [Company 1] • [Company 2] • [Company 3] • [Company 4] │
│ As of [Date] | All figures in USD Millions │
├─────────────────────────────────────────────────────────────────┤
│ OPERATING STATISTICS & FINANCIAL METRICS │
├──────────┬─────────┬─────────┬──────────┬─────────┬────────────┤
│ Company │ Revenue │ Growth │ Gross │ EBITDA │ EBITDA │
│ │ (LTM) │ (YoY) │ Margin │ (LTM) │ Margin │
├──────────┼─────────┼─────────┼──────────┼─────────┼────────────┤
│ [Data rows for each company] │
│ │
│ Maximum │ =MAX │ =MAX │ =MAX │ =MAX │ =MAX │
│ 75th % │ =QUART │ =QUART │ =QUART │ =QUART │ =QUART │
│ Median │ =MEDIAN │ =MEDIAN │ =MEDIAN │ =MEDIAN │ =MEDIAN │
│ 25th % │ =QUART │ =QUART │ =QUART │ =QUART │ =QUART │
│ Minimum │ =MIN │ =MIN │ =MIN │ =MIN │ =MIN │
├─────────────────────────────────────────────────────────────────┤
│ VALUATION MULTIPLES │
├──────────┬──────────┬──────────┬──────────┬───────────┬────────┤
│ Company │ Mkt Cap │ EV │ EV/Rev │ EV/EBITDA │ P/E │
├──────────┼──────────┼──────────┼──────────┼───────────┼────────┤
│ [Data rows + statistics] │
└─────────────────────────────────────────────────────────────────┘
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 · 110 lines · 8 tokens per session scan A 88a71a5c60a7
comps is a command published in the GitHub repository yuping322/financial-services-plugins-new (17 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 1,118 once invoked, about $0.0000 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.
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