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 skills add JoelLewis/finance_skills --skill proposal-generationgit clone --depth 1 https://github.com/JoelLewis/finance_skillsWrote 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/joellewis/finance_skills/proposal-generation)<a href="https://agentmods.dev/skills/joellewis/finance_skills/proposal-generation"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/proposal-generation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/joellewis/finance_skills/proposal-generation"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/proposal-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 5.1 | $0.00136 | $0.06539 |
| Opus 5 | $0.00068 | $0.03270 |
| Sonnet 5 | $0.00027 | $0.01308 |
| Haiku 4.5 | $0.00014 | $0.00654 |
Grade A, and why
proposal-generation 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 9d 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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proposal Generation
Core Concepts
Proposal Workflow Architecture
The investment proposal is the centerpiece of the advisory sales process. It translates a prospect's financial situation and goals into a specific, actionable investment recommendation. The end-to-end workflow proceeds through defined stages:
- Discovery meeting — the advisor meets with the prospect to understand their financial situation, goals, concerns, and expectations. The advisor collects current account statements, tax returns, and any existing financial plan. The discovery meeting establishes the advisory relationship's tone and sets expectations for the proposal.
- Data collection and organization — the advisor or operations team enters prospect data into the proposal system: personal information, current holdings (manually or via account aggregation), financial goals, time horizons, income, expenses, tax situation, and any unique circumstances (concentrated positions, restricted stock, estate planning needs).
- Risk profiling — the prospect completes a risk tolerance questionnaire. The system scores the responses and produces a risk profile that maps to a position on the firm's risk-return spectrum. The risk profile is the bridge between subjective client preferences and objective portfolio construction.
- Model portfolio selection — the risk profile score maps to a specific model portfolio from the firm's lineup. The advisor reviews the mapping, considers any client-specific factors that might warrant adjustment (tax sensitivity, income needs, ESG preferences, concentrated positions), and confirms the recommended model.
- Current portfolio analysis — if the prospect has existing investments, the system analyzes their current holdings: asset allocation, risk metrics, expense ratios, tax lots, concentrated positions, overlap, and style drift. This analysis quantifies the gap between the current portfolio and the recommended model.
- Proposal document generation — the system assembles the proposal document from templates, populating it with client-specific data, the recommended portfolio, fee schedule, projections, and disclaimers. The proposal document is the deliverable that the prospect reviews and uses to make their decision.
- Compliance review — before the proposal is presented, it undergoes supervisory review to verify suitability documentation, performance presentation compliance, fee disclosure adequacy, and proper disclaimers. For firms subject to the SEC Marketing Rule, proposals that include performance data require additional scrutiny.
- Presentation and discussion — the advisor presents the proposal to the prospect, walks through the analysis and recommendation, answers questions, and addresses concerns. The presentation meeting is where the advisory value proposition is demonstrated.
- Revision and finalization — based on the prospect's feedback, the advisor may revise the recommendation (different model, adjusted allocation, modified fee structure) and regenerate the proposal.
- Acceptance and onboarding — the prospect accepts the proposal by signing the advisory agreement (IMA or similar). The proposal data flows into the onboarding process: account opening, funding, and initial investment in the recommended model.
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.
- 9d ago First seen · 297 lines · 136 tokens per session scan A a4be08c49dca
proposal-generation is a skill published in the GitHub repository JoelLewis/finance_skills (184 stars, last pushed 1mo ago), licensed MIT. It adds 136 tokens to every session and 6,539 once invoked, about $0.0007 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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