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 EliasOulkadi/shokunin --skill business-proposalsgit clone --depth 1 https://github.com/EliasOulkadi/shokuninWrote 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/eliasoulkadi/shokunin/business-proposals)<a href="https://agentmods.dev/skills/eliasoulkadi/shokunin/business-proposals"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/business-proposals/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/eliasoulkadi/shokunin/business-proposals"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/business-proposals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00000 | $0.02626 |
| Opus 5 | $0.00000 | $0.01313 |
| Sonnet 5 | $0.00000 | $0.00525 |
| Haiku 4.5 | $0.00000 | $0.00263 |
Grade A, and why
business-proposals 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 13d 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Business Proposals v3.0
Win deals and raise funding. Covers the full pipeline: outreach, proposals, and pitch decks.
Workflow
When the user asks for any sales document, follow this process:
- Clarify stage: Outreach (cold) → Proposal (warm) → Pitch deck (investor)? Ask if unclear.
- Gather context: Run discovery questions for the specific stage (sections below).
- Select template: Match the deliverable to the appropriate structure below.
- Draft: Fill template with user-provided info. Use placeholders
[like this]for unknowns. - Review: Check against error handling table and production checklist.
- Verify anti-patterns: Scan the anti-patterns table — if any match, fix before delivery.
- Output: Return the completed document in the requested format (text, markdown, email body).
Sales Outreach
Required Discovery
- Prospect: Company + person + role
- Trigger: Why now? (funding, product launch, job change)
- Value prop: "We help [X] do [Y] so they can [Z]"
- Proof: Case study, testimonial, data point, mutual connection
- Goal: Reply? Call? Demo? Trial?
Cold Email Structure
- Subject: Personalized + curiosity gap. 10 words max.
- Opening: Specific reference to them (news, post, achievement)
- Value prop: One sentence. Their benefit, not your features.
- Proof: Social proof or relevant data point.
- Ask: Single, low-friction next step.
- Close: Simple. "Best, [Name]"
Subject Line Patterns
| Pattern | Example |
|---|---|
| Reference | "[Company] + [observation]" |
| Question | "Quick question about [situation]" |
| Compliment | "Impressed by [achievement]" |
| Mutual connection | "[Name] suggested I reach out" |
Personalization Levels (ALL required)
- Company: Recent news, funding, launch
- Person: Recent post, talk, job change, GitHub activity
- Fit: Why this matters to THEM specifically
If you cannot do level 2, do not send the email.
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.
- 13d ago First seen · 260 lines · 0 tokens per session scan A fb3ea4395a3c
business-proposals is a skill published in the GitHub repository EliasOulkadi/shokunin (113 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,626 tokens. 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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refresh
Use when an existing contextualizer's references may have drifted from current upstream state — typically weekly, or whenever a few days of upstream changes have accumulated — to bring them back into agreement.
apply
Use when a staged proposal has been reviewed and signed off — REVIEW.md Step 3 ticked reviewed or provisional — and is ready to promote into the live contextualizer.
config-set
Use when changing an engine-wide config value — currently diff.tool, the command /skill-engine:review prints for inspecting a proposed-vs-live diff.