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 KirKruglov/claude-skills-kit --skill proposal-and-quote-draftergit clone --depth 1 https://github.com/KirKruglov/claude-skills-kitWrote 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/kirkruglov/claude-skills-kit/proposal-and-quote-drafter)<a href="https://agentmods.dev/skills/kirkruglov/claude-skills-kit/proposal-and-quote-drafter"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/proposal-and-quote-drafter/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/kirkruglov/claude-skills-kit/proposal-and-quote-drafter"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/proposal-and-quote-drafter.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00104 | $0.01684 |
| Opus 5 | $0.00052 | $0.00842 |
| Sonnet 5 | $0.00021 | $0.00337 |
| Haiku 4.5 | $0.00010 | $0.00168 |
Grade A, and why
proposal-and-quote-drafter 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 12d 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proposal and Quote Drafter
This skill turns raw notes from a discovery call or client brief into a complete, client-ready proposal: executive summary, scope, deliverables, timeline, three pricing packages, and a cover letter. It always outputs a human-review checklist so you catch pricing errors, wrong names, and unrealistic timelines before sending.
Input:
- Unstructured notes from a discovery call or client brief (pasted as text, any format, RU or EN)
Output:
- Full proposal document (Markdown)
- Cover letter (email-ready text block, 5–7 sentences)
- Human-review checklist (≥4 checkbox items)
Language Detection
Detect the user's language from their message:
- If Russian (or contains Cyrillic): respond in Russian
- If English (or other Latin-script language): respond in English
- If ambiguous: respond in the language of the trigger phrase used
Instructions
Step 1: Validate Input
-
Check that the user has provided discovery notes or a brief.
- If input is empty or fewer than 5 words: stop. Return: "Notes are too sparse to build a proposal. Please describe at least: client name, project problem, and proposed solution."
- If input looks like an already-formatted proposal (contains existing section headers like "## Scope" or "## Pricing"): flag. Return: "This looks like an existing proposal. For revision, describe what to change. This skill generates from raw notes, not from existing documents." Stop.
-
Detect output language.
- If the user's notes are predominantly in Russian → respond in Russian.
- If the user explicitly requests a language (e.g., "in English" or "на русском") → use that language regardless of notes language.
- Default: match the dominant language of the notes.
Step 2: Parse Notes
Extract the following from the raw notes:
- Client information: client name (company or individual), contact name if mentioned.
- Project type: what kind of service or product is being proposed (e.g., website redesign, marketing campaign, consulting engagement).
- Pain points / problem: what the client wants to solve or achieve.
- Deliverables: specific outputs, features, or services mentioned explicitly or implied.
- Timeline: deadlines, milestones, or constraints mentioned. If none found → note as [TIMELINE].
- Budget signals: pricing, ranges, or constraints mentioned. If none found → mark as [PRICE] and proceed to Step 3.
What ships with it
4 files 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.
- 12d ago First seen · 165 lines · 104 tokens per session scan A 6b39cb65d326
proposal-and-quote-drafter is a skill published in the GitHub repository KirKruglov/claude-skills-kit (18 stars, last pushed 1mo ago), licensed MIT. It adds 104 tokens to every session and 1,684 once invoked, about $0.0005 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.
Other skills, from other repositories
spark-video-director
Translate a screenplay (one scene at a time) into a provider-agnostic storyboard fragment for the spark-video pipeline. Wraps Shanyin Super Director Master when available — the upstream Shanyin SKILL is the single source of truth for craft when present.
spark-video-episode
One-shot autopilot orchestrator — runs the full spark-video pipeline (screenwriter ↔ director per-scene parallel → render chain-DAG parallel + per-clip review → stitch). User confirms at 4 gates (+ 1 mode gate at start + 1 BGM gate when bgm/ folder detected). Use when the user wants "make me an episode" in one command.
vox-video-director
Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end with Aliyun Bailian CLI + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage"…
task-observer
Monitors task execution for skill improvement opportunities. Use during ANY multi-step task, agentic workflow, or work session where the agent uses tools and produces deliverables. Captures patterns, user corrections, workflow insights, and methodology worth preserving as reusable skills. Also triggers in post-task…
bailian-train-deploy
A workflow for using Alibaba Cloud’s Bailian command-line tool to fine-tune or directly deploy AI models as callable services. It covers text, speech-synthesis, image-generation, and video-generation models.
spark-video-cast
Scaffold and generate reference assets for characters (cast), locations (movie-set / set dressing), and key props — the three pillars of visual consistency in spark-video. Wraps bl image generate / edit for portrait creation. Use when adding new characters/locations/props or when costume/state changes are needed.