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 krillinai/growth-skills --skill growth-model-designgit clone --depth 1 https://github.com/krillinai/growth-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/krillinai/growth-skills/growth-model-design)<a href="https://agentmods.dev/skills/krillinai/growth-skills/growth-model-design"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/growth-model-design/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/krillinai/growth-skills/growth-model-design"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/growth-model-design.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 | $0.00032 | $0.02008 |
| Opus 5 | $0.00016 | $0.01004 |
| Sonnet 5 | $0.00006 | $0.00402 |
| Haiku 4.5 | $0.00003 | $0.00201 |
Grade A, and why
growth-model-design 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Model & Opportunity
Reuse Growth Context
At the start, read .agents/growth-context.md when it exists. Reuse only product, customer, market, outcome, constraint, evidence, and routing fields whose scope, definition, source, and date remain compatible; state what is reused and surface conflicts or staleness before asking for decision-changing gaps. The file grants no system access or execution authority, and this Skill must not silently rewrite the primary diagnosis.
Integrated Capabilities
This Skill consolidates adjacent workflows behind one trigger. Use the main workflow for core requests. When a request matches a module below, read that module before executing it:
Build an explicit, falsifiable explanation of how a defined customer reaches value, retains, creates a durable business outcome, and replenishes future growth inputs. Use equations and diagrams to expose assumptions, not to manufacture causality, certainty, or exponential forecasts.
Read model-contract.md before mapping entities, states, edges, time, evidence, economics, capacity, or model versions. Read modeling-methods.md before reconciling equations, running scenarios, testing sensitivity, or selecting a model constraint. Read output-contract.md before delivery. Use playbook-sources.md to cite the pinned Growth Playbook basis.
Select One Mode
| Mode | Use |
|---|---|
map |
Create a bounded current-state model and measurement contract |
audit |
Test an existing diagram, spreadsheet, equation, dashboard, or narrative for decision usefulness |
scenario |
Reconcile supplied compatible inputs and compare explicit assumption changes or ranges |
Name one primary mode, decision, owner, horizon, and permitted action. If private evidence is unavailable, complete a public-evidence-bounded hypothesis and calculation-ready specification rather than inventing coefficients.
What ships with it
13 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.
- agents/openai.yaml 255 B
- evals/evals.json 49 KB
- references/model-contract.md 4.3 KB
- references/modeling-methods.md 7.2 KB
- references/modules/growth-opportunity-sizing/references/opportunity-contract.md 3.8 KB
- references/modules/growth-opportunity-sizing/references/output-contract.md 3.6 KB
- references/modules/growth-opportunity-sizing/references/overlap-and-portfolio.md 3.2 KB
- references/modules/growth-opportunity-sizing/references/playbook-sources.md 1.6 KB
- references/modules/growth-opportunity-sizing/references/sizing-methods.md 4.5 KB
- references/modules/growth-opportunity-sizing/references/validation-and-governance.md 3.6 KB
- references/modules/growth-opportunity-sizing/SKILL.md 11 KB
- references/output-contract.md 3.2 KB
- references/playbook-sources.md 1.7 KB
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 · 107 lines · 32 tokens per session scan A bfff17d8a51c
growth-model-design is a skill published in the GitHub repository krillinai/growth-skills (43 stars, last pushed 16d ago), licensed MIT. It adds 32 tokens to every session and 2,008 once invoked, about $0.0002 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…