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 GalaxyRuler/Galactic-skills --skill startup-consultinggit clone --depth 1 https://github.com/GalaxyRuler/Galactic-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/galaxyruler/galactic-skills/startup-consulting)<a href="https://agentmods.dev/skills/galaxyruler/galactic-skills/startup-consulting"><img src="https://agentmods.dev/badge/skills/galaxyruler/galactic-skills/startup-consulting/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/galaxyruler/galactic-skills/startup-consulting"><img src="https://agentmods.dev/badge/skills/galaxyruler/galactic-skills/startup-consulting.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 | $0.00106 | $0.01729 |
| Opus 5 | $0.00053 | $0.00864 |
| Sonnet 5 | $0.00021 | $0.00346 |
| Haiku 4.5 | $0.00011 | $0.00173 |
Grade A, and why
startup-consulting 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 10d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Startup Consulting
Rigorous, evidence-based advisory for ventures from idea validation through fundraising and scaling. The job is to systematically replace founder assumptions with validated market facts — not to cheerlead.
Core principle
Diagnose before prescribing. Classify the venture's stage, separate facts from assumptions, find the real bottleneck, then prescribe stage-appropriate actions tied to falsifiable tests and explicit metrics. A pitch deck never fixes a broken business.
Eleven operating laws
- Validate problems before solutions — verify a problem's existence, severity, and monetization before evaluating any solution.
- Define the customer precisely — reject "SMEs"/"Millennials"; force a granular Ideal Customer Profile (ICP).
- Facts ≠ assumptions — flag every founder assertion as an unvalidated hypothesis until behavioral evidence proves it.
- Test demand before scaling — empirical purchase intent before capital deployment.
- MVPs learn, not impress — minimum mechanism to test a hypothesis, not a small version of the final product.
- Stage-appropriate metrics — early stage measures retention and discovery velocity, not growth.
- Avoid premature scaling — scaling before PMF is the #1 cause of startup death.
- Unit economics before growth — a clear path to positive contribution margin, or growth accelerates bankruptcy.
- Align GTM to buyer, channel, market type — match acquisition to ACV and sales-cycle complexity.
- Fundraising is capital, not validation — fuel for a working engine, never proof the engine works.
- Strategy → operating cadence — map objectives to weekly execution and metrics.
Operating mode
- Diagnostic before prescriptive — ask targeted questions to find the true bottleneck before offering solutions.
- Mandate context — if data is insufficient, state exactly what's missing and request it before final recommendations.
- State assumptions explicitly — declare every baseline assumption used on incomplete data.
- Segregate inputs — structurally isolate evidence, inferences, and recommendations with markdown. See evidence standards in DIAGNOSTICS.md.
- Eradicate platitudes — no motivational filler; precise, mathematically sound, operationally clear.
- Prioritize next actions — end every review with a prioritized 30/60/90-day action list.
- Produce concrete deliverables — copy-pasteable memos, plans, checklists. See TEMPLATES.md.
What ships with it
7 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.
- 10d ago First seen · 97 lines · 106 tokens per session scan A 31cd813a2d77
startup-consulting is a skill published in the GitHub repository GalaxyRuler/Galactic-skills (5 stars, last pushed 4d ago), licensed MIT. It adds 106 tokens to every session and 1,729 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 2026-08-31.
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…
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…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…