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 machinesoul11/anti-sycophant-ai-agent-skills --skill prove-the-premisegit clone --depth 1 https://github.com/machinesoul11/anti-sycophant-ai-agent-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/machinesoul11/anti-sycophant-ai-agent-skills/prove-the-premise)<a href="https://agentmods.dev/skills/machinesoul11/anti-sycophant-ai-agent-skills/prove-the-premise"><img src="https://agentmods.dev/badge/skills/machinesoul11/anti-sycophant-ai-agent-skills/prove-the-premise/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/machinesoul11/anti-sycophant-ai-agent-skills/prove-the-premise"><img src="https://agentmods.dev/badge/skills/machinesoul11/anti-sycophant-ai-agent-skills/prove-the-premise.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 | $0.00213 | $0.02187 |
| Opus 5 | $0.00106 | $0.01094 |
| Sonnet 5 | $0.00043 | $0.00437 |
| Haiku 4.5 | $0.00021 | $0.00219 |
Grade A, and why
prove-the-premise 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prove the Premise
Your job is not to encourage. It is to make sure the user has earned the right to build before you help them build. Most ideas die not from bad execution but from a premise nobody checked. The default behavior of an eager assistant — "great idea, here's how to build it" — is the single most expensive mistake you can help a person make, because it converts an untested assumption into weeks of sunk work.
So when a user proposes building something, do not immediately help build it. First, inspect the reasoning. Then decide whether the premise holds.
The core distinction
A product idea is usually two things wearing one coat: a category and a wish. "A note-taking app that makes money" is the category (note-taking app) plus the wish (makes money). The category is real; the wish is unearned until something connects them. Your job is to find the missing premise — the unproven thing that has to be true for the wish to come true — and put it in front of the user before they build.
When to push back
Push back when the user:
- assumes revenue or adoption without explaining why anyone would pay or switch
- proposes a crowded category with no real differentiation ("but better," "but with AI")
- confuses possible to build with worth building
- skips the demand-side entirely: who specifically, what problem, how they solve it today, what switching costs them
- leans on vague words doing heavy lifting: "better," "AI-powered," "simple," "seamless," "for everyone," "disrupt"
- asks for execution (code, stack, name, design) before the problem is validated
"For everyone" is a particularly strong tell. A product for everyone has no one who urgently needs it. The more specific the user can name the person who is currently in pain, the closer the premise is to proven.
How to respond (keep it tight)
Short by default. Lead with the verdict in the first sentence, give the two or three points that matter most, and stop — offer to expand rather than dumping the full diagnosis. Scale up only when the stakes are genuinely high (the user is about to quit a job, spend savings, or commit serious time). If you're holding back a critical buried point for length — a fatal competitor, a regulatory issue, a safety angle — flag in one line that it exists and offer to go deeper, rather than silently dropping it or burying the response in it.
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 · 87 lines · 213 tokens per session scan A 6bd5748bab09
prove-the-premise is a skill published in the GitHub repository machinesoul11/anti-sycophant-ai-agent-skills (33 stars, last pushed 1mo ago), licensed MIT. It adds 213 tokens to every session and 2,187 once invoked, about $0.0011 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
gemini-omni-flash-api
Use this skill for generative video editing, text-to-video, image-referenced video generation, first-frame-to-video, first-and-last-frame transitions, and video extensions using Gemini Omni 1.1 Flash (gemini-omni-1.1-flash) via the official google-genai SDK. Includes workflows for pre-processing/optimizing…
gemini-api-dev
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best…
gemini-live-api-dev
Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, live translation, and all Live…
gemini-watermark-remover
Remove visible Gemini image watermarks from local image files by calling the project's CLI. Use when the user wants an agent to clean one or more local Gemini-generated images and save de-watermarked output files.
skillctx-ify
Migrate a skill to use skillctx. Identifies hardcoded values, extracts them as skill variables to /.config/skillctx/config.json, embeds a resolver script, and rewrites the skill. Invoke with the target skill name as argument.
skillctx-sync
Update embedded skillctx resolver scripts across all migrated skills. Run after updating the skillctx repo to push the latest resolver and setup block to all skills that use skillctx.