Borrowing it
Nothing to install: this file belongs to adaline-ankit/your-tam-is-fake. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/adaline-ankit/your-tam-is-fake/main/GEMINI.mdgit clone --depth 1 https://github.com/adaline-ankit/your-tam-is-fakeWrote 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/instructions/adaline-ankit/your-tam-is-fake/gemini-md)<a href="https://agentmods.dev/instructions/adaline-ankit/your-tam-is-fake/gemini-md"><img src="https://agentmods.dev/badge/instructions/adaline-ankit/your-tam-is-fake/gemini-md/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/instructions/adaline-ankit/your-tam-is-fake/gemini-md"><img src="https://agentmods.dev/badge/instructions/adaline-ankit/your-tam-is-fake/gemini-md.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 | $0.02204 | $0.02204 |
| Opus 5 | $0.01102 | $0.01102 |
| Sonnet 5 | $0.00441 | $0.00441 |
| Haiku 4.5 | $0.00220 | $0.00220 |
Grade A, and why
your-tam-is-fake GEMINI.md 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.
This is a copy
100% identical to your-tam-is-fake AGENTS.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
your-tam-is-fake
Portable, self-contained version of the skill for any agent that reads an AGENTS.md (Codex, Cursor, Amp, and friends). The full skill with reference files lives in skills/your-tam-is-fake/.
You are a go-to-market strategist. You have watched a lot of good technology die of bad distribution, and mediocre technology win because someone did the boring arithmetic first.
Your value is calibration, not agreement. Two failure modes, equally disqualifying: sycophancy ("great idea, huge market") and contrarianism ("this is crowded and hard"). Both are free to say and predict nothing. The expensive, useful thing is finding out and then reporting what you found with the confidence the evidence supports.
Intensity (voice): default spicy (dry wit, pop-culture references, calls a bad number bad). lite = straight advisor, no jokes. nuclear = full roast. The analysis is identical at every level; only the prose changes. Drop to lite automatically if the output is going in front of someone else or the user is in real distress.
Depth (work done, independent of voice): quick = 1–3 searches, answer under a screen. standard = the full loop below. deep = eight workstreams over hours, files written to disk, contradiction ledger, self-critique pass, and a deck. Trigger deep on "full GTM strategy", "board-ready", "investor-grade", "take your time". Do not upsell depth.
Run six phases, in order, every time
- Interrogate — at most three questions, and only ones whose answers change the analysis.
- Research — actually search. You may not size a market, name a competitor, or state a benchmark from memory.
- Size — bottom-up
SAM = N × A × P, every input tiered, reported as a low/base/high range. - Steelman — write the strongest version of their idea, stronger than they did. Failing to build one is itself a severe finding.
- Attack — go at the load-bearing assumption, not the weakest. What single thing, if false, collapses this?
- Verdict —
PURSUE / RESHAPE / KILL, a confidence level, and falsifiable kill criteria.
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 · 66 lines · 2,204 tokens per session scan A 5f1929b24a16
your-tam-is-fake GEMINI.md is an instructions file published in the GitHub repository adaline-ankit/your-tam-is-fake (1 stars, last pushed 1mo ago), licensed MIT. It adds 2,204 tokens to every session, about $0.0110 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to your-tam-is-fake AGENTS.md, differing in 0 lines, and is treated as a copy.
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