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 yuusakuri/agent-skills --skill identify-assumptions-existinggit clone --depth 1 https://github.com/yuusakuri/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/yuusakuri/agent-skills/identify-assumptions-existing)<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/identify-assumptions-existing"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/identify-assumptions-existing/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/yuusakuri/agent-skills/identify-assumptions-existing"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/identify-assumptions-existing.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 | $0.00058 | $0.00466 |
| Opus 5.5 | $0.00023 | $0.00186 |
| Sonnet 5.5 | $0.00012 | $0.00093 |
| Haiku 4.5 | $0.00006 | $0.00047 |
Grade A, and why
identify-assumptions-existing 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 2mo 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 identify-assumptions-existing — 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.
What it actually says
Identify Assumptions (Existing Product)
Devil's advocate analysis to surface risky assumptions across four risk areas.
Context
You are stress-testing a feature idea for $ARGUMENTS.
If the user provides files (designs, PRDs, research), read them first.
Instructions
The user will describe their product, objective, market segment, and feature idea. Work through these steps:
-
Think from three perspectives about why this feature might fail:
- Product Manager perspective: Business viability, market fit, strategic alignment
- Designer perspective: Usability, user experience, adoption barriers
- Engineer perspective: Technical feasibility, performance, integration challenges
-
Identify assumptions across four risk areas:
- Value: Will it create value for customers? Does it solve a real problem?
- Usability: Will users figure out how to use it? Is the learning curve acceptable?
- Viability: Can marketing, sales, finance, and legal support it?
- Feasibility: Can it be built with existing technology? Are there integration risks?
-
For each assumption, note:
- What specifically could go wrong
- How confident you are (High/Medium/Low)
- Suggested way to test it
Think step by step. Be thorough but constructive — the goal is to strengthen the idea, not kill it.
Further Reading
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.
- 2mo ago First seen · 45 lines · 58 tokens per session scan A 59d788213014
identify-assumptions-existing is a skill published in the GitHub repository yuusakuri/agent-skills (2 stars, last pushed 14d ago), licensed MIT. It adds 58 tokens to every session and 466 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to identify-assumptions-existing, differing in 0 lines, and is treated as a copy.
identify-assumptions-existing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| identify-assumptions-existingyuusakuri/agent-skills | Skill | 2 | 14d ago | MIT | A | 58 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |