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 Neeeophytee/finding-unknowns-skills --skill assumption-testgit clone --depth 1 https://github.com/Neeeophytee/finding-unknowns-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/neeeophytee/finding-unknowns-skills/assumption-test)<a href="https://agentmods.dev/skills/neeeophytee/finding-unknowns-skills/assumption-test"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/assumption-test/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/neeeophytee/finding-unknowns-skills/assumption-test"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/assumption-test.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 | $0.00050 | $0.00456 |
| Opus 5 | $0.00025 | $0.00228 |
| Sonnet 5 | $0.00010 | $0.00091 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
assumption-test 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 2d 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 — 24 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assumption test
A plausible assumption can survive every planning conversation and still fail on contact with the system. Turn the consequential uncertainty into a question an experiment can answer.
Steps
- Read the request, relevant code, and existing evidence. If inspection already settles the question, cite that evidence and stop; do not manufacture an experiment. If several assumptions remain, select the one whose failure would most change the approach.
- State the assumption as an observable prediction. Define what would refute it, what would support it within the tested scope, and what would leave it inconclusive. Set those criteria before observing the result.
- Design the smallest discriminating experiment. Use an isolated fixture or test environment, the real component under question where available, and a bounded number of operations. Name what the setup cannot represent; a mock's behavior is not evidence about its provider.
- Run the experiment within the user's authorized scope. Preserve the command, relevant inputs, actual output, and environment details needed to reproduce it. If a tool or dependency is unavailable, report the experiment as unrun or inconclusive, with the missing prerequisite.
- Close with the assumption, method, observation, verdict (supported within scope, refuted, or inconclusive), and the planning decision this evidence changes. Recommend the next discriminating check only if it could change that decision. Keep temporary code separate from the production implementation.
Guardrails
- One successful trial does not establish a universal claim. State the tested conditions and remaining uncertainty, particularly for concurrency and performance.
- Do not use production writes, real payments, destructive operations, or newly incurred costs without authorization. An experiment does not grant additional permissions.
- Distinguish the component failing from the experiment failing to run. Never turn missing access or a broken fixture into a verdict about the system.
- Do not fix the implementation or broaden into a build unless the user requested it. The deliverable is evidence that informs a decision.
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.
- 2d ago First seen · 24 lines · 50 tokens per session scan A 65aae0c9f8e8
assumption-test is a skill published in the GitHub repository Neeeophytee/finding-unknowns-skills (329 stars, last pushed 3d ago), licensed MIT. It adds 50 tokens to every session and 456 once invoked, about $0.0003 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 2026-09-09.
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