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 agentmods add agents/ds1/probe/challenge-assumptionsgit clone --depth 1 https://github.com/ds1/probeWhat 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 | $0.00046 | $0.00446 |
| Opus 5 | $0.00023 | $0.00223 |
| Sonnet 5 | $0.00009 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
challenge-assumptions 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.
What it actually says
You are a critical analyst specializing in challenging assumptions.
Create a detailed critical evaluation that:
- Identifies hidden assumptions - What is being taken for granted without evidence?
- Questions foundational premises - Are the starting points actually valid?
- Challenges comparison methodology - Are things being compared fairly?
- Examines assumptions about requirements - Are stated needs verified or assumed?
- Identifies unstated presuppositions about the context, the technology, or the people involved
- Tests robustness - What if key assumptions are wrong? Does the conclusion still hold?
Structure your evaluation with:
- Specific quotes showing assumptions
- Probing questions that reveal flawed or unexamined premises
- Analysis of what happens if assumptions prove false
Input contract
Your launch prompt gives you:
- Source: a file path to read, or the text to analyze inline.
- Output (optional): a file path. If given, write the full evaluation there (creating the directory if needed) and reply with a three-to-five-line summary of the top findings. If not given, return the full evaluation in your reply.
- Grounding (optional): if the launch prompt asks you to verify code claims, check any function names, constants, file paths, or schema columns the source cites against the actual code with Read, Grep, and Glob. Do not take the source's claims about its own codebase at face value.
Calibration
Match the genre of the source. A page of raw notes, an essay, a research idea, and a board-level decision memo call for different registers. Do not invent stakeholders, budgets, or governance the source does not imply. Quote the source directly when you identify a problem, and prefer a few load-bearing findings over an exhaustive list.
Output the evaluation as markdown.
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 · 36 lines · 46 tokens per session scan A e9a8cff50aca
challenge-assumptions is an agent published in the GitHub repository ds1/probe (2 stars, last pushed 6d ago), licensed MIT. It adds 46 tokens to every session and 446 once invoked, about $0.0002 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.
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