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 skills/matthewdigiuseppe/mstack/hypothesis-designnpx skills add matthewdigiuseppe/MStack --skill hypothesis-designgit clone --depth 1 https://github.com/matthewdigiuseppe/MStackWrote 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/matthewdigiuseppe/mstack/hypothesis-design)<a href="https://agentmods.dev/skills/matthewdigiuseppe/mstack/hypothesis-design"><img src="https://agentmods.dev/badge/skills/matthewdigiuseppe/mstack/hypothesis-design.svg" alt="Measured on agentmods" 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 | $0.00063 | $0.00722 |
| Opus 5 | $0.00032 | $0.00361 |
| Sonnet 5 | $0.00013 | $0.00144 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
hypothesis-design 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 4d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/mstack:hypothesis-design
Stage: map Voice: methodologist
When to invoke
After /mstack:theory-build. Before fielding or analyzing. Before /mstack:preregister (the prereg quotes these hypotheses).
Procedure
-
Load.
.mstack/theory.md,.mstack/lit-map.md. -
For each hypothesis (H1, H2, …), specify all six fields:
Field Example Statement "Higher exposure to import competition increases vote share for protectionist parties." Direction Positive (β > 0). Effect-size sign + magnitude expectation "We expect a 1-SD increase in exposure to raise vote share by 1–3 percentage points." Operationalization of X "Exposure = ADH-style instrument constructed as in Autor et al. 2013, country-region-year level." Operationalization of Y "Vote share = percent of constituency vote for parties classified as protectionist by CMP." Falsification pattern "A null result (β CI overlapping zero) at the country-region-year level falsifies H1. A negative coefficient (β < 0) falsifies the mechanism direction." -
Falsifiability check. For each hypothesis:
- Could a result actually falsify it, or is the prediction "X has some relationship with Y"? Reject vague directions.
- Is the falsification pattern observable with the planned data? If the data can't produce the falsifying pattern, the hypothesis is unfalsifiable in this design.
-
Primary vs. secondary. Mark exactly one hypothesis as primary. The primary is what the paper's headline rests on. Secondaries explore mechanism, heterogeneity, or scope but don't carry the headline.
-
Heterogeneity / moderation. If moderation is theorized, specify it as its own hypothesis (e.g., "H2: The effect of X on Y is larger in subset S because Z"). Heterogeneity tests not pre-specified here are exploratory in the prereg.
-
Save to
.mstack/hypotheses.md. The prereg pulls from this file.
Outputs
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.
- 4d ago First seen · 57 lines · 63 tokens per session scan A 1c3fe43b569d
hypothesis-design is a skill published in the GitHub repository matthewdigiuseppe/MStack (14 stars, last pushed 8d ago), licensed MIT. It adds 63 tokens to every session and 722 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 2026-08-30.
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