hypothesize-and-design

hypothesize-and-design is a skill for Claude Code from airas-org/airas. It costs 55 tokens per session (1,464 once invoked), scanned A, original, MIT.

A research-planning workflow that turns prior studies into a testable hypothesis and a fixed experiment design. It defines the runs, measurements, models, datasets, and computing environment before execution.

In plain words
What is it for?
Use it to formulate hypotheses, choose research inputs, set expected result ranges, define metrics, and record what would disprove the hypothesis.
Why use it?
It removes ambiguity about what will be tested and how success or failure will be judged.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the airas plugin — 9 skills, 3 hooks, 1 MCP server shipped together

Good fit Use it to formulate hypotheses, choose research inputs, set expected result ranges, define metrics, and record what would disprove the hypothesis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/airas-org/airas/hypothesize-and-design
Install

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.

Any agent
npx skills add airas-org/airas --skill hypothesize-and-design
Clone the repo
git clone --depth 1 https://github.com/airas-org/airas

Made for: Claude Code.

Or install airas, the plugin that ships this one along with the rest of its 9 skills, 3 hooks, 1 MCP server.

Wrote 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.

agentmods badge for hypothesize-and-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/airas-org/airas/hypothesize-and-design/github.svg)](https://agentmods.dev/skills/airas-org/airas/hypothesize-and-design)
Your own site
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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.

agentmods 80×15 button for hypothesize-and-design

Your own site · 80×15
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Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,464 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.01464
Opus 5.5 $0.00022 $0.00586
Sonnet 5.5 $0.00011 $0.00293
Haiku 4.5 $0.00006 $0.00146

Measured 22d ago against content hash 4a7ea9706797, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

hypothesize-and-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 22d 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.

plugins/airas/skills/hypothesize-and-design/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hypothesize & design

Starts from the .research/sources/<id>/ that search-papers had CI fetch. This is a loop, not a pass: read, hypothesize, notice what the literature does not settle, go back to search-papers for it, and refine until the hypothesis rests on passages you have actually read.

  1. Read the fetched papers (.research/sources/<id>/fulltext.txt, with the search row in metadata.json) with your own tools — a paper runs to 80k+ characters, so read in parts or search within the file. Keep, per paper the research will rest on, its source id and the passages that matter (page and verbatim quote): preregister_record takes exactly these (passages get ids p1, p2, … within a source), so note which passages the hypothesis answers (its gap) and which the design follows; record both as quoted_passage_ids. A quote is matched against the snapshot ignoring line breaks, end-of-line hyphenation and ligatures, so copy it as the extracted text has it; keep it to one passage on one page (pages are separated by form feeds and a quote cannot span two).
  2. Fix the compute target: ask the user if it is not known, and record GPU and arch (x86_64/aarch64) — the design and later the dependency lockfile depend on it.
  3. Map the method onto the upstream code, then enumerate the knobs when the design reuses an existing implementation. The map: for each step of the method as the paper states it, the upstream module.Class.method that carries it. A step the upstream cannot carry unmodified is yours to write, and the map says so: which upstream function was considered and why it cannot be used — a deviation from the method, declared in the design's summary and the hypothesis's notes. Use the upstream for every step it can carry; a map that leaves most steps to you goes to the user before any code is written. Then the knobs: from the repository at the commit you will pin, list the keys of its config files, the keyword defaults of the entry points you will call, its module constants, and the prompt or resource files it reads (by reading the code until the inventory tool lands). Classify each as varied (in params, on the grid), fixed away from the upstream default (with the passage stating the default and the reason), or kept at the default (with the reason); a knob you decide not to consider is an assumption, not an omission. Declare all of it in the record: the repository goes under its paper's repositories (url, commit, files naming the whole package, method_entry = the module.Class.method whose call runs the method), and the design carries repository_integration (repository_id, extension_points = upstream names your adapter subclasses, overrides or replaces, written as the defining module's module.Class — scigym.api.api.LLM, not the re-export scigym.api.LLM — arguments = one module.Class.method.arg per knob you set, fixed or on the grid alike: the argument of the function that consumes the value — the upstream's, or a src/ function's for an own knob (seed, workers, a threshold); each is a key of every run's params holding the value that reaches the argument unchanged). The run hook records what every src/ function and the upstream were called with, and the gate compares each run's params with it.
  4. Author the hypothesis and the design against the guide get_prompts(step="hypothesis_and_design") returns: it states what a hypothesis, a claim (statement, rationale, criterion, predicted interval, cited passages), a design and a run must contain, and ends in the exact literature and hypotheses arguments preregister_record takes. retrieve_models / retrieve_datasets list curated candidates; search_huggingface_hub when they lack what the design needs. A gap the papers at hand cannot confirm is a reason to go back to search-papers, not to assume. Write the prose in the user's working language; metric names stay English identifiers. The design's summary states every choice that fixes the hypothesis space, what the method gets to see, how it selects and how it is scored — enough to re-implement the run without the code — and lists each departure from the paper's method as paper: … / here: … / why: …. Depart only where the paper's form cannot be run; declaring a departure does not excuse it.
  5. Agree the design with the user before any code is written: run ids, params, claims with criteria and predictions, tables, and the departure list from step 4 as a table. A consultation is not a go-ahead to build. Then write the agreed design to .research/design.json — exactly the literature and hypotheses arguments preregister_record will take — and commit it.

Read the full file on GitHub · 99 lines

Changes

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.

  1. 22d ago Changed · +5 tokens per session 4a7ea9706797
  2. 23d ago Changed · +2 lines 05a8734cf55c
  3. 26d ago Changed · +6 lines 3f4a072789db
  4. 29d ago Changed · +10 lines 872d67d60030
  5. 1mo ago Changed · +13 lines 33e9144e9e11
  6. 1mo ago Changed · +20 lines b1c7f72f18a8
  7. 1mo ago Changed · -12 lines 467641360f83
  8. 1mo ago Changed · +16 lines · -1 tokens per session 4dfc2c87b803
  9. 1mo ago Changed · +5 lines e86a9e21d214
  10. 1mo ago First seen · 39 lines · 51 tokens per session scan A 1682df1e98bd

Subscribe to this mod's changes

hypothesize-and-design is a skill published in the GitHub repository airas-org/airas (39 stars, last pushed 21d ago), licensed MIT. It adds 55 tokens to every session and 1,464 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-04.

Related

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