Agent skill

Hypotheses

by davepoon in davepoon/buildwithclaude

Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far.

MITAuto-check passedBusiness, Finance & HR

Install Hypotheses

skills CLI
$ npx skills add davepoon/buildwithclaude --skill hypotheses -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davepoon/buildwithclaude hypotheses --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davepoon/buildwithclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/startup-superpowers/skills/hypotheses .claude/skills/hypotheses && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hypotheses
GitHub stars
3.6k
Token cost
~2k tokens
SKILL.md length
1,011 words
Files
2 (incl. references)
Skills in repo
245
Repo updated
First seen
Licence
MIT

At a glance

Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far.

  • The conversation touches assumptions
  • SKILL.md covers Before you start, When hypotheses already exist, When no hypotheses exist and Assessing hypothesis state, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • What to validate

What it does

Hypotheses is an agent skill from davepoon/buildwithclaude. Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far. Use when the conversation touches assumptions, risks, what to validate, hypotheses, interview prep, assessing which hypotheses are confirmed or invalidated, reviewing overall hypothesis health, or when the user questions whether something about their idea is true.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/initial-hypotheses.md`).

It sits in Business, Finance & HR, covering Interview preparation. The repository describes itself as: A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code, Claude Desktop, Agent SDK and OpenClaw. The licence is MIT.

When your agent uses it

  • The conversation touches assumptions
  • What to validate
  • Assessing which hypotheses are confirmed
  • Reviewing overall hypothesis health

Example prompts

  • “Use the hypotheses skill to manage the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the…”
  • “/hypotheses”

What it can do on your machine

Read from SKILL.md and the folder at commit 10bfc43. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hypotheses loads about 2k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 118 tokens; SKILL.md has 1,011 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~118
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davepoon/buildwithclaude at commit 10bfc43, republished under its MIT licence (© davepoon). 1,011 words, ~1,988 tokens.

Download SKILL.mdSave it as .claude/skills/hypotheses/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
hypotheses
description
Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far. Use when the conversation touches assumptions, risks, what to validate, hypotheses, interview prep, assessing which hypotheses are confirmed or invalidated, reviewing overall hypothesis health, or when the user questions whether something about their idea is true.

Hypotheses

Helps the user surface, refine, and manage testable assumptions about their idea. These hypotheses are the foundation for interview scripts, surveys, and validation experiments.

Before you start

Read startup/core.md to load project context (name, seed description, and all fields under ## Core).

Check if startup/hypotheses/ contains any .md files.


When hypotheses already exist

Load and understand them for context. Infer intent from the conversation — don't mechanically ask "what do you want to do?" If the user is:

  • Talking about a specific assumption — help them refine or update the matching hypothesis
  • Questioning new assumptions — help shape new hypotheses following the conventions below
  • Reviewing the full set — summarize what exists, grouped by tag type, with status
  • Updating status — read the file, propose the status change, get confirmation, write it back
  • Archiving — when a hypothesis is no longer relevant (e.g., after a pivot), set status: archived and add archived_reason to frontmatter with a one-line explanation. Archived hypotheses stay in place — they can be restored by flipping the status back
  • Wanting web research on a hypothesis — dispatch the web-researcher agent (fast model) with a focused prompt: include the hypothesis statement, the problem space from core.md, and ask for community signals (Reddit, forums), existing workarounds, and willingness-to-pay evidence. Incorporate key findings into the hypothesis ## Notes section. Save the full web-researcher output to startup/research/{YYYY-MM-DD}-{hypothesis-slug}-research.md with frontmatter date, topic, and source_skill: hypotheses

When adding or updating hypotheses, follow the file conventions:

  • YAML frontmatter with status (untested, confirmed, invalidated, or archived)
  • Optional last_assessed ISO date (YYYY-MM-DD) — set by assessments, not on creation
  • H1 heading: the hypothesis as a testable statement
  • Obsidian tag on the next line: #problem, #solution, #willingness_to_pay, #urgency, or #other
  • Description: what the assumption is, why it matters, what changes if it's wrong
  • Optional ## Notes section
  • Optional ## Next Action section — the smallest observable next validation move. Advisory and generated by assessments (see below), not authored by hand. No required internal structure: a tight one-sentence directive is the norm. It is overwritten on each assessment, always reflecting the latest reasoning — not an append-only log.

Slug convention: lowercase the title, replace spaces and non-alphanumeric characters with hyphens, collapse multiple hyphens.

Read before writing, propose before saving, get confirmation.


When no hypotheses exist

Check if startup/core.md has at minimum Audience and Problem defined under ## Core.

  • If not: Mention that fleshing out the core idea first would help — strongly suggest to do it first, and if the user agrees, invoke the whats-next skill to initialize the project, and then you can come back to hypotheses. But do not block: if the user insists to work on hypotheses now, proceed.
  • If yes (or user insists): Load the reference file for the guided first-time conversation:
.claude/skills/hypotheses/references/initial-hypotheses.md

The reference file's instructions take over from this point.


Assessing hypothesis state

State assessment is one of this skill's core capabilities. When hypothesis state is in question, dispatch the hypotheses-manager subagent rather than evaluating evidence inline — it's bias-isolated, reads across interview evidence independently, and returns structured recommendations.

When to dispatch:

  • The user asks directly about hypothesis health ("how are my hypotheses looking?", "what do we know so far?", "any hypothesis ready to confirm?", "which of these are we still guessing on?")
  • Right after an interview has been analyzed and new [[slug]] backlinks have arrived (this is wired in automatically by the interviews skill's post-transcript flow — you'll see that path in the interviews skill)
  • You're orienting the user on what to do next and hypothesis state is material to the decision
  • The user questions whether a specific hypothesis still holds, or whether a cross-interview pattern deserves a new hypothesis

What to pass:

  • slugs: the keyword all (or a specific list if the conversation is about particular hypotheses)
  • scope: include instruction to also synthesize candidate new hypotheses from unlinked statements across interview files
Show full SKILL.md (387 more words)Show less

What comes back: a structured block of state recommendations — each with a What changed line, reasoning, evidence pointers, and a Next action — plus a single cross-hypothesis Top pick and any candidate new hypotheses. The subagent never edits files.

What to do with the result:

  • First (no user confirmation needed) — eager bookkeeping: for every hypothesis the subagent actually evaluated, update two things in its file:
    • Its last_assessed frontmatter to today's date.
    • Its ## Next Action section to the subagent's suggested next action (create the section if absent, overwrite it if present). Both are mechanical, advisory bookkeeping — a factual record of what the subagent recommended against current evidence. Neither changes status or the hypothesis body, so neither needs per-item approval. Writing the next action eagerly keeps hypothesis files a live dashboard (the whats-next skill reads these sections) and keeps the stability anchor accurate even if the user nods and closes the chat, or if the assessment ran as a byproduct of another flow. (Read the file before writing, so you only touch frontmatter and the ## Next Action section.)
  • Then surface the state recommendations conversationally — lead each touched hypothesis with what changed → the next action, not just a status. Surface the Top pick as the single most pressing move. Then any candidate new hypotheses.
  • For each recommended status change, use this skill's normal propose-before-writing flow — confirm per-item before flipping status.
  • For each candidate new hypothesis, get the user's go-ahead before creating a file following the conventions above.
  • Do not flip statuses or create new hypothesis files without explicit per-item confirmation.

This is the same subagent dispatched by the interviews skill after a transcript is analyzed — so state assessment is centralized here regardless of which entry point triggers it.


Ad-hoc web search vs. dispatching web-researcher

Not every web question needs a subagent:

  • Inline WebSearch / WebFetch (you, the main agent): single-fact lookups ("is this Reddit thread still active?", "what's the latest on X pricing model?"), quick verification of a claim, one data point asked about in flow. Stays in conversation, no persistence needed.
  • Dispatch web-researcher: multi-source validation passes for a specific hypothesis (scanning community signals across Reddit/HN/forums, surveying workarounds, gathering willingness-to-pay evidence). Output is structured and gets saved to startup/research/{YYYY-MM-DD}-{hypothesis-slug}-research.md for later reference — and the findings feed into the hypothesis's ## Notes section.

Rough rule: one fact in flow → inline. Multi-source or results-should-persist → dispatch.

© davepoon, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/startup-superpowers/skills/hypotheses of davepoon/buildwithclaude.

  • SKILL.md
  • references/initial-hypotheses.md

Open the folder on GitHubat commit 10bfc43

Compare with similar skills

Hypotheses next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hypotheses compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hypotheses this skilldavepoon/buildwithclaude3.6k—~2kAutomated safety check: PassMIT
Career-Ops Job Search Centercareer-ops-hq/career-ops74k—~3.3kAutomated safety check: PassMIT
Internship Project Preparation ToolLiuMengxuan04/shushu-internship-tool2.1k—~2.3kAutomated safety check: PassCustom licence
Job Application AssistantMadsLorentzen/ai-job-search45k1 repos~1.2kAutomated safety check: NotesMIT
Interview Coachnoamseg/interview-coach-skill2.3k—~3.7kAutomated safety check: PassMIT
Algo Senseikaranb192/algo-sensei284—~1.7kAutomated safety check: PassMIT

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Questions about Hypotheses

What does Hypotheses do?

Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far. Hypotheses is an agent skill from davepoon/buildwithclaude. Manages the project's testable hypotheses — surfacing new ones, refining existing ones, updating status, reviewing the full set, and assessing hypothesis state based on evidence gathered so far.

When should I use Hypotheses?

Hypotheses fits situations like: the conversation touches assumptions; what to validate; assessing which hypotheses are confirmed; reviewing overall hypothesis health.

How do I install Hypotheses in Claude Code?

Run `npx skills add davepoon/buildwithclaude --skill hypotheses -a claude-code`. Or copy the skill folder (plugins/startup-superpowers/skills/hypotheses in davepoon/buildwithclaude) into .claude/skills/hypotheses in your project. Claude Code loads it when a task matches its description.

How do I install Hypotheses in Codex?

Run `npx skills add davepoon/buildwithclaude --skill hypotheses -a codex`. Or copy the skill folder (plugins/startup-superpowers/skills/hypotheses in davepoon/buildwithclaude) into .agents/skills/hypotheses in your project. Codex loads it when a task matches its description.

Can I use Hypotheses in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davepoon/buildwithclaude --skill hypotheses -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hypotheses, .gemini/skills/hypotheses, .github/skills/hypotheses and .opencode/skills/hypotheses in your project.

What does Hypotheses need to run?

SKILL.md names no scripts, command-line tools or credentials: Hypotheses is instructions for the agent only.

Does Hypotheses access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hypotheses safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hypotheses use?

Hypotheses is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hypotheses use?

About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.2k tokens, read only when the agent opens those files.

What are the alternatives to Hypotheses?

Skills that share tags, products or a category with Hypotheses: Career-Ops Job Search Center (career-ops-hq/career-ops, 74k stars), Internship Project Preparation Tool (LiuMengxuan04/shushu-internship-tool, 2.1k stars), Job Application Assistant (MadsLorentzen/ai-job-search, 45k stars) and Interview Coach (noamseg/interview-coach-skill, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hypotheses?

davepoon (a GitHub user) maintains it in davepoon/buildwithclaude, which has 3,604 GitHub stars. The repository holds 245 skills in this directory. The repository was last updated on October 6, 2026.

Source: davepoon/buildwithclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.