Experiment

Pack Availability Guard

Before telling the user to run a skill from another project-local pack, check .agents/project.json.enabled_packs. If the target pack is not enabled, recommend $pack install <pack> instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.

Experiment — Lean Validation Design

Takes a hypothesis (from $assumption-tracker or user) and designs a cheap, fast validation experiment. Covers landing page tests, fake-door tests, concierge MVPs, surveys, A/B tests, pricing tests, and smoke tests. Outputs a structured plan with hypothesis, method, success criteria, sample size, timeline, and decision rules.

Soft Prerequisites

• Read research/assumption-tracker.md if it exists — pulls the highest-priority unvalidated assumption
• Read research/icp.md if it exists — grounds experiment design in who the target is
• Read research/metrics.md if it exists — aligns success criteria with existing metric definitions
• Read research/gtm.md if it exists — leverages channel strategy for reaching test subjects

Process

0. App Scope Resolution (Monorepo Support)

Before checking prerequisites, determine the app scope:

1. If $ARGUMENTS specifies an app name matching a subdirectory of research/, use it.
2. If research/ contains subdirectories (excluding files), list them and ask the user which app to target. If the session is already in Plan mode and there are 2-3 concrete choices, prefer request_user_input; otherwise ask in plain text. If only one subdirectory exists, use it automatically.
3. If no subdirectories exist, proceed with flat structure (single-product mode).

When app scope {app} is active:

• Read/write research from research/{app}/ instead of research/

1. Parse Input & Load Context

Read $ARGUMENTS:

• If it's a specific hypothesis or assumption: use it directly
• If it's a reference to an assumption number (e.g., "#3"): look it up in research/assumption-tracker.md
• If empty: check research/assumption-tracker.md for the highest-priority unvalidated assumption. If no tracker exists, ask the user what they want to test. If the session is already in Plan mode and there are 2-3 concrete choices, prefer request_user_input.

Load context: Read available research docs to understand the ICP, channels, metrics, and existing knowledge.

2. Structure the Hypothesis

Convert the input into a structured hypothesis:

Format: "We believe that [target segment] will [expected behavior] because [rationale]. We'll know this is true when [measurable outcome]."

Present and refine with the user. If the session is already in Plan mode and there are 2-3 concrete choices, prefer request_user_input; otherwise ask in plain text:

• "Here's how I've structured the hypothesis. Does this capture what you want to test?"
• If the hypothesis is too broad, help narrow it to something testable in 1-2 weeks

3. Research Experiment Methods

Use WebSearch with 3-5 targeted queries to find best practices for this type of validation:

1. Method-specific — "[experiment type] validation method", "how to test [hypothesis type]"
2. Sample size — "[experiment type] sample size calculator", "minimum viable test size"
3. Benchmarks — "[category] conversion rate benchmark", "[experiment type] typical results"
4. Tools — "[experiment type] tools", "cheapest way to test [hypothesis]"

4. Design the Experiment — Present & Validate

Select the most appropriate experiment type and design the full plan:

Experiment Types

Present the experiment design to the user. If the session is already in Plan mode, prefer request_user_input; otherwise ask in plain text. Show:

• Recommended experiment type with rationale (why this method over alternatives)
• Detailed plan with timeline and cost estimate
• Success criteria with specific numbers (citing benchmarks from research)
• Decision rules for both outcomes

Ask:

• "Does this experiment design feel feasible? Too ambitious or too simple?"
• "Any resource constraints I should know about? (budget, time, access to users)"

Incorporate feedback before proceeding.

5. Define Decision Rules

For each possible outcome, define what happens next:

• If hypothesis is validated (success criteria met): What's the next step? (e.g., build the feature, commit to the pricing, double down on the channel)
• If hypothesis is invalidated (criteria not met): What's the pivot? (e.g., test alternative, revisit ICP, change approach)
• If results are inconclusive (between thresholds): What additional data is needed? Run a follow-up experiment or extend the current one?

6. Populate Next Steps

Include a Recommended item for the current design-stage next step, followed by Other options. Separate current next steps from outcome-specific next steps:

Use this format in the output:

## Next Steps

**Recommended:** Run the experiment — the plan is only useful after the evidence is collected

Other options:
- [2-4 applicable alternatives]

• ALWAYS: Run the experiment (manual step — the plan tells you how)
• For a newly designed experiment, do not list validation/invalidation commands as current top-level next steps; put those under ## Decision Rules because they are only valid after results exist.
• In ### If Validated: include the next valid command, usually $customer-feedback [results] to log evidence, $assumption-tracker to mark the assumption validated, or $roadmap / $spec-interview [validated opportunity] if the result commits the team to build.
• In ### If Invalidated: include $assumption-tracker to mark the assumption invalidated, plus $brainstorm, $icp, $gtm, or $monetization only when the failed assumption belongs to that domain.
• In ### If Inconclusive: include $experiment [follow-up] if the test needs another run, or $customer-feedback if qualitative evidence is the missing signal.
• IF more assumptions remain untested after this design: $experiment [next assumption] — Design the next experiment
• IF enough assumptions are validated after completed results: $research-roadmap — Check if research docs need updating based on learnings

7. Write Output

Present final plan to user. Ask:

• "Ready to write this experiment plan? Anything to adjust?"

Only after confirmation, write the output file.

Output

research/experiments/[experiment-name].md (or research/{app}/experiments/[experiment-name].md)

# Experiment: [Descriptive Name]

> Date designed: [current date]
> Status: Designed | Running | Completed
> Assumption: [from assumption-tracker, if applicable — include # reference]
> Priority: [from assumption-tracker score, if applicable]

## Hypothesis

**We believe that** [target segment]
**will** [expected behavior]
**because** [rationale from research]

**We'll know this is true when** [measurable outcome with specific threshold]

## Method

**Type**: [Landing page test / Fake-door / Concierge MVP / Survey / A/B test / Pricing test / Smoke test / Pre-sale / Wizard of Oz]
**Why this method**: [rationale — why this is the cheapest/fastest way to test this hypothesis]

### Setup
[Step-by-step instructions for setting up the experiment]

1. [Step 1]
2. [Step 2]
3. ...

### Tools Needed
- [Tool 1] — [purpose]
- [Tool 2] — [purpose]

### Audience
**Who**: [specific segment from ICP]
**How to reach them**: [channel — from GTM if available]
**Sample size**: [number needed for statistical significance]
**Recruitment method**: [how to get participants]

## Success Criteria

| Metric | Failure | Inconclusive | Success |
|--------|---------|--------------|---------|
| [Primary metric] | < [threshold] | [range] | ≥ [threshold] |
| [Secondary metric] | < [threshold] | [range] | ≥ [threshold] |

**Benchmarks**: [what industry/competitor data says is typical]

## Timeline

| Phase | Duration | Tasks |
|-------|----------|-------|
| Setup | [days] | [what to prepare] |
| Run | [days] | [data collection period] |
| Analyze | [days] | [how to analyze results] |
| **Total** | **[days]** | |

## Budget

| Item | Cost |
|------|------|
| [item] | [amount] |
| **Total** | **[amount]** |

## Decision Rules

### If Validated (success criteria met)
[Specific next actions — what to build, commit to, or double down on]

### If Invalidated (failure criteria met)
[Specific pivot — what to change, test next, or abandon]

### If Inconclusive
[What additional data is needed, whether to extend or redesign]

## Results

> Fill this section after the experiment completes.

**Status**: [Validated / Invalidated / Inconclusive]
**Date completed**: [date]

### Raw Data
[Key numbers and observations]

### Analysis
[What the data shows — connect back to hypothesis]

### Decision
[What was decided based on the results]

### Learnings
[What was learned beyond the hypothesis — surprises, side findings]

## Next Steps

**Recommended:** [recommended next step] — [one-line reason grounded in this artifact]

Other options:
- [conditional items from step 6 — only include items whose conditions are met]

Create the research/experiments/ directory if it doesn't exist.

Task Classification

When this skill produces follow-up work, file it by execution semantics:

• Immediately actionable implementation or documentation work goes in tasks/todo.md.
• Human-only external actions tied to automated steps go in tasks/manual-todo.md with _(blocks: Step N.X)_ or _(after: Step N.X)_; repo edits, SDK wiring, generated assets, local commands, tests, audits, and authenticated CLI/API work stay in tasks/todo.md.
• One-time condition-gated records, baselines, or future measurements go in tasks/record-todo.md with source, condition, non-blocking reason, evidence, and promotion rule.
• Cadence-based reviews, playtests, adoption checks, investor updates, retros, or docs-health checks go in tasks/recurring-todo.md with cadence, owner/agent, next due, evidence path, and escalation conditions.
• Do not put non-blocking records or recurring obligations in tasks/todo.md unless they have been explicitly promoted into current execution work.

Constraints

• One hypothesis per experiment. If the user has multiple things to test, design separate experiments. Don't bundle.
• Cheap and fast. Every experiment should be completable in 1-4 weeks with minimal budget. If the design is expensive or slow, simplify.
• Specific success criteria. "Users like it" is not a success criterion. "≥40% of landing page visitors click 'Get Early Access'" is.
• Present before writing. Never write output files until the experiment design has been presented and validated.
• Include decision rules. Every experiment must specify what happens for each possible outcome. No experiment should end with "we'll figure it out."
• Reference benchmarks. Success thresholds should be grounded in industry benchmarks or competitor data, not arbitrary numbers.
• Don't overdesign. A simple survey can validate an assumption just as well as an elaborate A/B test. Recommend the simplest method that produces a clear signal.

Alignment Page

When this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page at alignment/experiment-{topic}.html. Use a normalized topic slug derived from the app, feature, research subject, report subject, or output filename.

Full content requirement. The alignment page must contain the complete content of every proposed markdown deliverable -- every section, every finding, every detail, every list item. It is a thorough interactive review document, not a summary. Render the full deliverable content in clean, readable HTML with appropriate hierarchy, styling, and navigation. If the skill writes multiple scoped deliverables in one run, build one alignment page that contains all deliverables with anchor-linked navigation. Durable tracker artifacts, such as research/assumption-tracker.md, remain canonical markdown outputs but must also be fully rendered into the alignment page before approval.

Dark-mode styling. Use a dark color scheme by default. Base CSS variables: --bg: #0d1117; --surface: #161b22; --border: #30363d; --text: #c9d1d9; --text-muted: #8b949e; --accent: #58a6ff; --green: #3fb950; --red: #f85149; --orange: #d29922; --purple: #bc8cff;. Apply background: var(--bg); color: var(--text); on body. Use --surface for cards, nav, and table headers. Use --border for all borders. Use --purple for question blocks and gate headings. Use --accent for links and section headings. Keep headings color: #fff or var(--accent) for hierarchy. Question block backgrounds should use #1c2333.

Alignment gates. Treat gates as explicit review sections inside the HTML page. A gate blocks finalization until its required inline questions are answered and compiled into YAML. Include every gate that applies to the skill output, and include these gate types whenever relevant: evidence coverage, assumptions/confidence, scope/non-goals, candidate/verdict decisions, artifact destination, proposed file changes, coverage checkpoint, and post-approval route.

Report-only research gates. For report-only or pre-approval research skills, the alignment page must explicitly contain evidence coverage, assumptions/confidence, recommended path, proposed file changes, and approval gates before any canonical research, spec, or task file is created or updated.

Risk-validation gates. Render assumption/risk evidence coverage, confidence, candidate verdicts or mitigations, artifact destination, proposed file changes, coverage checkpoint, and post-approval route as gates. Durable tracker outputs remain canonical markdown artifacts and must also be fully rendered in the alignment page.

Required inline questions. Each gate must contain at least one required inline question placed directly under the content it governs, inside a visually distinct question block. Each question must use radio-button inputs and include two standing options after the skill-generated choices: "Other / None of the above" backed by a multi-line text box for free-form input, and "Need clarification" backed by an optional notes box where the user can explain what is unclear. When any radio option other than "Other" or "Need clarification" is selected, show an optional "Additional notes" text box beneath it so the user can qualify their choice. Generate questions based on what genuinely needs user input -- do not add filler questions. Do not create a separate bottom "Decisions & Clarifications" section.

Gate YAML contract. At the bottom of the page, include a "Compile Answers" button that aggregates answers from all inline gate questions throughout the page, including free-text notes. The button remains disabled until every required question has a selection, shows a count of remaining unanswered questions, and scrolls to the first unanswered question if clicked early. When every question is answered, generate a structured YAML block with one item per gate answer using this stable shape: section, gate_type, status (answered, other, or needs-clarification), answer, optional notes, and optional target_artifact or target_path when the gate controls file output. After successful compilation, automatically attempt to copy the YAML to the clipboard with the Clipboard API, display copy status, and display the YAML in a read-only textarea with an explicit "Copy YAML" button. The copy button must retry clipboard copy when supported and fall back to selecting the textarea contents when clipboard access is unavailable or blocked.

Pre-approval stop. Before user approval, the next action is review of the HTML alignment page, not downstream routing. Ask the user to review the page and provide the compiled YAML answers. Do not include Recommended next skill, Recommended next command, or downstream routing language until after compiled YAML has been provided and the approved artifacts have been written or updated.

Diff highlighting on updates. When the agent updates an existing alignment page after receiving compiled answers, highlight what changed since the previous version. The agent chooses inline annotation or side-by-side layout per situation.

Archiving. Before replacing an existing alignment page, archive it to docs/history/archive/YYYY-MM-DD/HHMMSS/alignment/experiment-{topic}.html.

Browser open. Attempt to open the resulting HTML page in the browser and report whether the open succeeded or was blocked. A blocked browser-open attempt does not make the skill fail when the files were written correctly.

Archive-First Replacement Policy

• Before replacing or substantively rewriting an existing canonical research/spec document (research/**/*.md, specs/**/*.md, or docs/specifications/**/*.md), copy the current file to docs/history/archive/YYYY-MM-DD/HHMMSS/<original-relative-path>.
• Preserve the archived snapshot exactly as it existed before the change; do not edit the archived copy after creating it.
• After the archive snapshot exists, write the updated document to the original canonical path.
• Report both the archive path and the updated canonical path in the final output.
• New files do not need archive snapshots. Append-only updates do not need archive snapshots unless an existing section is regenerated or rewritten.
• Keep any existing user approval requirement before overwriting or replacing a document; archiving does not replace asking when the skill already requires approval.

Default Shipping Contract

• Default next-step routing: when reporting completion, include either Recommended next skill: <command> or the two-line pair **Next work:** <specific task or "none"> and **Recommended next command:** <one command or route> so the next operator has a concrete handoff.
• If this skill creates or modifies tracked repository files, finish by committing and pushing all intended changes to the repository primary branch (main when present, otherwise master) before stopping, even if the user did not explicitly ask for commit/push.
• Do not leave tracked changes or unpushed commits behind. If unrelated tracked work is already present, either include it in sensible commits too or stop and explain the blocker.
• This contract does not override stricter safety rules about secrets, destructive history changes, release publication/tag confirmation, or production deploy confirmation.