# Assumption Tracker

> Extract and risk-rank assumptions from research docs — living register of what to validate first

- Skill: `georgeqle/assumption-tracker` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add georgeqle/assumption-tracker`
- Raw SKILL.md: https://api.skillmd.com/api/skills/georgeqle/assumption-tracker/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: GeorgeQLe (https://skillmd.com/u/georgeqle)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/georgeqle/assumption-tracker

---


# Assumption Tracker — Riskiest Assumptions Register

Invoke as `$assumption-tracker`.

Scans all `research/*.md` files, extracts implicit and explicit assumptions, ranks by risk (catastrophic if wrong) × uncertainty (how little evidence), and produces a living register prioritizing what to validate first.

## Prerequisites

- **Hard**: At least 3 files must exist in `research/` (or `research/{slug}/`). If fewer exist, tell the user to run more research skills first and stop.
- **Soft**: The more research docs exist, the more comprehensive the register. Reads all of: `research/icp.md`, `research/competitive-analysis.md`, `research/journey-map.md`, `research/metrics.md`, `research/gtm.md`, `research/monetization.md`, `research/customer-feedback.md`, `research/positioning.md`.

## Process

### 0. Product-Path Scope Resolution

Resolve research scope by product path before using code or app structure as a hint:

1. If `$ARGUMENTS` names a non-archived `research/{slug}/` directory or a product-path ID whose `scope_path` points there, use that path. Treat `{slug}` as the product/app name, not the ICP, audience, or segment label.
2. If `$ARGUMENTS` names only `research/_archive/{slug}/` or a manifest entry with `status: archived` or legacy `status: abandoned`, stop and warn that the path is archived; do not write or update scoped outputs there.
3. Read `research/.progress.yaml` when present. Normalize legacy `active_path` to `active_paths` on read and write back `active_paths` on manifest updates. Treat legacy `abandoned` as `archived`; exclude `archived`, `abandoned`, `deferred`, `revisit_candidate`, `promoted`, and any `scope_path` under `research/_archive/` from active target selection.
4. If active product paths exist in the manifest, use those paths. If multiple active paths exist, ask which one to target unless this skill explicitly supports cross-path output.
5. If no active manifest target exists, list non-archived product directories under `research/`, excluding `research/_archive/` and dot directories. Auto-select only when exactly one exists; ask when multiple exist.
6. If no product directories exist, use flat `research/` single-product mode.
7. Detect monorepo/app/package structure only as a secondary hint. Suggest creating a missing `research/{slug}/` product path when code clearly exposes an app, but do not require code or monorepo detection before using `research/{slug}/`.

When product path `{slug}` is active, read and write research under `research/{slug}/`, specs under `specs/{slug}/`, and treat top-level `research/*.md` files as flat-mode documents or cross-path summaries.

### 1. Load All Research

Read every `research/*.md` file (or `research/{slug}/*.md`). For each document, extract:

- **Explicit claims** — statements presented as facts ("our ICP has budget authority", "the market is $2B")
- **Implicit assumptions** — unstated beliefs the analysis depends on ("users will switch from Excel", "word-of-mouth will be a growth channel", "the aha moment happens within 5 minutes")
- **Dependency assumptions** — where one research doc builds on conclusions from another ("GTM pricing assumes ICP willingness-to-pay from monetization research")

Track which document and section each assumption comes from.

### 2. Categorize Assumptions

Group assumptions into categories:

| Category | Examples |
|----------|----------|
| **ICP & Market** | Target segment exists, pain is severe enough to pay, market size estimates |
| **Value Proposition** | Our solution solves the pain, users prefer us over alternatives |
| **Pricing & Revenue** | Willingness to pay, price sensitivity, unit economics viability |
| **Channel & Distribution** | Can reach ICP through chosen channels, conversion rates, CAC assumptions |
| **Product & UX** | Users can achieve aha moment, activation flow works, retention drivers |
| **Competitive** | Competitor won't copy, switching costs exist, differentiation is durable |
| **Timing** | Market is ready now, no regulatory changes coming, technology is mature |

### 3. Score Each Assumption

For each assumption, score two dimensions:

**Risk (if wrong)** — 1 to 5:
- 1: Minor inconvenience, easy pivot
- 3: Significant rework needed, delays
- 5: Existential — business model collapses, wasted months of work

**Uncertainty (how little evidence)** — 1 to 5:
- 1: Strong evidence — multiple data points, validated by customer feedback
- 3: Moderate — some research supports it, but not validated with real users
- 5: Pure assumption — no evidence, taken on faith or "common sense"

**Combined priority** = Risk × Uncertainty (max 25). Higher = validate first.

### 4. Check Validation Status

Cross-reference assumptions against:
- `research/customer-feedback.md` — findings classified as "Confirmed" or "Wrong" may validate or invalidate assumptions
- `research/experiments/` directory — completed experiment results
- `research/cohort-review-*.md` — real performance data

Mark each assumption's validation status:
- **Unvalidated** — no evidence for or against
- **Partially validated** — some supporting evidence, not conclusive
- **Validated** — strong evidence confirms this assumption
- **Invalidated** — evidence contradicts this assumption
- **Stale** — was validated, but newer data raises questions

### 5. Present & Validate

Present the top 10 highest-priority assumptions to the user. If the session is already in Plan mode and there are 2-3 concrete validation choices, prefer `request_user_input`; otherwise ask in plain text:

- Show the assumption, source document, risk score, uncertainty score, combined priority, and validation status
- Ask: "Do these priorities feel right? Any assumptions I'm missing or scoring wrong?"
- Ask: "Are there any assumptions here you already know the answer to?"

Incorporate feedback before proceeding.

### 6. Generate Validation Recommendations

For each unvalidated high-priority assumption (combined score ≥ 12), recommend a validation method:

| Validation Method | Best For |
|-------------------|----------|
| `$experiment` — landing page test | Demand validation, messaging tests |
| `$experiment` — fake-door test | Feature demand, willingness to explore |
| `$experiment` — pricing test | Willingness to pay, price sensitivity |
| `$experiment` — survey | Broad sentiment, preference ranking |
| `$customer-feedback` — user interview | Deep understanding, "why" questions |
| `$cohort-review` — analyze real data | Post-launch metrics, funnel performance |
| Direct observation | UX assumptions, activation flow |
| Competitor analysis | Market timing, differentiation durability |

### 7. Populate Next Steps

Include 3–5 applicable items with "Pick one:" framing:

- IF unvalidated assumptions with score ≥ 15: `$experiment [top assumption]` — Design a cheap test for the riskiest assumption
- IF customer feedback exists but assumptions remain unvalidated: `$customer-feedback` — Gather targeted feedback on top assumptions
- IF product is live: `$cohort-review` — Check if real data validates or invalidates key assumptions
- IF assumptions cross multiple docs: `$reconcile-research` — Ensure research docs are internally consistent
- ALWAYS: `$research-roadmap` — Check overall project status

### 8. Write Output

Present final register to user. Ask:
- "Ready to write this to `research/assumption-tracker.md`? Anything to adjust first?"

Only after confirmation, write the output file.

## Output

### `research/assumption-tracker.md` (or `research/{slug}/assumption-tracker.md`)

```markdown
# Assumption Tracker

> Last updated: [current date]
> Sources: [list of research docs scanned]
> Total assumptions: [count] | Unvalidated high-risk: [count]

## Summary

[2-3 sentences: the riskiest unvalidated assumptions and what to do about them]

## Top 10 Riskiest Assumptions

| # | Assumption | Source | Category | Risk | Uncertainty | Priority | Status |
|---|-----------|--------|----------|------|-------------|----------|--------|
| 1 | [assumption] | [doc:section] | [category] | [1-5] | [1-5] | [R×U] | [status] |
| ... | | | | | | | |

## Full Register

### ICP & Market
| Assumption | Source | Risk | Uncertainty | Priority | Status | Validation Method |
|-----------|--------|------|-------------|----------|--------|-------------------|
| [assumption] | [doc:section] | [1-5] | [1-5] | [R×U] | [status] | [method] |

### Value Proposition
[Same table format]

### Pricing & Revenue
[Same table format]

### Channel & Distribution
[Same table format]

### Product & UX
[Same table format]

### Competitive
[Same table format]

### Timing
[Same table format]

## Validation Plan

### Immediate (This Week)
[Top 1-3 assumptions to validate, with specific method and success criteria]

### Short-term (This Month)
[Next 3-5 assumptions, with recommended approach]

### Can Wait
[Lower-priority assumptions that don't block current decisions]

## Recently Validated / Invalidated

| Assumption | Previous Status | New Status | Evidence | Date |
|-----------|----------------|------------|----------|------|
| [assumption] | Unvalidated | Validated/Invalidated | [evidence source] | [date] |

## Next Steps

Pick one:
- [conditional items from step 7 — only include items whose conditions are met]
```

Create the `research/` 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

- **Read-only on research docs.** Extract assumptions from existing research — do not modify source documents.
- **Be specific.** "Market exists" is not an assumption. "Solo creative professionals earning $50K-150K will pay $20/mo for portfolio analytics" is.
- **Trace to source.** Every assumption must reference the specific document and section it was extracted from.
- **Score honestly.** Don't inflate uncertainty to make things seem more urgent. If there's real evidence, score it low.
- **Update, don't duplicate.** If `research/assumption-tracker.md` already exists, ask the user whether to update (re-scan and merge) or overwrite. If the session is already in Plan mode and there are 2 concrete choices, prefer `request_user_input`. When updating, preserve validation status and "Recently Validated" history.
- **Present before writing.** Never write output files until findings have been presented and validated.

## Alignment Page

Follow the shared alignment-page convention via the packaged convention resolver; output path is `alignment/assumption-tracker-{topic}.html`.

## Default Shipping Contract

Follow the shared shipping contract convention in CLAUDE.md.