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Assumption Mapper Skill · mohitagw15856 | DecimalAI

productivityby mohitagw15856

Assumption Mapper Skill

mohitagw15856/assumption-mapper

Source mohitagw15856/pm-claude-skills ↗License MIT

Extract and risk-rate hidden assumptions in a product brief or PRD.

SkillScore91Maintained

Automatic

Product Management pack

Last verified 8/14/2026

What it changes

Passed 20 of 22 test cases with the skill, and 9 of 22 without it.

Without skill41%

With skill91%

Checks it passed that the model alone missed

Flags the Impact 5, Confidence 1 assumption as Critical.
Rates each assumption on Impact (1-5) and Confidence (1-5).
Includes a Priority column calculated as Impact minus Confidence.

and 20 more in the full report

13 fixed7 passed either way0 still failing2 broke

Pass-rate lift: +50 pp
Tokens: +65%
Agent turns: 0%
Response time: +9%

Model gemini-3.6-flashMeasured 8/14/2026v620 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mohitagw15856-assumption-mapper/SKILL.md https://app.decimal.ai/s/mohitagw15856-assumption-mapper/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mohitagw15856-assumption-mapper, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mohitagw15856-assumption-mapper/ and pins it in .decimal/skills.lock

decimalai skills add mohitagw15856-assumption-mapper

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mohitagw15856-assumption-mapper/SKILL.md https://app.decimal.ai/s/mohitagw15856-assumption-mapper/SKILL.md

Raw file: /s/mohitagw15856-assumption-mapper/SKILL.md ↗ · machine-readable summary at /s/mohitagw15856-assumption-mapper.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 13

Prompt

I'm about to start writing the PRD for an AI-powered automated meeting summarizer feature for our enterprise workspace tool, and we are currently at the pre-build stage. Before committing engineering resources, I need to surface all hidden risks and hypotheses across desirability, feasibility, viability, and usability. Please analyze our idea and give me a prioritized matrix detailing each assumption with category, confidence rating, impact score, priority calculation, and a validation method. Call out any high-risk critical bets that could derail the feature, and provide a top 3 priority list of tests to run this week, specifying research methods, estimated effort, and what decision each result will drive.

What was checked, without and with the skill
Checked	Without skill	With skill
Calculates priority for each assumption strictly as Impact minus Confidence.	Missed	Passed
Tags each assumption with a provenance indicator of either [data] or [hunch].	Missed	Passed
Flags assumptions with Impact rating of 4 or higher and Confidence rating of 2 or lower as Critical.	Missed	Passed

case-01 · gemini-3.6-flash · 8/14/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md104 linessingle file

Assumption Mapper Skill

Surface and prioritize the untested assumptions embedded in any product plan before development begins.

Required Inputs

Ask the user for these if not provided:

Product brief, PRD, or concept description (even rough notes work)
Stage (concept / discovery / pre-build / post-launch — affects which assumptions matter most)

Where this sits — the spine's entry point

This is the front of the product-decision spine: assumption-mapper → /prd-template → /rice-prioritisation → /roadmap-narrative. It takes a raw idea or brief and hands the next skill one thing: the riskiest assumption, and whether it survived a cheap test. Shared terms (assumption, load-bearing, confidence, provenance) are defined once in docs/craft/product-decisions.md — consult it rather than re-deriving them. Writing a PRD on top of an untested load-bearing assumption is the failure this skill exists to prevent, so run it before /prd-template, not after.

The loop

Four phases. Phase 3 is the skill; the rest feed it. Each ends on a completion criterion — don't advance until it's met.

Surface across all four lenses. Extract assumptions in Desirability (do users want it?), Feasibility (can we build it?), Viability (will the business sustain it?), Usability (can users actually use it?). The dangerous assumptions are the ones so obvious no one wrote them down. Done when: at least one assumption per lens, and re-reading the brief for the emptiest lens surfaces nothing new.
Rate on the two axes only. For each: load-bearing (1–5, does the plan collapse if it's false?) and confidence (1–5, how sure are we it's true?). Priority = load-bearing − confidence. Tag each fact's provenance ([data]/[hunch]). Done when: every assumption has both scores and a provenance tag, and the highest-priority one is genuinely the scariest — not the easiest to test.
Find and pressure the riskiest. The top-priority assumption (high-load-bearing × low-confidence) is the one that can sink the whole plan. Name the cheapest test that could disprove it before a line of code is written (see the disclosed

Track record

Benchmark

20 / 22

test cases passed, vs 9 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mohitagw15856 / pm-claude-skills

skills/assumption-mapper/SKILL.md

View on GitHub ↗

License MITImported 8/10/2026Version v6

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

borghei/identify-assumptionsAssumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.Close match+68 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Assumption Mapper Skill

Required Inputs

Where this sits — the spine's entry point

The loop

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills