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Agent skill

Identify Assumptions

by borghei in borghei/Claude-Skills

Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.

MITAuto-check passed

Install Identify Assumptions

skills CLI
$ npx skills add borghei/Claude-Skills --skill identify-assumptions -a claude-code

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

GitHub CLI
$ gh skill install borghei/Claude-Skills identify-assumptions --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/project-management/discovery/identify-assumptions .claude/skills/identify-assumptions && 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
identify-assumptions
GitHub stars
881
Token cost
~1.4k tokens
SKILL.md length
556 words
Files
7 (incl. scripts, references, assets)
Skills in repo
349
Repo updated
First seen
Licence
MIT

At a glance

Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.

  • SKILL.md covers Overview, Core Capabilities, When to Use and Clarify First, plus 4 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Identify Assumptions is an agent skill from borghei/Claude-Skills. Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/assumption_map_template.md`, `examples/shared-dashboards-assumption-mapping.md` and `references/assumption-mapping-guide.md`).

The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

Example prompts

  • “/identify-assumptions”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. 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

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Identify Assumptions loads about 1.4k tokens when it runs, and up to ~9.6k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 556 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.6k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 556 words, ~1,420 tokens.

Download SKILL.mdSave it as .claude/skills/identify-assumptions/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
identify-assumptions
description
Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.
license
MIT + Commons Clause
metadata.version
1.0.1
metadata.author
borghei
metadata.category
project-management
metadata.domain
product-discovery
metadata.updated
2026-06-15
metadata.python-tools
assumption_tracker.py
metadata.tech-stack
assumption-mapping, risk-matrix, teresa-torres, continuous-discovery

Assumption Mapping Expert

Overview

Systematically identify, categorize, and prioritize the assumptions underlying your product decisions. This skill extends Teresa Torres' four risk categories with four additional categories for new products, and uses a devil's advocate approach from PM, Designer, and Engineer perspectives to surface hidden assumptions.

Core Capabilities

  • 4-8 category risk model — Value, Usability, Viability, Feasibility (Torres core) plus Ethics, Go-to-Market, Strategy, Team for new products.
  • Devil's advocate surfacing — adversarial PM, Designer, and Engineer perspectives expose hidden assumptions.
  • Impact x Risk scoring — Risk Score = Impact x (1 - Confidence) ranks what to test first.
  • Quadrant classification — Test Now / Proceed / Investigate / Defer with category-matched validation methods.
  • Automated tracking — assumption_tracker.py sorts by priority and suggests next actions.

When to Use

  • After ideation, before committing to build.
  • When a product decision "feels right" but has not been validated.
  • When the team disagrees on risk or priority -- assumptions make disagreements explicit.
  • Before designing experiments -- test the riskiest assumptions first.

Clarify First

Before mapping assumptions, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • The decision or idea being mapped — the specific product bet whose assumptions you surface (without it the map has no subject)
  • Product type — new vs existing (determines whether to use the 4 core categories or the full 8-category model)
  • Impact and confidence basis — what evidence sets each impact (1-10) and confidence (high/med/low) (drives Risk Score = Impact × (1 − Confidence) and quadrant placement)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

bash
python3 scripts/assumption_tracker.py --demo            # built-in sample (8 assumptions)
python3 scripts/assumption_tracker.py input.json        # score & prioritize your assumptions
python3 scripts/assumption_tracker.py input.json --format json

Each assumption needs description, category (value/usability/viability/feasibility/ethics/gtm/strategy/team), confidence (high/medium/low), and impact (1-10). Document with assets/assumption_map_template.md.

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

  • references/methodology-and-tools.md — the full 4-8 category tables with examples, the devil's advocate prompts, the 5-phase scoring/quadrant process, assumption_tracker.py usage and flags, output formats, troubleshooting, success criteria, and bibliography. Read when mapping or scripting assumptions.
  • references/assumption-mapping-guide.md — deep theory: Torres' four risks and the extended 8-category model with red flags per category, confidence calibration techniques (evidence-based, Five Whys, pre-mortem check), the prioritization matrix with tripwires, and assumption-to-experiment mapping. Read for the underlying framework.
  • references/red-flags.md — anti-patterns (assumption inflation, miscategorization, confidence without evidence) with bad/good examples anchored in Torres' categories. Read before sharing an assumption map.
Show full SKILL.md (170 more words)Show less

Scope & Limitations

In Scope: systematic assumption identification using PM/Designer/Engineer devil's advocate perspectives; 8-category risk classification; quantitative scoring with Impact x (1 - Confidence); quadrant classification with suggested validation methods; assumption registry with priority sorting and action plans.

Out of Scope: running validation experiments (brainstorm-experiments/); product strategy or roadmap decisions (execution/outcome-roadmap/); technical feasibility deep-dives (engineering/ skills); financial modeling for viability (finance/ skills).

Important Caveats: confidence levels map to fixed numeric values (0.8/0.5/0.2) — a simplification of continuous confidence; the "high impact" threshold is 7/10, adjustable for your risk tolerance; assumption mapping works best collaboratively (Product Trio), not solo.

Integration Points

IntegrationDirectionDescription
brainstorm-ideas/Receives fromIdeas generated become the subjects whose assumptions are mapped
brainstorm-experiments/Feeds into"Test Now" assumptions become hypotheses for experiment design
pre-mortem/ComplementsPre-mortem catches risks that assumption mapping may miss (especially elephants)
execution/create-prd/Feeds intoValidated assumptions populate the PRD Assumptions section (Section 7)
execution/brainstorm-okrs/Feeds intoViability assumptions inform OKR key result selection and confidence levels
senior-pm/Feeds intoHigh-impact assumptions feed into portfolio risk registers

© borghei, 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 6 other files (scripts, references, assets) in project-management/discovery/identify-assumptions of borghei/Claude-Skills.

  • SKILL.md
  • assets/assumption_map_template.md
  • examples/shared-dashboards-assumption-mapping.md
  • references/assumption-mapping-guide.md
  • references/methodology-and-tools.md
  • references/red-flags.md
  • scripts/assumption_tracker.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Identify Assumptions 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.

Identify Assumptions compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Identify Assumptions this skillborghei/Claude-Skills881—~1.4kAutomated safety check: PassMIT
Prioritize Assumptionsphuryn/pm-skills27k—~571Automated safety check: PassMIT
Identify Assumptions Existingphuryn/pm-skills27k—~525Automated safety check: PassMIT
Identify Assumptions Newphuryn/pm-skills27k—~807Automated safety check: PassMIT
Impediment Prioritizationgithub/awesome-copilot40k1 repos~2.3kAutomated safety check: PassMIT
Mapping Mitre Attack Techniquesmukul975/Anthropic-Cybersecurity-Skills34k—~1.8kAutomated safety check: PassApache-2.0

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  • Prioritize Assumptions

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Questions about Identify Assumptions

What does Identify Assumptions do?

Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis. Identify Assumptions is an agent skill from borghei/Claude-Skills. Assumption mapping expert that identifies, categorizes, and prioritizes product assumptions across 4-8 risk categories using devil's advocate analysis.

How do I install Identify Assumptions in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill identify-assumptions -a claude-code`. Or copy the skill folder (project-management/discovery/identify-assumptions in borghei/Claude-Skills) into .claude/skills/identify-assumptions in your project. Claude Code loads it when a task matches its description.

How do I install Identify Assumptions in Codex?

Run `npx skills add borghei/Claude-Skills --skill identify-assumptions -a codex`. Or copy the skill folder (project-management/discovery/identify-assumptions in borghei/Claude-Skills) into .agents/skills/identify-assumptions in your project. Codex loads it when a task matches its description.

Can I use Identify Assumptions 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 borghei/Claude-Skills --skill identify-assumptions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/identify-assumptions, .gemini/skills/identify-assumptions, .github/skills/identify-assumptions and .opencode/skills/identify-assumptions in your project.

What does Identify Assumptions need to run?

Going by SKILL.md and its folder, Identify Assumptions needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Identify Assumptions 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 Identify Assumptions 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Identify Assumptions use?

Identify Assumptions is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Identify Assumptions use?

About 1.4k tokens (SKILL.md is roughly 5.7k 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 8.2k tokens, read only when the agent opens those files.

What are the alternatives to Identify Assumptions?

Skills that share tags, products or a category with Identify Assumptions: Prioritize Assumptions (phuryn/pm-skills, 27k stars), Identify Assumptions Existing (phuryn/pm-skills, 27k stars), Identify Assumptions New (phuryn/pm-skills, 27k stars) and Impediment Prioritization (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Identify Assumptions?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.

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