Sfdipot Product Factors

What it does

When your agent uses it

• Analyzing requirements
• User stories to generate prioritized test ideas across Structure
• Time dimensions

Example prompts

• “Use the sfdipot-product-factors skill to jame Bach's HTSM Product Factors (SFDIPOT) analysis for comprehensive test strategy generation”
• “/sfdipot-product-factors”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1IDENTIFY document type (epic, user story, spec, architecture doc)
2. 2DETECT domain context (ecommerce, healthcare, finance, etc.)
3. 3ANALYZE each SFDIPOT category systematically
4. 4GENERATE test ideas with action verbs (no "Verify" patterns)
5. 5ASSIGN priorities (P0-P3) and automation fitness
6. 6SURFACE clarifying questions for coverage gaps
7. 7OUTPUT in requested format (HTML, JSON, MD, Gherkin)

What it can do on your machine

Read from SKILL.md and the folder at commit 1363bc7. 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 (its code samples are typescript).

  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

Sfdipot Product Factors loads about 2k tokens when it runs. Until then it costs about 75 tokens; SKILL.md has 762 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~75

When it runs · the whole SKILL.md, loaded when a task matches

~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

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 proffesor-for-testing/agentic-qe at commit 1363bc7, republished under its MIT licence (© proffesor-for-testing). 762 words, ~2,039 tokens.

name

sfdipot-product-factors

description

James Bach's HTSM Product Factors (SFDIPOT) analysis for comprehensive test strategy generation. Use when analyzing requirements, epics, or user stories to generate prioritized test ideas across Structure, Function, Data, Interfaces, Platform, Operations, and Time dimensions.

category

requirements-analysis

priority

high

tokenEstimate

1500

agents

qe-product-factors-assessor, qe-test-idea-rewriter

implementation_status

optimized

optimization_version

1

last_optimized

2026-01-17

dependencies

brutal-honesty-review

quick_reference_card

true

tags

sfdipot, htsm, product-factors, test-strategy, requirements, james-bach

// Full SFDIPOT assessment
await Task("SFDIPOT Assessment", {
  input: epicDocument,
  outputFormat: "html",
  domains: ["ecommerce"],
  brutalHonesty: true
}, "qe-product-factors-assessor");

// Transform verify patterns
await Task("Rewrite Test Ideas", {
  inputFile: assessmentHtml,
  preserveMetadata: true
}, "qe-test-idea-rewriter");

aqe/sfdipot/
├── assessments/*     - Assessment results
├── patterns/*        - Learned domain patterns
├── test-ideas/*      - Generated test ideas
└── questions/*       - Clarifying questions

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

Files

Just SKILL.md in assets/skills/sfdipot-product-factors of proffesor-for-testing/agentic-qe.

Open the folder on GitHubat commit 1363bc7