Artifact Deconstruct

Artifact Deconstruct

Reverse-engineer the design decisions behind any polished artifact. The goal is not summary — it is design archaeology: surface what the creator decided, what frameworks they borrowed, and what they deliberately omitted.

When to use

Trigger phrases (any language):

• 「拆解這份」「反推這個」「為什麼這份寫得這麼好」「這份是怎麼設計的」
• "deconstruct this", "reverse engineer", "design behind this", "teardown"
• "why does this work" / "what is this artifact's blueprint"

Skip when:

• User wants a summary — use plain reading
• Artifact is < 200 words and not a structured argument — there is not enough design to deconstruct
• Artifact is purely informational reference (Wikipedia, dictionary, raw data) — no design to recover
• Target is source code — use sourceatlas instead
• Target is the user's own thinking — use philosophers-toolkit

Workflow

Six steps, run in order. Track progress with this checklist:

Deconstruction Progress:
- [ ] Step 1: Identify artifact type
- [ ] Step 2: Select lens combination
- [ ] Step 3: Run six-dimension analysis
- [ ] Step 4: Apply selected lenses
- [ ] Step 5: Generate deconstruction report
- [ ] Step 6: Self-check against anti-patterns

Step 1: Identify artifact type

Detect which type the input belongs to. Use signals, not just user labels.

| Type | Signals | |---|---| | Marketing copy / advertising | Short, persuasion-focused, has CTA, hero section | | Document pack / playbook | Multi-file, README present, role-routed sections | | Single SOP / how-to | Sequential numbered steps, checklist format | | Presentation deck | Slide structure (1 slide ≈ 1 idea), visual-heavy | | Onboarding flow | UI screens or sequential steps, progressive disclosure | | Long-form article | Argumentative or narrative prose, 1000+ words | | Speech / political text | First-person plural, emotional cadence, call to collective | | Literature / film | Narrative, character arcs, symbolic imagery | | UI screen | Visual layout, interactive elements, status indicators |

Record the detected type. If multiple apply, pick the dominant one and note secondary types in the report.

Step 2: Select lens combination

Read [protocols/lens-selection.md](protocols/lens-selection.md) for the full decision tree. Default mappings:

| Artifact type | Lens combination | |---|---| | Marketing copy | lens-persuasion + lens-rhetoric | | Document pack | lens-genre + 6-dimension full pass | | SOP / playbook | lens-genre | | UI / onboarding | lens-ux + lens-persuasion | | Speech / political | lens-rhetoric + lens-frame | | Literature / film | lens-semiotic + lens-frame | | Presentation deck | lens-rhetoric + lens-genre |

You may add a third lens if the artifact has unusual depth (e.g., a landing page that also embeds a long argument benefits from lens-rhetoric + lens-persuasion + lens-genre). Do NOT use all six — that signals indecision, not thoroughness.

Step 3: Run six-dimension analysis

Always run these six dimensions, regardless of which lenses you selected. They are the structural backbone.

1. Audience routing — Who reads what, when?
2. Creation sequence — Reading order vs probable writing order
3. Source genealogy — What existing frameworks were borrowed?
4. Rhetorical structure — How does it persuade?
5. Design patterns — What recurring techniques appear?
6. Negative space — What is deliberately omitted?

See [protocols/six-dimensions.md](protocols/six-dimensions.md) for the prompts that operationalize each dimension.

Step 4: Apply selected lenses

Before reading lens references, resolve the language variant for any of the 4 culturally-sensitive lenses (lens-rhetoric / lens-persuasion / lens-genre / lens-frame) per [protocols/lens-variant-selection.md](protocols/lens-variant-selection.md). The universal-core lens-{rhetoric,persuasion,genre,frame}.md files contain meta-only routing content; the analytical questions live in the per-language variant (-anglo / -ja / -zh). lens-semiotic and lens-ux do not have language variants in v0.2.0.

Read each selected lens reference (variant-resolved) and apply its analytical questions to the artifact. Each lens reference contains:

• Primary-source citation (locked)
• Specific analytical questions
• Worked example
• "Do not over-apply" pitfalls

Available lenses (* = language-variant routing required):

• [references/lens-semiotic.md](references/lens-semiotic.md) — Barthes 5 codes (HER / PRO / SEM / SYM / REF)
• [references/lens-rhetoric.md](references/lens-rhetoric.md) ✱ — universal core; routes to -anglo (Burke + Toulmin) / -ja (Hinds + kishōtenketsu) / -zh (文心雕龍 六觀)
• [references/lens-frame.md](references/lens-frame.md) ✱ — universal core; routes to -anglo (Goffman + Lakoff) / -ja (建前/本音 + ma) / -zh (面子/關係 + 陰陽)
• [references/lens-genre.md](references/lens-genre.md) ✱ — universal core; routes to -anglo (Swales + Bhatia) / -ja (序論-本論-結論 + 拝啓 letter) / -zh (緒論-本論-結論 + 公文)
• [references/lens-ux.md](references/lens-ux.md) — Nielsen-Norman 10 heuristics + Norman affordance
• [references/lens-persuasion.md](references/lens-persuasion.md) ✱ — universal core; routes to -anglo (Cialdini + Brignull) / -ja (Cialdini + JP cultural) / -zh (Cialdini + 面子/關係)

Always state which variant was applied in the report (e.g., "Applied lens-rhetoric-ja") — see protocols/lens-variant-selection.md §"Step 5".

Step 5: Generate deconstruction report

Use [assets/report-template.md](assets/report-template.md). Six sections:

1. Surface observations (what you see)
2. Design decisions (audience / sequence / rhetoric)
3. Borrowed frameworks (genealogy)
4. Rhetorical mechanisms (with ethical position 🟢/🟡/🔴/⚫)
5. Replicable lessons (5 concrete takeaways)
6. Weaknesses or warnings (missing moves / suspicious warrants / dark-pattern risk)

End with a one-line bottom-line verdict.

Step 6: Self-check

Before delivering, run [checklists/anti-patterns.md](checklists/anti-patterns.md) self-check. Most common failures:

• Output drifted toward summary ("this document covers A, B, C") — must be design-decision focused
• Persuasion mechanisms named but no ethical position assigned
• All six dimensions not covered
• Negative space ignored — only analyzed what IS written
• Single lens tunnel vision — applied one lens to a multi-lens artifact

Lens Library Quick Reference

All lens files are in references/, one level deep. Lenses marked ✱ are language-variant-routed — see protocols/lens-variant-selection.md.

| Lens | Variants | Authors (per variant) | When to apply | |---|---|---|---| | lens-semiotic | (no variants) | Roland Barthes (S/Z, 1970) | Literature, film, advertising imagery, texts with strong subtext | | lens-rhetoric ✱ | -anglo / -ja / -zh | Burke 1945 + Toulmin 1958 / Hinds 1983 + 1987 + Oh 2025 (kishōtenketsu) / 劉勰《文心雕龍》六觀 | Speeches, proposals, political texts, arguments needing structural validation | | lens-frame ✱ | -anglo / -ja / -zh | Goffman 1974 + Lakoff 1980 / + Doi 1971 + Yamamoto 1977 + Markus & Kitayama 1991 (建前/本音, 空気, ma) / + Hu 1944 + Hwang 1987 + Peng & Nisbett 1999 (面子/臉, 陰陽) | Texts with strong metaphors, suspected hidden assumptions, ideological texts | | lens-genre ✱ | -anglo / -ja / -zh | Swales 1990 + Bhatia 1993 / + 木下 1981 + Hinds 1987 (序論-本論-結論, 拝啓 letter) / + 行政院公文程式條例 (緒論-本論-結論, 公文) | Document packs, SOPs, academic papers, business proposals — anything genre-recognizable | | lens-ux | (no variants) | Jakob Nielsen + Don Norman (1988, 2013) | UI screens, app flows, websites, onboarding experiences (yes, docs are UX too) | | lens-persuasion ✱ | -anglo / -ja / -zh | Cialdini 2021 + Brignull 2024 / + Doi 1971 + cross-cultural empirical work / + Hwang 1987 (面子/關係/人情) | Marketing copy, sales pages, landing pages, onboarding, political/policy texts |

Output template

See [assets/report-template.md](assets/report-template.md) for the full 6-section format.

Anti-patterns

See [checklists/anti-patterns.md](checklists/anti-patterns.md) for the self-check list. Run before every delivery.

Sample artifacts (eval fixtures)

• [assets/sample-dropbox-landing-2024.md](assets/sample-dropbox-landing-2024.md)
• [assets/sample-notion-onboarding-pack.md](assets/sample-notion-onboarding-pack.md)
• [assets/sample-stripe-signup-flow.md](assets/sample-stripe-signup-flow.md)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: kouko
• Source: kouko/monkey-skills
• License: MIT

Install and usage instructions live in the source repository linked above.