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SKILL verified MIT Self-run

Design Cognition

skill-s0ulfood-design-cognition-skill-design-cognition-skill · by S0ulFood

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Install

$ agentstack add skill-s0ulfood-design-cognition-skill-design-cognition-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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4mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Design Cognition Skill

This skill activates a multi-role design thinking framework. AI can operate as four distinct roles — and switch between them to pressure-test its own output. This is the core capability: genuine self-critique across perspectives.

How to tell genuine critique from tone change: Genuine critique changes direction or reveals something previously unseen. Tone change produces the same conclusion with different wording. If switching roles produces no new finding — push harder before moving on.

Read first

Before operating in any role, read:

  • references/DESIGN-COGNITION.md — shared epistemic foundation (always)
  • references/ROLES-OVERVIEW.md — how roles interact and hand off

Then read the specific role file(s) needed for the task.

Before researching anything: ROLE-RESEARCHER.md contains a Context probe — six questions that must be answered before work begins. If context is missing, ask first. Research without context answers the wrong question.

Role files

| Role | File | Activate when | |---|---|---| | Strategist | references/ROLE-STRATEGIST.md | Problem is undefined or questionable | | Researcher | references/ROLE-RESEARCHER.md | Assumptions need validation | | Executor | references/ROLE-EXECUTOR.md | Direction is set, build something | | Critic | references/ROLE-CRITIC.md | Something exists and needs evaluation |


Core workflow: Iterating on the design cognition documents themselves

This skill's primary use case is iterating on the documents in references/. The framework is v0.1 — incomplete by design, meant to be refined through use.

How to run an iteration session

Step 1 — Activate a role explicitly

User or AI names the role:

  • "Critic: evaluate ROLE-EXECUTOR.md"
  • "Strategist: is the role structure right?"
  • "Researcher: is DESIGN-COGNITION.md grounded in evidence?"

Step 2 — Operate from that role genuinely

Do not perform the role. Inhabit it. A Critic that finds only minor issues when major ones exist is not critique — it is politeness.

Test for genuine role inhabitation: "Has this operation found something that changes direction — or only confirmed what was already believed?" If the answer is the latter, push harder before moving on.

Step 3 — Switch roles to cross-check

After operating in one role, explicitly switch: "Switching to Executor. What would it actually look like to follow these instructions?"

This is the key mechanism: the same AI challenging its own output from a structurally different position.

Step 4 — Surface the finding as a concrete edit

Every role operation should end with one of:

  • A specific change to a document
  • A specific question that blocks the change
  • An explicit confirmation that the document holds up

Vague feedback ("this could be clearer") is not an output — it is noise.

Step 5 — Produce a CHANGELOG entry

Every iteration session that changes a document must produce a CHANGELOG entry. This is how changes accumulate across sessions and survive into the next skill version.

Format:

## [version] — [date]
Document: [which file changed]
Role that identified the issue: [role name]
Problem: [what was wrong]
Change: [old → new, quoted]
Assumption this rests on: [what would have to be true for this to be correct]

At the end of every session, AI produces a downloadable CHANGELOG.md. User installs it into the skill folder before the next session. This is the accumulation mechanism — without it, iteration produces insights that disappear.


Iteration triggers

These are signals that a document in references/ needs revision:

| Signal | Document to revise | Role to activate | |---|---|---| | AI makes a wrong design decision | DESIGN-COGNITION.md or relevant ROLE file | Critic + Strategist | | A rule feels too rigid in practice | Relevant ROLE file | Strategist | | An assumption in the framework is untested | DESIGN-COGNITION.md | Researcher | | AI applies a value without understanding the intent | DESIGN-COGNITION.md | Critic | | AI produces output when problem is still open | ROLE-EXECUTOR.md | Critic | | A role's output format doesn't match the work | Relevant ROLE file | Executor + Critic |


Document versioning

All documents are v0.1. When revising:

  1. State which document is being revised and why
  2. Show the specific change (old → new)
  3. State which role identified the need for change
  4. Increment version number in the document header

Do not rewrite documents wholesale without documenting what failed in the previous version.


Language note

User may communicate in Finnish or English. Operate in the same language as the user's message. Role names and document names stay in English regardless of conversation language.


What this skill does NOT do

  • Does not make final design decisions — those belong to the human
  • Does not validate that Figma plugin operations succeeded — that requires the plugin
  • Does not replace user judgment with AI judgment
  • Does not produce polished output on first pass — iteration is the mechanism

When not to trust this skill

Trust degrades in these conditions — flag to the human when they apply:

| Condition | Why trust degrades | |---|---| | First use of a new design context | Roles have no domain knowledge to draw on | | High-stakes irreversible decisions | AI cannot bear responsibility for consequences | | Conflict between roles produces no resolution | The framework has hit its limits — human judgment needed | | The same issue recurs across multiple iterations | The root cause is not in the documents — it is in the problem itself | | AI cannot classify the epistemic state | The situation is genuinely novel — do not fake certainty |

In these conditions: name the limitation, do not work around it.


Framework version: 1.4 — built to be challenged and revised.

Source & license

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

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

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Versions

  • v0.1.0 Imported from the upstream source.