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talk-stack-humans-architect-ai-writes-code

Explains Paul Stack's architecture-first AI workflow and helps create safe design artifacts: intent documents, architecture constraints, planner/reviewer loops, UAT criteria, and agent-output review gates. Use when the user asks about humans owning architecture while agents implement, why vibes do not scale, or applying the talk to team workflow design.

67

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, mostly lean reference skill with concrete templates and clear workflows. Its main weakness is progressive disclosure: the body references outline.md, quote.md, and transcript.md, but no references/ bundle directory exists, so those paths are broken.

Suggestions

Add the missing bundle files (outline.md, quote.md, transcript.md) under references/, or remove the references and inline the essential content, so the Read Order navigation actually resolves.

Add an explicit validate-then-fix-then-retry feedback loop to the application workflow (e.g., after 'Reject output', restate the recovery step) to strengthen workflow clarity.

De-duplicate the artifact list between 'What This Skill Produces' and the Output Templates to tighten conciseness.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence, but the artifact list appears twice — once in 'What This Skill Produces' and again implicitly across Output Templates — which could be tightened.

4 / 5

Actionability

Provides concrete fill-in templates (Goal/Boundaries/Review points/Evidence/Open questions) and numbered workflows with specific steps; appropriate for an instruction-only skill though it lacks executable code.

4 / 5

Workflow Clarity

Both the factual-question and application workflows are clearly sequenced with an explicit review gate ('Reject output that cannot be reviewed against intent'), but no explicit validate-then-fix-then-retry feedback loop is spelled out.

4 / 5

Progressive Disclosure

The Read Order clearly signals one-level-deep references to outline.md, quote.md, and transcript.md, but those files are not present in the bundle, so the signaled navigation does not actually resolve.

3 / 5

Total

15

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description with concrete artifacts, explicit trigger guidance, and a clear niche. The only minor gap is trigger-term breadth, which leans on the talk's specific phrasing rather than wider synonyms.

DimensionReasoningScore

Specificity

Lists multiple concrete artifacts — 'intent documents, architecture constraints, planner/reviewer loops, UAT criteria, and agent-output review gates' — giving comprehensive coverage of what the skill produces.

5 / 5

Completeness

Clearly states what it does (explains the workflow, creates design artifacts) and provides an explicit 'Use when...' clause with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural triggers like 'humans owning architecture while agents implement', 'why vibes do not scale', and 'applying the talk to team workflow design' are phrases a user would say, though coverage is somewhat niche to the talk's terminology rather than broad synonyms.

4 / 5

Distinctiveness Conflict Risk

A clearly defined niche — Paul Stack's architecture-first AI workflow — with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

19

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
jscraik/Agent-Skills
Reviewed

Table of Contents

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