Quality Attribute Discovery
SkillMediaUse when a problem under exploration needs its quality attributes (non-functional requirements) identified and prioritized before architecture and design begin. This should trigger when an issue's Quality Attribute Discovery point of view needs evaluation, or when a maintainer directly asks to discover and prioritize candidate quality attributes for a problem, before any ADR or design work starts. Part of Plinth Toolkit
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Quality Attribute Discovery skill
What this skill tells your AI
The instructions your AI receives, as published by jabrena/plinth in skills/025-quality-attribute-discovery/SKILL.md and read by ahel’s review.
Guide identification and prioritization of the quality attributes a future solution must satisfy, before architecture and design decisions begin. This is an interactive SKILL.
What is covered in this Skill?
- Identifying candidate quality attributes (for example performance, security, availability, maintainability, scalability, usability, observability) relevant to the problem
- Grounding each candidate in evidence from the problem frame, root causes, assumptions, and context map, not a generic checklist
- Prioritizing candidate quality attributes by stakeholder impact and risk
- Stopping at a prioritized discovery list rather than selecting or recording an architectural decision
- Explicitly not producing ADRs or an architecture direction itself
Constraints
Discover and prioritize candidate quality attributes as input to later architecture work; do not make or record the architecture decision here. When this technique is orchestrated by another workflow, the orchestrator owns clarifying-question sequencing; when applied standalone, ask directly.
- MUST read
references/025-quality-attribute-discovery.mdbefore applying Quality Attribute Discovery guidance - MUST ground each candidate quality attribute in evidence from the problem frame, root causes, assumptions, or context map
- MUST prioritize candidate quality attributes by stakeholder impact and risk, not list them unordered
- MUST stop at a prioritized discovery list without selecting or recording an architecture decision
- MUST NOT record an architectural decision, ADR, or design direction as part of this skill's output
- MUST NOT invent a quality attribute or priority when the available content is vague or ambiguous; flag the gap for a clarifying question instead
When to use this skill
- Discover the quality attributes for this problem
- Identify non-functional requirements before design begins
- Prioritize candidate quality attributes for this issue
- Apply quality attribute discovery before architecture decisions
- Draft the Quality Attribute Discovery section of a Functional Specification
Workflow
- Read the Reference
Read references/025-quality-attribute-discovery.md, then review the problem frame, root-cause findings, assumptions, and context map for evidence of quality pressure.
- Identify Candidate Quality Attributes
Identify candidate quality attributes grounded in that evidence, avoiding a generic unfiltered checklist.
- Prioritize by Impact and Risk
Prioritize the candidate quality attributes by stakeholder impact and risk if unmet.
- Stop Before Architecture Decisions
Stop at the prioritized discovery list; do not select an architecture approach or record an ADR here.
- Report the Discovery List
Report the prioritized quality attributes, stating explicitly that the output stops at this discovery list and does not select or record an architecture decision; flag any item left open pending a clarifying answer.
Reference
For detailed guidance, examples, and constraints, see references/025-quality-attribute-discovery.md.
Signals
- GitHub stars
- 439
- Forks
- 92
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
x-025-quality-attribute-discovery- Source
- github.com/jabrena/plinth