Summary
A gap analysis cross-referencing 9 planned SDLC agents against the 21 existing ai-helpers skills identified 27 proposed new skills for patternfly/ai-helpers, organized into a number of proposed epics.
This spike evaluates each proposed skill for feasibility, value, and scope — then creates pruned Jira epics in ai-helpers with refined skill lists the team can estimate and prioritize.
Motivation
The gap analysis was intentionally exhaustive — it decomposed every agent opportunity into discrete skills to ensure nothing was missed. Before committing to epics, we need to:
- Validate that each skill is actually needed — some may be covered by extending existing skills, MCP Q2 extensibility, or harness-level capabilities.
- Prune skills that are premature — some depend on infrastructure or decisions that aren't settled.
- Consider if there are skills which would be better than the ones proposed
- Right-size the epics — current groupings came from gap analysis categories; real epics should be scoped for delivery.
- Resolve open questions that affect skill scope.
Scope
In scope
Out of scope
- Building or implementing any skills — this is evaluation only
Evaluation Criteria
For each proposed skill, assess:
Criterion
Question
Agent demand
How many agents need this? Is it on any agent's critical path?
Existing coverage
Does an existing ai-helpers skill, MCP capability, or external tool already cover this?
Feasibility
Can this be built with current infrastructure? What's blocking it?
Standalone value
Does this provide value on its own, or only as part of a larger pipeline?
Effort
Rough t-shirt size (S / M / L / XL)
GH Issue 57
Upstream URL: #57
Reporter: Nicole Thoen
Assignees:
The linked distribution (PF-4034) and harness investigation (PF-4035) spikes produced findings that affect how the 27 proposed skills should be evaluated — review those before starting this work.
Jira Issue: PF-4014
Summary
A gap analysis cross-referencing 9 planned SDLC agents against the 21 existing ai-helpers skills identified 27 proposed new skills for patternfly/ai-helpers, organized into a number of proposed epics.
This spike evaluates each proposed skill for feasibility, value, and scope — then creates pruned Jira epics in ai-helpers with refined skill lists the team can estimate and prioritize.
Motivation
The gap analysis was intentionally exhaustive — it decomposed every agent opportunity into discrete skills to ensure nothing was missed. Before committing to epics, we need to:
Scope
In scope
All 27 proposed ai-helpers skills from the gap analysis
The proposed epics from the unified plan
Out of scope
Evaluation Criteria
For each proposed skill, assess:
Criterion
Question
Agent demand
How many agents need this? Is it on any agent's critical path?
Existing coverage
Does an existing ai-helpers skill, MCP capability, or external tool already cover this?
Feasibility
Can this be built with current infrastructure? What's blocking it?
Standalone value
Does this provide value on its own, or only as part of a larger pipeline?
Effort
Rough t-shirt size (S / M / L / XL)
GH Issue 57
Upstream URL: #57
Reporter: Nicole Thoen
Assignees:
The linked distribution (PF-4034) and harness investigation (PF-4035) spikes produced findings that affect how the 27 proposed skills should be evaluated — review those before starting this work.
Jira Issue: PF-4014