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feature-evaluator

Structured evaluation of proposed features for existing projects.

Skill by autoencoders

IndexedCC-BY-4.0
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/autoencoders-feature-evaluator

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Structured evaluation of proposed features for existing projects. Use when developers want to assess whether a new feature should be built, understand tradeoffs, find alternatives, identify complementary features, or determine minimum viable implementations. Triggers on phrases like "evaluate this feature", "should we build", "feature proposal", "is this feature worth it", "feature assessment", "feature tradeoffs", or when asked to analyze the value and implementation options of a proposed addition to a codebase.

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/feature-evaluator

What's inside

Skill name
feature-evaluator
Description
Structured evaluation of proposed features for existing projects. Use when developers want to assess whether a new feature should be built, understand tradeoffs, find alternatives, identify complementary features, or determine minimum viable implementations. Triggers on phrases like "evaluate this feature", "should we build", "feature proposal", "is this feature worth it", "feature assessment", "feature tradeoffs", or when asked to analyze the value and implementation options of a proposed addition to a codebase.
License
CC-BY-4.0
Instructions
349 lines in SKILL.md · view on GitHub

Files (3)

  • SKILL.md
  • context-template.md · references/
  • evaluation-criteria.md · references/

SKILL.md (first lines)

# Feature Evaluator

Evaluate proposed features through structured critical analysis to determine value, alternatives, and optimal implementation paths.

## Execution Modes

This skill adapts to the pipeline execution mode:

| Mode | Behavior |
|------|----------|
| `full` | All phases, full depth |
| `fast` | Combined eval+plan output, risk-based gating |
| `prototype` | Abbreviated output (value + risks only) |
| `spike` | Skip evaluation entirely |

## Adaptive Depth

Scale evaluation depth to feature stakes:

| Feature Scale | Phases to Complete | Time Investment |
|---------------|-------------------|-----------------|
| **Small** (< 1 week, easily reversible) | Phases 1, 2, 5 (abbreviated) | 5-10 min |
| **Medium** (1-4 weeks, moderate risk) | All phases, standard depth | 15-30 min |
| **Large** (> 1 month, high stakes/irreversible) | All phases + reference file deep-dive | 30-60 min |

Ask about scale if unclear. Default to Medium.

## Context Gathering

If context is missing, request these essentials before evaluating:

**Must have:**
- What the project does (1-2 sentences)
- What the proposed feature does (plain English)
- Who requested it and why

**Helpful for deeper analysis:**
- Current pain points driving the request
- Existing components that might be relevant
- Constraints (deadline, team size, risk tolerance)
- Success metrics that matter

See [references/context-template.md](references/context-template.md) for full context template when doing formal evaluations.

## Evaluation Process

Execute phases in order. Produce concrete, specific outputs — avoid generic statements.

### Phase 1: Value Articulation

Analyze the feature's value proposition:

```
VALUE PROPOSITION
─────────────────
Problem: [Specific problem in one sentence]
User value: [What gets easier/faster/safer]
Business value: [Cost saved, risk reduced, revenue enabled]
Who benefits: [Specific user segments]
Who doesn't: [Users unaffected or potentially harmed]

Status quo cost: [What happens if we do nothing — quantify if possible]

Strategic fit: [High/Medium/Low] — [Why]
Urgency: [High/Medium/Low] — [Why now vs. later]

RISK ASSESSMENT
───────────────
Estimated effort: [< 1 week / 1-4 weeks / > 1 month]
Reversibility: [Easy / Moderate / Difficult / Irreversible]
Scope clarity: [Clear / Moderate / Unclear]

Risk tier: [Low / Medium / High]
```

**Risk Tier Determination:**
- **Low:** Effort < 1 week AND easily reversible AND clear scope
- **Medium:** Any moderate factor, no high-risk factors
- **High:** Effort > 1 month OR irreversible OR unclear scope

Risk tier controls flow in `fast` and `prototype` modes.
User value: [What gets easier/faster/safer]
Business value: [Cost saved, risk reduced, revenue enabled]
Who benefits: [Specific user segments]
Who doesn't: [Users unaffected or potentially harmed]

Status quo cost: [What happens if we do nothing — quantify if possible]

Strategic fit: [High/Medium/Low] — [Why]
Urgency: [High/Medium/Low] — [Why now vs. later]
```

The "status quo cost" is critical — it forces honest ROI assessment.

### Phase 2: Critical Analysis

Systematically challenge the feature:

**Why this might NOT help:**
- Misalignment risks (wrong problem, rare edge case, solves symptom not cause)
- Adoption risks (discoverability, habit change, trust)
- Complexity/maintenance burden
- Performance/reliability risks
- Security/privacy/compliance risks

**Alternative approaches using existing functionality:**
- What already exists that could be combined/reconfigured?
- Would documentation, training, or better defaults solve this?
- Is there a third-party solution?
- Would a different feature solve this AND other problems?

```
CRITICAL ANALYSIS
─────────────────
Potential drawbacks:
• [Concern 1] — Severity: [High/Med/Low], Likelihood: [High/Med/Low]
• [Concern 2] — Severity: [High/Med/Low], Likelihood: [High/Med/Low]
• [Concern 3] — Severity: [High/Med/Low], Likelihood: [High/Med/Low]

From autoencoders/skills, CC-BY-4.0.

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Last commit (this folder)
Feb 6, 2026 (9 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
CC-BY-4.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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feature-evaluator skill. Agent Mart. https://agentmart.dev/skills/autoencoders-feature-evaluator (last updated 2026-10-24)