feature-evaluator
Structured evaluation of proposed features for existing projects.
Skill by autoencoders
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Install
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
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
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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A simple test skill that says hi.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Feb 6, 2026 (9 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- CC-BY-4.0
- Repository
- github.com/autoencoders/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
feature-evaluator skill. Agent Mart. https://agentmart.dev/skills/autoencoders-feature-evaluator (last updated 2026-10-24)