product-lens

Scans a local project codebase to produce a structured app context summary. Reports facts about the app's core features, data models, user journey, tech stack, and architectural patterns. Does not evaluate or judge. Examples: <example> Context: Need app context before evaluating whether to add a feature. user: "Scan app context for /path/to/my-ios-app" assistant: "I'll use the app-context-scanner agent to analyze the codebase." </example>

Evaluates a single product dimension from an indie developer perspective. Receives pre-merged sub-questions (universal + platform-specific) and scoring anchors directly in its prompt. Produces structured per-sub-question analysis with evidence citations and a 1-5 star dimension score. Examples: <example> Context: Evaluating Demand Authenticity for a local iOS project. user: "Evaluate Demand Authenticity for Delphi at /path/to/project" assistant: "I'll use the dimension-evaluator agent to assess demand authenticity." </example> <example> Context: Deep-dive teardown of Moat for an external app. user: "Teardown moat for Bear notes app" assistant: "I'll use the dimension-evaluator agent in deep mode to analyze the moat." </example>

Generates the mandatory extra modules for a product evaluation: Kill Criteria, Feature Necessity Audit, Elevator Pitch Test, Pivot Directions, and Validation Playbook. Receives dimension scores and module-specific instructions from the skill. Examples: <example> Context: Full evaluation complete, need extra modules. user: "Generate extras for Delphi evaluation" assistant: "I'll use the extras-generator agent to produce Kill Criteria, Feature Audit, Elevator Pitch, and Pivot Directions." </example> <example> Context: External app evaluation, no code access. user: "Generate extras for Bear notes evaluation" assistant: "I'll use the extras-generator agent. Feature Audit will be skipped since this is an external evaluation." </example>

Use this agent to group recent file and commit changes into likely feature slices so `recent-feature-review` can judge coherent chunks of work instead of raw files.

Evaluates a single feature assessment dimension from an indie developer perspective. Receives pre-merged sub-questions, app context, and signal anchors directly in its prompt. Produces structured per-sub-question analysis with a signal (Positive/Neutral/Negative) and confidence level (High/Medium/Low). Examples: <example> Context: Evaluating Demand Fit for adding a tagging feature to a notes app. user: "Evaluate Demand Fit for adding tags to NoteApp at /path/to/project" assistant: "I'll use the feature-dimension-evaluator agent to assess demand fit." </example> <example> Context: Evaluating Build Cost for adding sync to a todo app. user: "Evaluate Build Cost for adding cloud sync to TodoApp" assistant: "I'll use the feature-dimension-evaluator agent to assess build cost." </example>

Use when the user wants to compare multiple products or projects to decide which to focus on. Evaluates each app and produces a scoring matrix with recommendations.

Use for a quick demand reality check on a product idea or project. Runs only the demand validation dimension and Elevator Pitch test. Fast first-pass filter before committing to build.

Use when the user wants to evaluate a product — assess demand, market viability, moat, and execution quality from an indie developer perspective. Works on local projects (by reading code) or external apps (via web search).

Use when the user wants to evaluate whether an existing app should add a specific feature. Analyzes demand fit, journey contribution, build cost, and strategic value. Produces a GO/DEFER/KILL verdict with conditional follow-up: integration map (GO) or alternative directions (DEFER/KILL). Works on local projects only (requires code access).

Use for periodic scans over a project root such as ~/Code. Builds a root-level picture of active projects, current risks, and PKOS exchange artifacts for downstream ingestion.