tercel

Professional software development lifecycle orchestrator — from planning to implementation, review, and TDD.

Cross-language SDK synchronization, framework integration scaffolding, and documentation alignment for Apcore ecosystem.

Deep Project Intelligence & Technical Due Diligence Skill — comprehensive analysis of architecture, codebase, and strategic positioning.

Analyze a collection of documents to build a knowledge map, identify themes, find gaps, duplicates, conflicts, and staleness, then produce an organized analysis with improvement recommendations. Designed for document ecosystems (cross-repo docs, research collections, mixed-format doc repos) where the challenge is understanding the landscape, not auditing against code.

Audit existing project documentation for quality, completeness, consistency, and code alignment. Scans docs against the actual codebase to find stale references, missing coverage, internal contradictions, and quality issues. Generates a structured findings report with severity levels and actionable fix recommendations. Works on any project with a docs/ directory.

Lightweight project decomposition skill. Analyzes project scope through a brief interview and determines whether the project should be treated as a single feature or split into multiple sub-features. For multi-split projects, generates a project manifest listing sub-features, dependencies, and execution order.

Use when exploring a new idea before writing formal specifications. Guides users through iterative discovery, research, and critical analysis to crystallize vague ideas into validated requirement drafts. Includes anti-pseudo-requirement checks, competitive research, demand evidence gathering, and "What if we don't build this?" analysis. Supports pause/resume across sessions, stores ideas in the project's ideas/ directory, and graduates validated ideas into the spec-forge auto chain (idea → decompose → tech-design + feature specs).

Review spec-forge generated documents (tech-design + feature specs) for quality, completeness, and internal consistency. Finds issues like incomplete sections, contradictions, missing traceability, and vague specs, then optionally auto-fixes them. Supports iterative review-fix cycles with a maximum of 2 iterations.

Complete Codex development workflow for turning requirements, feature docs, or prompts into working code. Use when the user asks to plan implementation work, execute tasks, enforce TDD, review code, fix bugs, debug failures, verify completion, manage worktrees or branch finishing, dispatch parallel agents, port a project to another language, check progress, or run an end-to-end build flow. Supports complex orchestration across plan -> impl -> review -> fix -> verify, plus build, forge smart dispatch, worktree, finish, parallel, port, tdd, debug, and status workflows.

Debug and fix bugs with interactive upstream trace-back — diagnoses root cause level, confirms upstream document updates, and applies TDD fixes. Supports --repos flag for parallel bug fixing across multiple repositories.

Execute pending tasks for a feature — TDD-driven implementation with sub-agent isolation and progress tracking. Use when starting to build, implement, or code a planned feature, resuming partially completed work, or running the next task in a code-forge plan. Supports --repos flag for parallel implementation across multiple repositories.

Analyze documentation (or a prompt) and generate an implementation plan with task breakdown, TDD steps, and progress tracking. Use when breaking down a feature, creating tasks from docs or requirements, planning implementation work, or turning a spec into actionable steps.

Display code-forge feature dashboard with task-level progress from state.json, or show detailed status for a specific feature. Use when checking progress, asking "what's left", viewing task completion, or wanting a bird's-eye view of the project.

Use when reviewing code, handling review feedback, or posting a review to a GitHub PR — 15-dimension quality analysis PLUS an Acceptance Gate (runs the test suite fresh and reconciles every P0/P1 acceptance criterion against a named passing test, hard-blocking merge on any uncovered P0 or failing test) for features or entire projects (generate mode), structured evaluation and response to incoming review comments (feedback mode via --feedback flag), or automated PR review posted as a GitHub comment (--github-pr flag).

Use when encountering any bug, test failure, or unexpected behavior — enforces root cause investigation before fixes. Prevents symptom-fixing, masking bugs, and "just try this" approaches. For code-forge features, use code-forge:fix instead.

Use when implementation is complete and you need to merge, create a PR, or clean up — verifies tests pass, presents 4 structured integration options, executes chosen workflow, and cleans up worktrees. Pairs with code-forge:worktree.

Professional specification system for Codex. Use when the user asks to create, improve, review, audit, analyze, or propagate product/software documentation, including ideas, PRDs, SRS documents, technical designs, architecture/RFC docs, feature specs, test cases, documentation audits, document landscape analysis, and full idea-to-spec chains. Supports complex multi-skill orchestration: idea -> decompose -> tech-design + feature specs -> review, with optional PRD, SRS, test-cases, audit, analyze, and propagate workflows.

Analyze a collection of documents to build a knowledge map, identify themes, find gaps, duplicates, conflicts, and staleness, then produce an organized analysis with improvement recommendations. Designed for document ecosystems (cross-repo docs, research collections, mixed-format doc repos) where the challenge is understanding the landscape, not auditing against code.

Audit existing project documentation for quality, completeness, consistency, and code alignment. Scans docs against the actual codebase to find stale references, missing coverage, internal contradictions, and quality issues. Generates a structured findings report with severity levels and actionable fix recommendations. Works on any project with a docs/ directory.

Lightweight project decomposition skill. Analyzes project scope through a brief interview and determines whether the project should be treated as a single feature or split into multiple sub-features. For multi-split projects, generates a project manifest listing sub-features, dependencies, and execution order.

Use when exploring a new idea before writing formal specifications. Guides users through iterative discovery, research, and critical analysis to crystallize vague ideas into validated requirement drafts. Includes anti-pseudo-requirement checks, competitive research, demand evidence gathering, and "What if we don't build this?" analysis. Supports pause/resume across sessions, stores ideas in the project's ideas/ directory, and graduates validated ideas into the spec-forge auto chain (idea → decompose → tech-design + feature specs).

Generates professional Product Requirements Documents (PRDs) following industry-standard methodologies. This skill activates when the user asks to write PRD, create a product requirements document, draft product requirements, do product planning, do feature planning, write a product spec, or create a product document. It synthesizes best practices from the Google PRD framework, the Amazon Working Backwards methodology, and the Stripe Product Spec approach to produce comprehensive, actionable PRDs tailored to the user's project.

Walk an upstream documentation change downstream — when a PRD, SRS, tech-design, or feature spec is edited, find every dependent document, identify which sections are now stale, and interactively update them to keep the entire doc chain consistent. Use after editing any spec-forge document, or run periodically with --since to catch accumulated drift.

Review spec-forge generated documents (tech-design + feature specs) for quality, completeness, and internal consistency. Finds issues like incomplete sections, contradictions, missing traceability, and vague specs, then optionally auto-fixes them. Supports iterative review-fix cycles that run until the review converges — passing, or a round with no net reduction in findings — typically 1–2 rounds.

Technical Evangelist & Growth Skill — transform code and projects into high-impact content for developer platforms.

Analyze a technical project and plan a multi-platform content series for its promotion. Scans README, source code, and tech stack to generate content ideas and a publishing schedule across Dev.to, Hashnode, X.com, Hacker News, and Reddit.

Generate a deep-dive technical analysis report for developers, tech leads, and AI investors. Performs 4-phase analysis: Deep Scan → Market Intelligence → Value Modeling → Report Generation. Outputs include architecture diagrams (Mermaid), data-driven competitor matrices, and investment assessments.

Transform raw code snippets into narrative-driven explanations — the "story" of the code. Adds context, narrative arc, step-by-step breakdowns, and trade-off analysis.

Generate a platform-specific technical draft based on project context. Supports Dev.to, Hashnode, Hacker News, Reddit, X.com Articles, and X.com Threads — each with a unique persona and structure.

Critique a technical draft by simulating real-world developer community feedback. Adopts three personas — Skeptical HN Reader, Practical Dev.to Junior, and Anti-AI Advocate — to identify fluff, missing benchmarks, and inauthentic voice.

Suggest where to insert GIFs, images, diagrams, and code screenshots to improve readability and engagement in technical drafts. Provides placement recommendations and descriptive captions.

Stage-Aware Project Intelligence & Strategic Due Diligence — evaluates projects against the criteria that matter at their lifecycle stage, from concept to market leader.

Stage-aware due diligence analysis of a project across business, technical, and moat/strategy dimensions, weighted by lifecycle stage. Supports remote URLs, local directories, and local files.

Side-by-side comparison of 2+ competing projects with stage-fair scoring. Supports mixing remote URLs and local paths. Produces a comparison matrix with ranked recommendation.

Generate a polished, professional stage-aware due diligence report. Supports remote URLs, local directories, and local files as analysis targets.

Quick scan of a project — gather metadata, key metrics, lifecycle stage classification, and first impressions. Supports remote URLs, local directories, and local files.

Professional Gemini CLI Skill Architect — specialized in scaffolding, converting (Claude to Gemini), and refactoring/optimizing skills.