Tercel

Generates professional Test Plan and Test Cases documents following IEEE 829 test documentation standards, ISTQB testing methodologies, and Google Testing Blog best practices. This skill activates when the user asks to write a test plan, create test cases, draft a test plan document, create a test cases document, define a test strategy, write a QA document, produce a testing document, draft a test specification, or build a quality assurance plan. It produces comprehensive, structured test documentation that ensures thorough coverage, traceability to requirements, and a clear path from test design through execution and defect management.

Use when writing a PRD, product spec, or product requirements — follows Google/Amazon/Stripe methodologies

Use when generating software specifications — full chain (Idea→Decompose→Tech Design + Feature Specs) or individual documents

Use when writing an SRS, requirements spec, or functional/non-functional requirements — follows IEEE 830 with traceability

Use when writing a tech design, architecture doc, RFC, or design document — follows Google Design Doc format

Use when writing test cases, generating tests, supplementing test coverage, or improving test completeness — auto-scans project, designs multi-dimensional test cases with coverage matrix

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 with a maximum of 2 iterations.

Generates professional Software Requirements Specification (SRS) documents based on IEEE 830, ISO/IEC/IEEE 29148, and Amazon technical specification standards. This skill activates when the user needs a requirements document, requirements specification, SRS, functional requirements, non-functional requirements, software requirements, requirements analysis, or requirements engineering. It formalizes product needs into structured, testable, and traceable requirements with unique IDs, acceptance criteria, use cases, a CRUD matrix, and a full traceability matrix linking back to the upstream PRD.

Generates professional Technical Design Documents following industry-standard engineering practices. This skill activates when the user asks to write a technical design, create an architecture design, draft a design doc, write a technical proposal, do system design, create a technical design document, write an RFC, create a design document, or produce an architecture document. It synthesizes best practices from the Google Design Doc format, the RFC template structure, and Uber/Meta engineering design standards to produce comprehensive, implementable technical designs tailored to the user's project and codebase.

Generates structured test case sets with multi-dimensional coverage from project code analysis or specification documents. This skill activates when the user asks to write test cases, generate tests, supplement tests, create test coverage, or improve test completeness. It auto-scans the project to extract testable units (APIs, functions, components, CLI commands, tool definitions), identifies coverage gaps, designs test cases across multiple dimensions (coverage depth, input types, interaction patterns), and produces a structured test case document with coverage matrix. Includes test strategy and methodology by default. Use --formal flag to add management sections (environment, roles, schedule, defect management).

Use when you want end-to-end implementation from feature spec or prompt to working code — auto-chains test-cases → plan → impl → review → verify. Works with or without existing documentation.

Show all code-forge commands and usage guide

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.

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.

Use when facing 2+ independent problems that can be solved concurrently — dispatches one sub-agent per problem domain for parallel investigation and fixing. For parallel task execution within a feature, use code-forge:impl instead.

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.

Port a documentation-driven project to a new target language — initializes project skeleton, analyzes reference implementation, and batch-generates plans for selected features. Use when converting a project to another language, rewriting in a different language, or creating a multi-language SDK from existing feature specs.

Use when reviewing code, handling review feedback, or posting a review to a GitHub PR — 15-dimension quality analysis 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).

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 implementing any feature or fix outside code-forge workflow — enforces Red-Green-Refactor cycle with mandatory test-first discipline. Supports three modes: (1) Standalone — ad-hoc TDD for quick changes, (2) Auto-Analysis — runs the full spec-forge:test-cases analysis pipeline (project profile, four-layer deep scan, multi-dimensional coverage) then implements all cases via TDD, (3) Driven — reads a test-cases.md document and implements each case via TDD.

Use before claiming work is done, fixed, or passing — requires running verification commands and confirming output before any success claim. Prevents false completion claims, unverified assertions, and "should work" statements.

Use when starting feature work that needs workspace isolation — creates git worktree with automatic project setup and baseline test verification. Ensures worktree directory is git-ignored and safe. Integrates with code-forge:impl and code-forge:finish.