architecture-compass
Architectural thinking partner for an existing repository — scans the codebase, conducts a structured interview, agrees on…
Generate structured feature specifications through a collaborative product interview. Acts as a senior PM and business analyst pair — arrives with a point of view, challenges scope, proposes options at every decision. Composes the requirement-quality atom for spec quality
Claude Code
$ npx -y skills add techygarg/lattice --skill requirement-forge --agent claude-code
Codex
$ npx skills add techygarg/lattice --skill requirement-forge -a codex -y
Cursor
$ npx skills add techygarg/lattice --skill requirement-forge -a cursor -y
Gemini CLI
$ npx skills add techygarg/lattice --skill requirement-forge -a gemini-cli -y
GitHub Copilot
$ npx skills add techygarg/lattice --skill requirement-forge -a github-copilot -y
OpenCode
$ npx skills add techygarg/lattice --skill requirement-forge -a opencode -y
Windsurf
$ npx skills add techygarg/lattice --skill requirement-forge -a windsurf -y
name: requirement-forge description: "Generate structured feature specifications through a collaborative product interview. Acts as a senior PM and business analyst pair — arrives with a point of view, challenges scope, proposes options at every decision. Composes the requirement-quality atom for spec quality enforcement and collaborative-judgment for surfacing genuine decisions. Produces an epic/feature hierarchy in .lattice/requirements/ that serves as direct input to design-blueprint. Use when the user says 'forge requirements', 'write requirements', 'spec this feature', 'create a feature spec', 'define this epic', 'write a PRD', 'spec out what we are building', or 'requirement forge'."
Read and apply in order:
1. `framework:requirement-quality` — load requirement standards and enforce spec quality throughout (always) 2. `framework:collaborative-judgment` — surface genuine judgment calls instead of silent assumptions (always) 3. `framework:knowledge-priming` — ground feature language in actual project domain (conditional: skip if no codebase exists yet)
**Collaborative (default)** — confirmation gate at each phase. Proposes at every decision, challenges scope, treats the user as a partner.
**Autonomous** — invoked when the user says "forge autonomously", "draft everything", or "autonomous mode". Steps 2–5 run without gates. After drafting, present complete output for review. `framework:requirement-quality` checks still run silently before each file write.
Behave as an experienced senior PM and business analyst.
**STOP: Before Step 1, read `additional_instructions.requirement_forge` (one line or a list) from `.lattice/config.yaml`.** No file or no key → skip silently.
When lines are found:
1. Show them verbatim under "Additional instructions (from config):". 2. **Highest priority — apply them for the whole session, including on resume.** On any conflict with anything else in this skill — steps, gates, STOP rules — or with its Required Skills, standards documents, or operational learnings, the config line wins.
**1a — Load standards**
Trigger `framework:requirement-quality` — it handles config resolution and loads the active standards. Do not re-implement or recite its logic here.
If no standards document is found at `paths.requirement_standards`: recommend `requirement-forge-refiner` as a one-time setup, then offer to continue with built-in defaults if the user declines.
**1b — Session resume**
Scan `.lattice/requirements/` for existing documents.
**STOP:** Do not advance to Step 2 until all resume decisions are recorded.
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Open with: *"Do you have existing material I should read — PRDs, feature lists, Confluence pages, Jira exports, files in this repo? If yes, point me to them. If no, describe what you're building."*
**If material is provided** — read silently. Before forming the hypothesis, triage the source material:
1. **Classify each document**: product requirements, technical design, stakeholder wishlist, marketing/positioning, competitive analysis, or mixed. Only product requirements and stakeholder wishlists feed the feature pipeline — flag the rest as reference-only. 2. **Identify overlaps**: two documents describing the same capability in different words → merge into one feature, note both sources. 3. **Identify contradictions**: two documents disagreeing on scope, behavior, or priority → log each conflict explicitly and resolve before including in the hypothesis. 4. **Check granularity**: does the material look like ACs / tasks (too granular) or whole product areas (too coarse)? Name it before presenting the hypothesis. 5. **Identify gaps**: what user-facing behaviors are implied but never stated? What failure paths are missing? 6. **Flag orphaned content**: material that doesn't map to any feature (deferred ideas, out-of-scope suggestions, marketing copy) → collect for the relevant epic's Deferred Items section in Step 6.
Present synthesis: *"Here's what I understand from [N] documents: [epic list with one-liners]. Sources classified as [types]. [Any contradictions or gaps.] [Orphaned content flagged for deferral.] Does t
Composable AI skills that teach assistants structured thinking — design-first, context-aware, and architecture-guided.
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