AI Specification Writer
Most AI spec writers take your prompt and return a document. That document could describe any project. It has no idea your auth system uses magic links, that your UserService already handles role-based access, or that your API follows a specific pattern.
Tekk.coach reads your codebase before writing the first word. Every question is grounded in what it found. Every subtask references the actual files. Every spec is yours — not a template with your project name swapped in.
Connect your repo. Describe the problem. Get a spec your coding agent can actually execute.
How Tekk.coach Writes Specifications
The moment you start a planning session in Tekk, the agent reads your codebase. Not a summary — the actual code. Semantic search across your files, regex lookups, directory structure, framework detection, dependency analysis. It knows what you're working with before you answer the first question.
Then it asks questions. Not "who is the user?" — your code already shows that. Instead: "Your UserService handles role-based access through a middleware chain. Should this feature extend that pattern, or does it need a separate permission model?" Every question is specific to your repo.
After your answers, it presents options. Two or three architecturally distinct approaches, each with concrete tradeoffs. Not abstract pros and cons — actual implications for your specific stack.
Then it writes the spec. It streams directly into a BlockNote rich text editor — a living document you can edit immediately. Not a chat message you copy-paste. Not a static markdown file you email around. A working specification your team builds from.
The spec includes: a TL;DR, explicit Building and Not Building scope boundaries, subtasks with acceptance criteria and file references, assumptions with risk levels, and validation scenarios. When Tekk hands this to Cursor or Claude Code, the agent knows exactly what to build, where to build it, and what done looks like.
Key Benefits
Specs that reference your actual files Every subtask names the specific files and patterns to touch. Your coding agent stops guessing. It executes against real targets.
Questions that know your codebase Generic questions produce generic specs. Tekk reads your code first — questions are grounded in your actual architecture, not a blank slate.
Explicit scope protection Every spec includes a "Not Building" section. You define the boundaries before anyone writes code. Scope creep requires a deliberate decision, not a default.
A living document, not a chat message The spec streams into a rich text editor. Edit it, share it, build from it. It stays connected to the planning session that created it.
Best practices built in For anything outside your current expertise — a new API, an auth pattern, a data pipeline design — Tekk searches the web during planning and folds current best practices into the spec.
How It Works
Step 1: Connect your repository Link your GitHub, GitLab, or Bitbucket repo. Tekk reads the codebase — languages, frameworks, file structure, dependencies. This happens before the planning session begins.
Step 2: Describe what you're building Open a task in Tekk and describe the feature or problem in plain language. No template to fill out.
Step 3: Answer grounded questions The agent asks 3-6 questions based on what it found in your code. Each question is specific to your repo. You answer; the agent builds on your answers without starting over each turn.
Step 4: Review your options For non-obvious problems, the agent presents 2-3 architectural approaches with honest tradeoffs. You pick the direction. For straightforward features, it skips straight to the spec.
Step 5: Get the spec The full specification streams into your task editor in real time. TL;DR, scope boundaries, subtasks with file references and acceptance criteria, assumptions with risk levels, validation scenarios. Edit it directly. It's your working document.
Who This Is For
Developers building with AI coding agents. If you're using Cursor, Claude Code, or Codex and your agents keep flailing — producing code that doesn't match your existing patterns, missing edge cases, needing constant re-prompting — the problem is spec quality. Tekk fixes that at the source.
Solo founders and small technical teams. You don't have a senior architect on call. You're making implementation decisions yourself, sometimes in domains where you're not an expert. Tekk reads your code and brings that expertise to the planning session. You get a spec that reflects your actual architecture, not a generic best-practice template.
Anyone who's tired of copy-pasting context into chat. The .cursorrules file and the CONTEXT.md you maintain manually — that's a workaround for the codebase-blindness problem. Tekk solves it structurally.
This is not the right tool for enterprise teams that need Jira-style workflow governance, or for senior architects who already know exactly how to spec and just want a typist.
What Is an AI Specification Writer?
An AI specification writer is a tool that uses AI to generate structured technical documents defining what a feature should do, how it should behave, and how it should be built. In software development, a technical spec typically includes scope definition, subtasks with acceptance criteria, architectural decisions, assumptions, and validation scenarios.
The current generation of AI spec tools follows a prompt-in, document-out pattern. You describe what you want to build; the AI generates a spec. These tools work, but the output is context-free — the AI has no knowledge of your actual codebase, your existing patterns, or your current architecture. The spec could describe any project.
The next generation — and what Tekk.coach does — is codebase-first spec generation, also called automated spec generation from live code. The AI reads the repository before generating anything. Questions are grounded in what it found. Subtasks reference real files. The spec is tightly coupled to your specific project, not a generic template.
As AI coding agents become the primary way software gets written, specification quality becomes the critical bottleneck. An agent is only as good as the spec it receives. Tools that generate accurate, file-referenced, scope-bounded specs are now the differentiator between coding agents that ship and coding agents that flail.
Ready to Write Specs That Know Your Code?
Stop pasting context into chat windows and hoping the output matches your architecture. Connect your repo, describe the problem, and get a technical spec grounded in your actual codebase — with file references, acceptance criteria, and scope boundaries your coding agent can execute against.