ot-spec-writing

Write and review feature specifications with skeleton-first drafting and severity-ranked architectural review.

Updated Sep 10, 2026
One-click install
npx skills add https://github.com/triage-software/skills --skill ot-spec-writing-triage-software
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ot-spec-writing
Source: https://github.com/triage-software/skills/tree/main/skills/ot-spec-writing
Command: npx skills add https://github.com/triage-software/skills --skill ot-spec-writing-triage-software

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Writing feature specifications that are rigorous enough to drive implementation is slow and inconsistent, and reviewing them against a project's architecture rules requires staff-engineer discipline that is hard to sustain. This Skill structures spec drafting and review so every spec ends with a phased, testable implementation plan. ## Core Features & Use Cases - Skeleton-first drafting with an Open Questions gate: Start with a minimal TLDR plus critical unknowns, block on answers before designing, then iterate into a full spec with architecture, data model, API contracts, and edge cases. - Severity-ranked architectural review: Review specs against the repository's own agent instructions and canonical primitives, producing Critical/High/Medium/Low findings with evidence and corrections. - Autonomous mode for unattended pipelines: Under --autonomous, resolve open questions with the most reversible defaults, mark high-stakes ones as needing human confirmation, and feed the phased plan directly into ot-auto-create-pr. - Use Case: A team needs a spec for adding rate limiting to a login endpoint. The Skill drafts a skeleton, asks blocking questions, researches market leaders, then produces a phased implementation plan that an automation skill executes phase by phase. ## Quick Start Ask the agent to write a spec for your feature, for example: write a specification for adding rate limiting to the login endpoint.

Frequently Asked Questions about ot-spec-writing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a feature specification with an AI agent?▼

Invoke the skill with your feature idea and it drafts a skeleton spec first: TLDR, problem statement, and a numbered Open Questions block for critical unknowns. After you answer, it iterates into architecture, data model, API contracts, and a phased implementation plan.

How to review a software design spec for architectural issues?▼

The review mode applies a staff-engineer checklist covering scope cohesion, canonical primitives, contract compatibility, reversibility, and failure scenarios. Findings are ranked Critical/High/Medium/Low with cited evidence and a recommended correction for each.

Can spec writing run autonomously without user interaction?▼

Yes, the --autonomous flag resolves Open Questions itself using the most reversible, lowest-blast-radius defaults and records them in a Resolved assumptions section. High-stakes defaults are marked as needing human confirmation and surfaced to the calling skill.

Does the spec workflow require repository configuration files?▼

No, the .ai/agentic.config.json config is optional and only resolves the specs directory, defaulting to .ai/specs. Without config, the skill uses the repo's existing design-doc area such as docs/specs or rfcs, or proposes the default after confirming.

What are the limitations of AI-generated feature specs?▼

The skill never edits code and produces only the document, so implementation still requires a separate execution step. Interactive runs hard-stop at the Open Questions gate, and review verdicts are limited by the evidence actually examined, which the report states explicitly.