Home / jellydn / my-ai-tools · configs/amp/plugins/my-ai-tools-skills/skills/spec-interview/SKILL.md · GitHub

spec-interview skillA

spec-interview is agent-read markdown (skill) from jellydn/my-ai-tools: Clarify requirements through targeted questions — uncovers unknown unknowns in specs.

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Spec Interview

## When to Use

Use this skill when:
- Feature requirements are vague or incomplete
- You have a general idea but lack specifics
- Stakeholders said "you know what I mean"
- The spec has obvious gaps
- Making assumptions that could be wrong

## What It Does

The agent interviews you to **uncover unknown unknowns** in your feature specification, focusing on questions that would change architectural decisions.

## How to Execute

### Step 1: Review Initial Spec

Analyze what the user provided:
- Explicit requirements (what they said)
- Implicit requirements (what they assumed)
- Missing details
- Ambiguous areas

### Step 2: Categorize Gaps

Identify question categories:

**Scope & Boundaries**:
- What's in scope vs out of scope?
- Edge cases to handle?
- MVP vs future iterations?

**User Experience**:
- What happens when...?
- Error states and recovery?
- Loading and async states?

**Technical Decisions**:
- Performance requirements?
- Data consistency needs?
- Integration points?
- Security considerations?

**Architecture Impact**:
- Does this change existing patterns?
- New abstractions needed?
- Migration strategy for existing data?
…

Read the whole file at its exact version.

How to install

Latest version
mdr add jellydn/my-ai-tools/spec-interview@git:20260814.d1987f5
Exact content
mdr add jellydn/my-ai-tools/spec-interview@sha256:371f6c225c08e362

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

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Versions

versioncommittedcommitsizeaudit
git:20260814.d1987f5 latest2026-08-14 d1987f5 8,320 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (8320 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

jellydn/my-ai-tools · 121 stars · license MIT · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_iysqisq5kt7sxufx
GET https://markdownregistry.com/api/v1/resolve?ref=jellydn/my-ai-tools/spec-interview
GET https://markdownregistry.com/api/v1/blob/371f6c225c08e362b9f3bb048e7f4a461c2bd34944a6b024ca4b96ca872d3ff3

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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