question-framing skillA
question-framing is agent-read markdown (skill) from ai-analyst-lab/ai-analyst: Structure analytical questions with the Question Ladder (Goal, Decision, Metric, Hypothesis), then fill the 7-field Analysis Design Spec, before touching data. Trigger on "analyze", "investigate", "look into", "why did", "what's happening with", "what happened with", "figure out", "explore", "deep dive", "what caused", "compare", "breakdown", "root cause", "show me", "pull", "calculate". Framing first, analysis second..
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
# Skill: Question Framing
## Purpose
Structure analytical questions using the Question Ladder framework so every analysis starts with a clear decision context, measurable success criteria, and testable hypotheses.
## When to Use
Apply this skill when starting any new analysis, when a user asks a vague question ("How are we doing?"), or when an analysis request lacks decision context. Always frame before analyzing.
## Instructions
### Pre-flight: Load Learnings
Before executing, check `.knowledge/learnings/index.md` for relevant entries:
- Read the file. If it doesn't exist or is empty, skip silently.
- Scan for entries under **"Question Framing"** and **"General"** headings (or related categories like "Business Context", "Methodology Notes").
- If entries exist, incorporate them as constraints or context for this execution.
- Never block execution if learnings are unavailable.
### The Question Ladder
Every analytical question climbs four rungs:
```
GOAL → What business outcome are we trying to achieve?
DECISION → What specific decision will this analysis inform?
METRIC → What will we measure to inform that decision?
…Read the whole file at its exact version.
How to install
mdr add ai-analyst-lab/ai-analyst/question-framing@git:20260902.b370de6mdr add ai-analyst-lab/ai-analyst/question-framing@sha256:a8a4d3818b0cf0fePin 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.
[](https://markdownregistry.com/a/art_bmvvwp2tyuskhbaf)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260902.b370de6 latest | 2026-09-02 | b370de6 | 12,359 B | A | view · diff |
| git:20260827.7ff2e25 | 2026-08-27 | 7ff2e25 | 12,236 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (12359 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
ai-analyst-lab/ai-analyst · 302 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_bmvvwp2tyuskhbaf GET https://markdownregistry.com/api/v1/resolve?ref=ai-analyst-lab/ai-analyst/question-framing GET https://markdownregistry.com/api/v1/blob/a8a4d3818b0cf0fefa1e2ee532bad39ecdd5c71f4ba09b40c69eae72c6b2d884
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