mcpField
I
inquiring

inquiring

github.com/tejas-kaleProductivity038 installsUpdated 3d ago
Repository

About inquiring

A question-focused interview skill that builds a claim tree from evidence, tests competing interpretations, and records what is settled or unknown. It is for users seeking a shared reading of a question, not a recommendation or action plan.

Key features

  1. 01Map questions into claim trees
  2. 02Research public claims and cite evidence
  3. 03Separate evidence gathering from user interpretation
  4. 04Track rounds and unsettled claims
  5. 05Record findings and computational artifacts

Use cases

  1. 01Assess whether a chart supports a conclusion
  2. 02Compare competing explanations for a result
  3. 03Investigate a question while recording uncertainty

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/tejas-kale/skills --skill inquiring

After installing, type/inquiringin Claude Code to confirm it loaded.

Bundled filesagents/openai.yaml

Details

From the project README

Interview the user until you share a reading of a question — what the evidence supports, not what to do next. Map this as a claim tree: every claim branches into the claims that hang off it (operationalizations, measurements, competing explanations, confidence).

Work the tree in rounds. The frontier is every claim whose prerequisites are already settled — the questions you can ask now without guessing at answers you haven't heard yet. Fill what you can from evidence first; ask the user only what the evidence cannot settle. Then wait.

Finding evidence is your job, never the user's. Dispatch a background research agent (or equivalent lookup) for a large primary-source hunt — don't block the rest of the frontier on it. The reading is the user's: put each unsettled interpretation to them and wait. Stress-test operationalizations, sample bias, and leaps from chart to conclusion. If the user's prior survives the evidence, record it as settled with that evidence.

If a decision appears ("what should we do?"), name it and stop — stay on claims. Do not start a design interview off the findings.

Round 0 — frame

Slug the question. If findings/<slug>.md already exists, reload it: settled claims stay settled; ask only the current frontier.

Otherwise write findings/<slug>.md before any fetch, containing: the restated question, a proposed operationalization, in-scope claims, and unknowns. Ask the frame (is this the question, is this a fair measure, any private constraints) in the round format below. Wait. Fetch starts in Round 1 after the user accepts or amends that frame.

Later rounds

  1. Fetch, compute, and cite against every public claim on the frontier. Parametric knowledge is a hypothesis, not a finding. Prefer primary sources and inspectable artifacts. User-supplied private data outranks a public source when they conflict — show the conflict.
  2. Update the findings file. Open a notebook only when a claim is settled by running code (see Artifacts).
  3. Curate the chat (see Chat). Ask the whole remaining frontier. Wait.

A claim whose answer depends on another claim still open in this round belongs to a later round.

Round format

Skip the preamble. Use the smallest visual that makes the point, with brief prose beside it: Mermaid, trees, or one HTML file. Point at file anchors; do not paste the findings file.

Data-shaped views are in scope when they are the smallest view: a 2-axis sketch, a tiny comparison table, a Mermaid of competing explanations, a sparkline-in-text, an HTML annotated chart. Decoration is not.

Each frontier item:

❓ **C1** - **<claim title>**: <one-line claim / operationalization>

**A.** …
**B.** …
**C.** bounded unknown / keep digging

➡️ **B** — <one line why>

One visual may sit above the letters when the options are easier to see than to read. Letter C (or the last letter) stays available as bounded unknown. If only one reading is honest, that reading is still an option, and the ➡️ still names it.

Evidence

A claim stays open until the findings file records all of:

  • the claim in one sentence
  • the operationalization
  • method (search, fetch, query, code)
  • sources or cells, with enough quote or output to check the claim
  • what was not searched or run
  • uncertainty / failure modes of the method
  • verdict: settled / bounded-unknown / needs you

Artifacts

Put files where the repo already keeps notes; if there is none, use findings/ and say the path.

  • findings/<slug>.md — canonical claim log for the session. One file; append rounds. Resume by reloading it.
  • findings/<slug>.ipynb — at most one per session, created on the first computational claim. Jupyter, Python 3, pandas-class tabular work, unless the repo is clearly another data stack. No notebook when nothing needs to run.
  • view-{description}.html — a round's view when Mermaid is not enough. Disposable. Do not HTML-wrap a plot the notebook already shows unless the plot needs a curated frame.

Chat is the round protocol. Files are the evidence locker.

Done

The frontier is empty: every in-scope claim is settled or explicitly bounded-unknown, each with documentary evidence. Stop. Wait for the user to confirm the shared reading. Do not start a design interview off the findings.

Comments

Markdown supported