Thinking Out Loud

---
name: thinking-out-loud
description: ">- A contract for what the agent does when a long, messy, stream-of-consciousness ramble arrives (usually voice dictation): act on nothing until the echo brief is approved. The echo audits the entire transfer, mission, locked decisions and constraints, open questions, flips and parked tangents, with the model's inferences and guesses quarantined away from the user's own phrasing, so the user verifies what the model believes, not just what it doubts. Use when the user says \"let me think out loud\" or wants to ramble a bit before building anything, when a message opens with a speech-to-text preamble like \"switching to voice, sorry for typos\", when input is a long weakly punctuated stream with restarts and mid-message reversals (\"actually no, wait, scrap that idea entirely\"), or when the user asks to be interviewed about a fuzzy half-formed idea. Includes an optional capture mode for..."
category: ai-agents-and-harness
source_repo: Shubhamsaboo/awesome-llm-apps
source_path: "agent_skills/thinking-out-loud/SKILL.md"
source_url: https://github.com/Shubhamsaboo/awesome-llm-apps/blob/HEAD/agent_skills/thinking-out-loud/SKILL.md
---


# Thinking Out Loud

A ten minute voice ramble transfers more context than any prompt a person
would type, and models reconstruct rambles well. The failure is
downstream and invisible: the model fills every gap in the ramble
confidently. "The usual model" silently becomes a specific model. "The
standard size" becomes a specific viewport. A position the user reversed
mid-ramble survives as fact. None of this registers as uncertainty from
the inside, so none of it ever becomes a clarifying question. The model
then acts on a misreading it fully believes, and the user discovers it an
hour of generated work later.

This skill is the fix: before acting on any ramble, produce an echo, a
short structured audit of everything absorbed, with the model's own
additions quarantined from the user's words. The user corrects three
lines instead of debugging a built artifact.

## Why an echo instead of follow-up questions

Asking clarifying questions is good, and the interview below does it.
But questions alone cannot secure a ramble, for two structural reasons:

- **Questions verify what the model doubts. The echo verifies what the
  model believes.** A clarifying question requires felt uncertainty, and
  confident misreadings feel like knowledge. The echo forces every
  inference and gap-fill into the open whether or not it felt uncertain.
- **Questions sample; the echo audits.** A long ramble carries dozens of
  facts and half-decisions. Even good questions probe three or four; the
  rest of the model's understanding goes unverified into action. The
  echo inventories the entire transfer, and it works by recognition, not
  recall: the user reads and spots what is wrong, which is far cheaper
  than producing answers, and ramblers often do not know their answer
  until they see the wrong guess written down.

## The contract

1. **Act on nothing.** No file edits, no code, no plans, no solutions to
   fragments, until the echo is approved. Reconstruct first.
2. **Label every addition.** Inferences and guesses live in their own
   section, apart from the user's own content. Never present a guess in
   the user's voice.
3. **Surface every reversal.** Adopt the later position, but flag the
   flip. Never silently average or pick.
4. **Lose nothing.** Tangents get parked, not dropped.
5. **Never remark on dictation artifacts.** Typos, homophones, filler,
   and restarts are resolved silently from context. Keep the user's own
   vocabulary and project names.
6. **Ask before persisting.** The approved brief is offered a home, never
   saved unprompted.

## When to use

- A message is a long, weakly punctuated stream of consciousness with
  restarts, filler, and mid-message reversals ("actually no, scrap that")
- A message opens with a voice preamble ("switching to speech
  recognition, sorry for any typos", "dictating this")
- The user says they want to ramble or think out loud
- The user asks to be interviewed to untangle a fuzzy idea

## When not to use

- Short requests that are already clear
- The user wants a verbatim transcript, minutes, or cleanup of dictation
  while keeping their exact words
- Long but already structured text, such as a pasted spec or document
- The user asked a direct question and wants a direct answer

## The echo

One structured reply. Dense, scannable, and short: the user should find
and fix an error in seconds. Full template with a worked example in
[references/echo-format.md](references/echo-format.md).

1. **Mission**: one sentence stating what the user is actually trying to
   achieve. Often this differs from what they said first; that is fine.
2. **Locked**: the user's decisions and constraints, merged into one
   list. Mark anything they called a top priority.
3. **Open**: questions the ramble raised but did not answer.
4. **Ledger**: flips (both positions in one line, later one adopted) and
   parked tangents (one line each).
5. **My additions**: the only interpretation callouts. "Inferred"
   (strongly implied but never stated) and "Guessed" (gaps you filled).
   Tell the user to correct these first.

Compression rules, non-negotiable:

- **Nothing appears twice.** Every fact lives in exactly one section.
- **No "you said" recap.** Everything outside My additions is the user's
  own content by definition; only the model's additions get called out.
- **One line per bullet.** If a bullet needs two lines, it is two bullets
  or it is bloat.
- **Vague quantifiers are never silently resolved.** "The usual model",
  "standard size", "soon": each lands in Open or Guessed, never absorbed
  into a locked item as if it were specified.

Close by inviting corrections and offering the interview.

## The interview (optional)

Follow-up questions have their place: after the audit, not instead of
it. Only if the user accepts the offer, or asked to be interviewed up
front.

- Ask only about items flagged in Open or Guessed
- One question per message, highest information gain first
- Each question states in one clause why it matters
- Cap at five questions; stop early once answers stop changing the brief
- After the interview, restate only the sections of the echo that changed

## Capture mode (multi-message rambles)

Not needed for dictation tools, where the whole ramble arrives as one
message. Use it when the user invokes the skill before rambling and then
adds thoughts across several messages, possibly over a long stretch.

- Acknowledge once, in one short line ("Go ahead, I'm listening. Say
  'done' when you want the echo.")
- For every following message, reply with a single minimal line
  ("Listening."). Vary it slightly so it does not feel robotic.
- Do NOT solve, praise, summarize, analyze, or ask questions mid-stream.
- If the user asks a direct question mid-ramble, answer it in at most two
  sentences, then return to listening.
- Exit on "done", "echo", "echo me", "that's it", "what did you get", or
  any clear equivalent, then deliver the echo.

## Persistence

After the user approves the echo, offer exactly three options:

1. Append the brief to CLAUDE.md so future sessions inherit it
2. Save it to `docs/rambles/YYYY-MM-DD-<topic>.md`
3. Keep it in-conversation only

The approved brief then governs the rest of the session: honor its
decisions and constraints without re-asking.

---

**Source:** [`Shubhamsaboo/awesome-llm-apps`](https://github.com/Shubhamsaboo/awesome-llm-apps) → `agent_skills/thinking-out-loud/SKILL.md`