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Shubhamsaboo/awesome-llm-apps/agent_skills/thinking-out-loud/SKILL.md

thinking-out-loud

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

Source repository stars
130,408
Declared platforms
0
Static risk flags
0
Last source update
2026-08-03
Source checked
2026-08-04

Decision brief

What it does—and where it fits

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 stan…

Best for

  • A message is a long, weakly punctuated stream of consciousness with
  • A message opens with a voice preamble ("switching to speech
  • The user says they want to ramble or think out loud

Not for

  • Short requests that are already clear
  • The user wants a verbatim transcript, minutes, or cleanup of dictation

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/Shubhamsaboo/awesome-llm-apps --skill "agent_skills/thinking-out-loud"
Safe inspection promptEditorial

Inspect the Agent Skill "thinking-out-loud" from https://github.com/Shubhamsaboo/awesome-llm-apps/blob/779e9f9bcf87fa8cd95870a438b70b84e47d3173/agent_skills/thinking-out-loud/SKILL.md at commit 779e9f9bcf87fa8cd95870a438b70b84e47d3173. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    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 theQuestions sample; the echo audits. A long ramble carries dozens ofAsking clarifying questions is good, and the interview below does it. But questions alone cannot secure a ramble, for two structural reasons:
  2. 02

    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.…

    Act on nothing. No file edits, no code, no plans, no solutions toLabel every addition. Inferences and guesses live in their ownSurface every reversal. Adopt the later position, but flag the
  3. 03

    When to use

    A message is a long, weakly punctuated stream of consciousness with

    A message is a long, weakly punctuated stream of consciousness withA message opens with a voice preamble ("switching to speechThe user says they want to ramble or think out loud
  4. 04

    When not to use

    Short requests that are already clear

    Short requests that are already clearThe user wants a verbatim transcript, minutes, or cleanup of dictationLong but already structured text, such as a pasted spec or document
  5. 05

    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.

    Mission: one sentence stating what the user is actually trying toLocked: the user's decisions and constraints, merged into oneOpen: questions the ramble raised but did not answer.

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score89/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars130,408SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
Shubhamsaboo/awesome-llm-apps
Skill path
agent_skills/thinking-out-loud/SKILL.md
Commit
779e9f9bcf87fa8cd95870a438b70b84e47d3173
License
Apache-2.0
Collected
2026-08-04
Default branch
main
View the original 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.

  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.