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
Shubhamsaboo/awesome-llm-apps/agent_skills/thinking-out-loud/SKILL.md
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
Decision brief
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…
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/Shubhamsaboo/awesome-llm-apps --skill "agent_skills/thinking-out-loud"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
Asking clarifying questions is good, and the interview below does it. But questions alone cannot secure a ramble, for two structural reasons:
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.…
A message is a long, weakly punctuated stream of consciousness with
Short requests that are already clear
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.
Permission review
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
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 89/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 130,408 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
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.
Asking clarifying questions is good, and the interview below does it. But questions alone cannot secure a ramble, for two structural reasons:
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.
Compression rules, non-negotiable:
Close by inviting corrections and offering the interview.
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.
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.
After the user approves the echo, offer exactly three options:
docs/rambles/YYYY-MM-DD-<topic>.mdThe approved brief then governs the rest of the session: honor its decisions and constraints without re-asking.