Q
Quinnod345/ponder
Convergent deliberation loop for coding agents: multi-pass, coverage-gated, append-only ledger review and…
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site
Install & config
Client config (built from the install command this repo gives)
{
"mcpServers": {
"quinnod345-ponder": {
"command": "npx",
"args": ["skills"]
}
}
}Parsed from the README we fetched on 2026-10-30; we have not executed it.
command/args come from the install command the repository states. When it is ambiguous, the project README wins.
VS Code (.vscode/mcp.json - the key is servers)
{
"servers": {
"quinnod345-ponder": {
"command": "npx",
"args": ["skills"]
}
}
}Same server, but VS Code keeps it under <code>servers</code>.
Claude Code (command line)
claude mcp add --transport stdio quinnod345-ponder -- npx skills
Claude Code does not read a config file; add the server with this command.
Key names differ by client: Clients & CLI
- Star count
- 7 ★ · Quinnod345/ponder · read from the GitHub search API · (checked 2026-11-13 20:00:50)
- Source
- read directly from its GitHub page · type: open-source project
- Harvest history
- first seen 2026-10-31 · last seen 2026-11-14 · seen 15× · listed by 3 sources
- Score
- score 303 · 7 ★ · 3 sources · repo
- Install
npx skills
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
npx skills. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: Agent 技能. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
Quinnod345/ponder；first catalogued 2026-10-31；last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.### AI that knows when to speak - and when to shut up.
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
MIT LICENSE · 0 NPM DEPENDENCIES · 101/101 CONFORMANCE · NODE >= 18 · CLAUDE CODE / CODEX / OPENCLAW
The Plot Hole in AI · How It Works · Research Paper · Studies & Benchmarks · One-Shot & Temperature Study · Install · 60s Quickstart · Full Spec
sh
# Install in 1 line (Claude Code, Codex, OpenClaw + CLI on PATH)
curl -fsSL https://raw.githubusercontent.com/Quinnod345/ponder/main/install.sh | sh
# Or via Homebrew / Claude Code Marketplace / Agent Skills CLI / Gemini CLI:
# brew install quinnod345/tap/ponder
# /plugin install ponder --marketplace Quinnod345/ponder
# npx skills add Quinnod345/ponder
# gemini extensions install https://github.com/Quinnod345/ponder
> Verified in the wild on 1M+★ of production open-source repos (studies/ecosystem-audits/): MERGED in EveryInc/compound-engineering-plugin#1919 (25.8k★) · ADOPTED in JuliusBrussee/caveman#1395 (116.1k★) · 5/6 🦞 diamond lobster on steipete/CodexBar#4830 (22.9k★) · 5/5 Greptile confidence on affaan-m/ECC#3822 (292.6k★).
## The Critical Plot Hole in AI: Forced Speech
Ponder does not claim to "solve all of AI." It solves one specific, critical plot hole in how modern AI models work: forced speech.
Every mainstream LLM is trained (via RLHF) to equate helpfulness with token generation. To a standard model, an empty response is a failure. That single training incentive creates three structural failure modes whenever you ask an AI agent to audit a codebase or plan a complex change:
### 1. When an AI doesn't know - or is asked to review a second time - it is forced to manufacture noise
If a route file is missing on disk, a standard single-shot prompt will often guess what is inside it and hallucinate findings. Worse, if you run an unstructured multi-pass loop ("Critique and improve your previous review" for 4 passes), by Pass 3 the real bugs are already listed - yet because the model does not know how to shut up, it justifies its turn by inventing speculative nitpicks (React.memo everywhere, BEM class renaming, dark-mode wrappers) while never retracting its Pass-1 false positives.
Why Ponder knows when to shut up (Epistemic Silence): Ponder separates having a perspective from mutating state. Every pass records voices (how many perspectives inspected the evidence and argued in deliberation.json) separately from deltaVoices (how many emitted a revision in deltas.jsonl). When a finding already holds, silence is the desired output. Two consecutive passes where all voices verify the evidence (voices >= 3, confidenceFloor == 0) and almost nothing moves (novelty Outcome: Actionable precision collapses to 29.0%. Real bugs get buried under performative churn (170.8 min of wasted developer time). | skeptic: "VOTE: DONE. Re-verified all open findings and file:line anchors on disk. Emitting 0 deltas." builder · dreamer · empath: "VOTE: DONE. Emitting 0 deltas." Outcome: voices: 4 · deltaVoices: 0 · churn: 0.00 · surprise: 0.00 → stop (converged). |
### 2. Agents deliver half a goal and silently forget the rest
A long sweep decays. The first ten screens get real attention, the last thirty get a sentence each, and after a context compaction the agent no longer remembers there were forty.
The Plot Hole in AI · How It Works · Research Paper · Studies & Benchmarks · One-Shot & Temperature Study · Install · 60s Quickstart · Full Spec
sh
# Install in 1 line (Claude Code, Codex, OpenClaw + CLI on PATH)
curl -fsSL https://raw.githubusercontent.com/Quinnod345/ponder/main/install.sh | sh
# Or via Homebrew / Claude Code Marketplace / Agent Skills CLI / Gemini CLI:
# brew install quinnod345/tap/ponder
# /plugin install ponder --marketplace Quinnod345/ponder
# npx skills add Quinnod345/ponder
# gemini extensions install https://github.com/Quinnod345/ponder
> Verified in the wild on 1M+★ of production open-source repos (studies/ecosystem-audits/): MERGED in EveryInc/compound-engineering-plugin#1919 (25.8k★) · ADOPTED in JuliusBrussee/caveman#1395 (116.1k★) · 5/6 🦞 diamond lobster on steipete/CodexBar#4830 (22.9k★) · 5/5 Greptile confidence on affaan-m/ECC#3822 (292.6k★).
## The Critical Plot Hole in AI: Forced Speech
Ponder does not claim to "solve all of AI." It solves one specific, critical plot hole in how modern AI models work: forced speech.
Every mainstream LLM is trained (via RLHF) to equate helpfulness with token generation. To a standard model, an empty response is a failure. That single training incentive creates three structural failure modes whenever you ask an AI agent to audit a codebase or plan a complex change:
### 1. When an AI doesn't know - or is asked to review a second time - it is forced to manufacture noise
If a route file is missing on disk, a standard single-shot prompt will often guess what is inside it and hallucinate findings. Worse, if you run an unstructured multi-pass loop ("Critique and improve your previous review" for 4 passes), by Pass 3 the real bugs are already listed - yet because the model does not know how to shut up, it justifies its turn by inventing speculative nitpicks (React.memo everywhere, BEM class renaming, dark-mode wrappers) while never retracting its Pass-1 false positives.
Why Ponder knows when to shut up (Epistemic Silence): Ponder separates having a perspective from mutating state. Every pass records voices (how many perspectives inspected the evidence and argued in deliberation.json) separately from deltaVoices (how many emitted a revision in deltas.jsonl). When a finding already holds, silence is the desired output. Two consecutive passes where all voices verify the evidence (voices >= 3, confidenceFloor == 0) and almost nothing moves (novelty Outcome: Actionable precision collapses to 29.0%. Real bugs get buried under performative churn (170.8 min of wasted developer time). | skeptic: "VOTE: DONE. Re-verified all open findings and file:line anchors on disk. Emitting 0 deltas." builder · dreamer · empath: "VOTE: DONE. Emitting 0 deltas." Outcome: voices: 4 · deltaVoices: 0 · churn: 0.00 · surprise: 0.00 → stop (converged). |
### 2. Agents deliver half a goal and silently forget the rest
A long sweep decays. The first ten screens get real attention, the last thirty get a sentence each, and after a context compaction the agent no longer remembers there were forty.
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- Source
- github · https://github.com/Quinnod345/ponder
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