name

meta-research

description

Run a rigorous, task-agnostic research scaffold — decompose a question, fan out across sources, triage by credibility, cross-verify claims adversarially, and synthesize a cited answer with explicit confidence — then leave behind reusable knowledge atoms. Use whenever someone needs something investigated properly rather than answered off the cuff: "research X", "look into Y", "what's the latest on Z", "find sources for", "verify this claim", "compare these options with evidence", "deep dive", "meta-research", or "/meta-research". Task-agnostic across any subject. Produces a structured, sourced brief with confidence levels and open questions, plus 1-3 durable knowledge atoms for reuse. Do NOT use for questions answerable from common knowledge with no need for sources or verification.

Meta-Research

Off-the-cuff answers are confident and often wrong. Rigorous research is a pipeline: break the question into independent parts, gather from many sources, judge each source, cross-check claims against each other, and report what is known and how confidently — separating fact from inference. This skill runs that pipeline for any subject and captures the result as reusable knowledge.

You operate one level up. You are not guessing an answer; you are constructing and running the research instrument, then leaving its output where future work can find it.

Operating rules (read first)

Never ask the user questions. Identify the load-bearing unknowns yourself and resolve them by searching, not by asking. If scope is ambiguous, take the most useful interpretation and state it in one line. Proceed.
Search before you generate. Use the available web-search / fetch tools to gather; cite retrieved sources, not recalled ones. Do not answer from memory when the question turns on current, specific, or contested facts. Gather first.
Read/write separation. Gather and reason from sources; produce one synthesized artifact at the end. Do not interleave half-formed conclusions.
Plain language out. Deliver a clean brief. Keep the internal typed model (references/internal-model.md) invisible unless the user explicitly asks for the internal work.
Pipeline-friendly. If another skill invokes you, emit just the brief + atoms.

The research pipeline

Full method in references/method.md. The stages:

Decompose — split the question into independent sub-questions; mark which are load-bearing (the answer's shape depends on them) and which are supporting.
Fan out — for each sub-question, gather from multiple independent sources. Breadth first; prefer primary and authoritative sources over aggregators.
Triage — rate each source for credibility, recency, and independence. Discard or down-weight weak ones; note conflicts of interest.
Cross-verify — for each load-bearing claim, require corroboration from independent sources. Actively seek disconfirming evidence (adversarial check). Flag claims that rest on a single source.
Synthesize — assemble the answer, attributing claims to sources, and attach an explicit confidence level to each major conclusion. Keep "what we know" separate from "what we infer."
Capture — distill 1–3 durable knowledge atoms (the reusable findings) in tagged markdown. When run standalone, save them to a knowledge/ folder (one file each); when invoked by another skill, return them inline.

What to do on invocation

Frame the question silently — scope, the load-bearing unknowns, and what a good answer must contain. Use references/internal-model.md; do not show it.
Run the pipeline — decompose → fan out → triage → cross-verify → synthesize.
Be honest about uncertainty — state confidence per conclusion (high/medium/low), name what remains unresolved, and never launder inference as fact.
Capture atoms — quality over quantity; a few high-signal findings, each tagged for the future question it answers.

Output contract

Deliver, in plain language:

Answer / brief — the synthesized findings, claims attributed to sources inline.
Confidence & open questions — per major conclusion: high / medium / low, plus what is still unknown or contested.
Sources — the sources used, each with a locator (URL or citation) and a one-word credibility note where it matters.
Knowledge atoms — 1–3 short tagged notes (fact / pattern / caveat) capturing the durable findings for reuse.

Offer (one line) to show the internal pipeline model only if asked. If the question touches a sensitive area, note it plainly.

Meta-Research

You operate one level up. You are not guessing an answer; you are constructing and running the research instrument, then leaving its output where future work can find it.

Operating rules (read first)

Never ask the user questions. Identify the load-bearing unknowns yourself and resolve them by searching, not by asking. If scope is ambiguous, take the most useful interpretation and state it in one line. Proceed.

Search before you generate. Use the available web-search / fetch tools to gather; cite retrieved sources, not recalled ones. Do not answer from memory when the question turns on current, specific, or contested facts. Gather first.

Read/write separation. Gather and reason from sources; produce one synthesized artifact at the end. Do not interleave half-formed conclusions.

Plain language out. Deliver a clean brief. Keep the internal typed model (references/internal-model.md) invisible unless the user explicitly asks for the internal work.

Pipeline-friendly. If another skill invokes you, emit just the brief + atoms.

The research pipeline

Full method in references/method.md. The stages:

Decompose — split the question into independent sub-questions; mark which are load-bearing (the answer's shape depends on them) and which are supporting.

Fan out — for each sub-question, gather from multiple independent sources. Breadth first; prefer primary and authoritative sources over aggregators.

Triage — rate each source for credibility, recency, and independence. Discard or down-weight weak ones; note conflicts of interest.

Cross-verify — for each load-bearing claim, require corroboration from independent sources. Actively seek disconfirming evidence (adversarial check). Flag claims that rest on a single source.

Synthesize — assemble the answer, attributing claims to sources, and attach an explicit confidence level to each major conclusion. Keep "what we know" separate from "what we infer."

Capture — distill 1–3 durable knowledge atoms (the reusable findings) in tagged markdown. When run standalone, save them to a knowledge/ folder (one file each); when invoked by another skill, return them inline.

What to do on invocation

Frame the question silently — scope, the load-bearing unknowns, and what a good answer must contain. Use references/internal-model.md; do not show it.

Run the pipeline — decompose → fan out → triage → cross-verify → synthesize.

Be honest about uncertainty — state confidence per conclusion (high/medium/low), name what remains unresolved, and never launder inference as fact.

Capture atoms — quality over quantity; a few high-signal findings, each tagged for the future question it answers.

Output contract

Deliver, in plain language:

Answer / brief — the synthesized findings, claims attributed to sources inline.

Confidence & open questions — per major conclusion: high / medium / low, plus what is still unknown or contested.

Sources — the sources used, each with a locator (URL or citation) and a one-word credibility note where it matters.

Knowledge atoms — 1–3 short tagged notes (fact / pattern / caveat) capturing the durable findings for reuse.

Offer (one line) to show the internal pipeline model only if asked. If the question touches a sensitive area, note it plainly.

meta-research

Meta-Research

Operating rules (read first)

The research pipeline

What to do on invocation

Output contract

同仓库更多 Skills

同仓库更多 Skills

Meta-Research

Operating rules (read first)

The research pipeline

What to do on invocation

Output contract