| 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.
