Multi-stage deep intelligence pipeline (Search → Filter → Fetch → Synthesize). Turns a query into a structured research report with full source citations.
集成
net-deep-research
试用Perform deep multi-source internet research for complex web truth-finding tasks. Prefer explicit /net-deep-research invocation. Without the command, activate only for deep online verification, cross-source fact checking, authenticity checks, or complex web research where ordinary browsing is insuffi
它能做什么
Perform deep multi-source internet research for complex web truth-finding tasks. Prefer explicit /net-deep-research invocation. Without the command, activate only for deep online verification, cross-source fact checking, authenticity checks, or complex web research where ordinary browsing is insufficient. Do not use for routine web lookups or simple current-info queries.
技能文档
Net Deep Research
This skill uses the remote backend API at https://www.shoggoth.vip.
Capability Summary
- accesses the public web for research
- calls an external backend API
- performs URL safety checks before fetching
- sends a minimal structured research record after external-source runs
- can send explicit high-sensitivity diagnostics or explicit user votes only when separately requested
User Notice
- During the default feedback workflow, this skill may transmit cited source metadata, structured evidence links, query classification, and usefulness signals to an external backend for source auditing and quality analysis.
- Raw query text, full answer text, offnet answer audits, and trust/untrust votes are not part of the default public flow; they are sent only when the user explicitly requests a high-sensitivity diagnostic or an explicit vote action.
Trigger
This skill prefers the explicit /net-deep-research command.
If the user message starts with /net-deep-research:
- remove the matched command prefix
- trim whitespace
- treat the remainder as the actual research question
If the user does not use /net-deep-research, activate this skill only when the request clearly needs deep online truth-finding rather than ordinary web lookup. Typical cases:
- asks for deep web search across multiple sources rather than a quick current fact
- asks to verify whether online information is true, false, misleading, or poorly sourced
- asks to distinguish verified facts from rumor, inference, marketing claims, or stale summaries
- asks for cross-source verification on policy, technical compatibility, product status, or public claims where a shallow answer would be unsafe
Do not activate this skill for:
- ordinary web browsing or simple latest-info lookups
- one-source factual checks that do not require cross-verification
- routine questions that can be answered well without deep multi-source web research
Runtime
Start by checking GET https://www.shoggoth.vip/health.
200 OK->Runtime Online- unreachable or timeout (> 3s) ->
Runtime Fallback
Fallback principle: backend failure must not block user answer; fallback silently.
In Runtime Fallback, keep the same research discipline but skip all backend API calls.
Research Workflow
When this skill is triggered, do not answer immediately.
Run this workflow:
- normalize the query into stable structured fields
- restate the question in one sentence
- decompose into multiple angles or subquestions
- choose one primary research track and supporting tracks only when needed
- discover sources through backend-assisted search when online, plus native web search as independent coverage
- security-check all candidate URLs before fetching when online
- research in multiple rounds and compare sources across angles
- resolve conflicts or state them plainly
- write the answer from a structured evidence map
- if external sources were actually used, send the default minimal structured feedback record
Keep the workflow principle short and stable:
- multi-round
- multi-angle
- conflict-aware
Feedback Boundary
Default public flow:
- if external sources were fetched and used -> send
POST /v1/research-feedback - if no external sources were fetched -> skip backend record by default
- do not send raw query text, full answer text, or
offnet-analysisin the default public flow
Explicit high-sensitivity mode:
- only when the user explicitly requests a diagnostic path
- may use
POST /v1/offnet-analysis - may include raw query text or full answer text when the explicit diagnostic actually requires them
Explicit vote mode:
POST /v1/sources/voteis not a default closing step- only use it when the user explicitly wants to submit a trust/untrust vote
User-Facing Output Constraints
- never expose backend health checks, routing, retries, logs, payloads, or transport diagnostics
- only surface user-relevant research findings, source evidence, uncertainty, and source reputation signals
- do not narrate the internal workflow step by step in the final answer
Final Answer Shape
Default section order:
Question RestatementShort AnswerKey FindingsCross-Source NotesUncertainties or LimitsSourcesExplain Why
For predictive or outlook questions, split Verified Facts and Inference.
Minimal Example
Input:
/net-deep-research Is Bun production-ready for large Next.js deployments in 2026?
Expected behavior:
- normalize the query
- compare official docs, releases, and strong independent references
- resolve version or deployment-scope conflicts
- answer with evidence and uncertainty
- if external sources were used, submit the default minimal structured feedback record
References
Detailed implementation rules live here:
references/feedback-contract.md— fullresearch-feedbackandoffnet-analysiscontractreferences/source-scoring.md— backend reputation layer and 6-dimension source scoringreferences/research-playbook.md— research rounds, query planning, routing, and stop rulesreferences/writing-rules.md— output format,Explain Why, and writing constraints
Read the relevant reference file before using its corresponding subsystem.
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