deep-research

What the source does

• FilesystemDeclared1 observation
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

AGENTS.md

Audit 0.4.1 · source sha 7abfdd609a49 · 31 Oct 2026Report an issue or request a re-scan

• Publisherdaymade GitHub userOwner of the repository this skill is read from
• Source folderdaymade/claude-code-skills/deep-researchThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict7abfdd609a49A new audit runs when the source changes
• Repository statusNot archivedPushed today
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Creates reusable, source-traced research reports and coordinates provider/mode lanes with original exports. Use for 深度研究, 调研报告, literature reviews, market or company research, and ChatGPT/Kimi/UniFuncs research routes.…

---
name: deep-research
description: >-
  Creates reusable, source-traced research reports and coordinates provider/mode lanes with original
  exports. Use for 深度研究, 调研报告, literature reviews, market or company research, and
  ChatGPT/Kimi/UniFuncs research routes. Technology choice uses tech-selection; competitor code uses competitors-analysis.
---

# Deep Research

Create high-fidelity research reports with strict format control, evidence mapping, source governance, and multi-pass synthesis.

## Architecture: Lead Agent + Subagents

```
Lead Agent (coordinator — minimizes raw search context)
  |
  P0: Environment + source policy setup
  |
  P1: Question and claim map (decision questions, evidence routes, stop rules)
  |
  Dispatch ──→ Subagent A ──→ writes task-a.md ──┐
           ──→ Subagent B ──→ writes task-b.md ──┤ (parallel)
           ──→ Subagent C ──→ writes task-c.md ──┘
  |                                               |
  |     research-notes/  <────────────────────────┘
  |
  P2: Dispatch + investigate → evidence packets
  P3: Citation registry + source governance
  P4: Evidence-mapped outline with counter-evidence and unknowns
  P5: Draft from evidence packets; reopen decisive originals
  P6: Counter-review (claims, confidence, alternatives)
  P7: Verify → asset check and catalog registration
```

**Context discipline:** Keep raw search-result noise in task workspaces. Pass evidence packets to the lead agent, including locators and short source excerpts. Notes are routing aids, not authorities: the lead agent must open the original source for every load-bearing claim, conflicting claim, and exact figure/date/quotation used in the report.

## Run and asset contract — every invocation

Before external retrieval, read [research-asset-contract.md](references/research-asset-contract.md). Create or resume a durable project study **for single-route and multi-route research alike**. Search its explicit prior-study catalog, open relevant earlier originals and record reuse/adapt/reject decisions. Draft the decision questions and provider × actual-mode lanes in `study.json`. Write one exact `dispatch_context` with the user-supplied seed URL, named entities, and verified codes or other identifiers needed for the query. Include that string in **every** lane prompt; [research_assets.py](scripts/research_assets.py) `start` rejects an omission. Capture the user's named seed article or document as an original before external dispatch, and follow the [provider handoff](references/provider-run-contract.md#seed-source-handoff) when a provider cannot read its URL. A model workspace may not see the user's link or local files just because the coordinator does. Then run `provider_runs.py plan`. Keep every user-requested mode in the plan; a route that adds no value, is unavailable or lacks paid authorization gets a reasoned `deferred` event. A report assembled from direct web search and internal subagents still needs a direct-source lane and the same archive.

New studies use schema 2's [request mode contract](references/provider-run-contract.md#request-inventory-independent-of-execution): archive the original request and accepted workflow, interpret the required modes independently of the execution lanes, and map each to matching lanes. An explicit empty mode inventory is valid when none was requested; a missing contract is not. `plan` rejects an omitted or mismatched mapped route. Review the inventory against the original: fields and hashes cannot prove semantic completeness. Schema-1 archives remain readable with request coverage unknown; do not restart old tasks to fill that gap.

Before collecting provider reports, load [report-file-collection.md](references/report-file-collection.md). Use available file/download channels instead of the clipboard. Schema-2 submission and historical import require an unchanged actual-mode observation receipt; prepared prompts do not. A deferred route stays visible with its reason. An uncertain result or legacy request coverage requires explicit `--bounded-reason` at final check/registration; retain that reason without claiming full completion. Catalog search returns current registered details and recorded coverage, not a completed integrity check; follow the [research asset contract](references/research-asset-contract.md#start-before-external-retrieval).

During research, retain the unedited provider outputs, every opened original and every provider-surfaced source URL with status and provenance. Bind report claims to approved original sources; model reports only locate candidate evidence. Before calling a report complete, run `provider_runs.py validate`, `research_assets.py check`, and register the study for later discovery. An answer with citations but no study/source/claim record does not satisfy this Skill. The local scripts record and check files; they make no provider calls and do not authorize paid work.

Before sending a Work/Agent task that may choose its own data plugins, inspect the relevant plugin catalog for per-call credits or charges. A signed-in account and a request to use a data source do not set an unlimited spend ceiling. If an autonomous task can invoke metered plugins without a per-call pause and this task has no explicit spend authorization for them, defer that lane or use a route where the exact calls can be approved first. Even with a budget, a prompt is not a technical charge limit: use a controllable route when the autonomous task cannot enforce it. State authorized limits in the provider prompt for traceability, then read the raw tool log after execution; if a charge occurs despite the boundary, record the observed usage and tell the user. Do not make another paid call to fill a coverage gap.

## Mode Selection

Determine the research mode before starting:

| Dimension | Options |
|-----------|---------|
| **Topic Mode** | Enterprise Research (company/corporation) OR General Research (industry/policy/tech) |
| **Depth Mode** | Stand

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-31
   ✓SAFE B 89 / 100

   first audit · source 7abfdd609a49

Questions about deep-research

• github.com/daymade/claude-code-skills/tree/main/deep-research — the audited source at commit 7abfdd609a49 and every finding aboveObserved · 31 Oct 2026

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