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Dispatches two sub-agents in parallel to gather external and local context for the current task.
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SOC 職業分類に基づく
| name | research |
| description | Dispatches two sub-agents in parallel to gather external and local context for the current task. |
| context | load |
/contract
Dispatch two sub-agents in parallel using the Agent tool. Prefer subagent_type: "research-agent"; fall back to subagent_type: "Explore" with thoroughness "very thorough" if the research-agent is not available. One researches the web for external context relevant to the current task. The other inspects the local working directory for domain-relevant artifacts. Return a concise merged research brief highlighting relevant findings, conflicts, risks, and implications for the task.
Web research agent — always the same: search for external context, prior art, patterns, APIs, and comparable approaches relevant to the task. Domain-agnostic.
Local inspection agent — adapt to the domain:
| Domain | What to inspect |
|---|---|
software | Code, config files, package manifests, CI configs, test suites, git history, README/docs, existing patterns and conventions |
research | Papers (PDF/LaTeX), notes, data files, citation databases (.bib), lab notebooks, analysis scripts, prior drafts |
design | Design files (Figma exports, SVGs, mockups), brand guidelines, component libraries, user research docs, style guides |
business | Financial models, strategy docs, market research, pitch decks, competitive analyses, KPI dashboards, stakeholder maps |
| (other) | Scan the working directory for any files relevant to the stated domain — documents, data, config, scripts — and describe what you find |
When domain is unspecified, infer it: git repo → software; PDFs/LaTeX/.bib → research; design assets → design; spreadsheets/decks → business. If ambiguous, inspect broadly and note what you found.
Both agents must end their response with a coverage assessment:
When merging results, surface coverage gaps prominently. If both agents report low coverage, flag: "Low epistemic coverage — findings may be incomplete. Consider consulting domain practitioners or providing access to private sources."
Orchestrates safe, large-scale structural changes across a codebase — symbol renames, API migrations, pattern standardizations, layer restructurings. Enumerates all affected sites, groups them into dependency layers via the DAG executor, applies changes in parallel per layer with worktree isolation, and verifies behavioral preservation at each layer boundary before proceeding. Exits immediately on first regression, surfacing the exact site, diff, and behavioral delta before any commit.
Parallel root-cause analysis for bugs and failing tests. Use when a test fails, a bug is reported, or behavior is unexplained — dispatches sub-agents to form and validate hypotheses in isolated worktrees.
Set up a scheduled headless afk run that pushes a summary to Telegram. Use when the user wants to automate a recurring task via the afk daemon scheduler (cron) with push-notified results.
Dispatch a parallel adversarial verifier wave after any high-stakes sub-agent investigation (code reviews, audits, findings reports, large refactors) — or whenever a sub-agent asserts a claim with high-confidence language (confident, certain, clearly, ≥80%), since confidence is a trigger, not a verdict. Shadow verifiers independently re-derive 2–3 key claims from scratch using tool calls only, returning CONFIRMED/REFUTED/UNVERIFIABLE, and flag disagreements before the user acts. Use when sub-agent output will drive decisions, file changes, commits, or external side-effects.
Discovers incidental complexity, duplication, and dead code in a codebase and produces a ranked, behavior-preserving reduction plan — optionally applying safe changes. Dispatches four parallel read-only discovery lenses (clone detection, dead code, complexity hotspots, wrong abstraction), synthesizes into a prioritized reduction plan, and gates apply mode behind /refactor and a hard test check.
Dispatches parallel dimension agents across a diff, PR (URL or number), commit SHA, branch, staged changes, or patch file — covering security, correctness, api-compat, test-coverage, and perf-observability — synthesizes findings by severity, and emits a merge recommendation. Use when changes are ready for review before merge. Read-only: this skill analyzes and reports only — it never edits files, commits, pushes, comments on a PR, or modifies the PR description.
