Research General

Research General

Research a general (non-programming) topic from multiple angles using parallel sub-agents, with critical evaluation of source credibility.

Usage

research-general <question or topic>
research-general "<exact claim to verify>"
research-general what does the evidence say about screen time and adolescent sleep
research-general causes of the 2008 financial crisis
research-general nuclear vs solar economics for grid power

Gotchas

• "Recent" doesn't mean "correct". For historical, philosophical, or settled empirical topics, a 30-year-old peer-reviewed paper can outweigh a recent op-ed. Weigh authority and topic-stability before recency.
• Wikipedia is grounding, not authority — follow its citations to primary sources before stating something as fact.
• Advocacy organizations and think tanks have a stance. Cite them as evidence of what that side says, not as neutral fact.
• Affiliate-driven and SEO listicle sites ("Top 10 Best X", coupon-hosting comparison sites) are biased toward whatever pays them. Weight independent test institutions and regulators above them.
• Quick mode may miss nuance. If a "simple" question turns out contested ("Is X healthy?" — depends on dose, population, endpoint), note it and suggest re-running in Standard.

Workflow

Step 1: Check Existing Knowledge

Before spawning any agents, assess whether you can already answer well from training data:

• High confidence (well-established facts, stable domain): answer directly, note you didn't search, offer to research if the user wants verification.
• Medium confidence (good answer but maybe outdated, regionally wrong, or incomplete): proceed in Quick mode to verify and supplement.
• Low confidence (unfamiliar, rapidly changing, contested, or regulatory/regional specifics): proceed in Standard mode.

When in doubt, lean toward searching — but only if searching can plausibly improve the answer.

Step 2: Parse Input

Extract: topic, sub-questions / claims, date scope, comparison targets, region/locale (drives which sources are authoritative), personal context (career stage, budget for consumer queries), and topic stability (current / active research / established / historical — drives the recency rubric).

Step 3: Classify Query Depth

When in doubt, use Standard. Stop at diminishing returns — if three agents return the same finding, broaden don't deepen.

Step 4: Spawn Agents in Parallel

Pick the relevant agents from the table below and launch each batch together as runtime capacity allows. Each agent captures source metadata: URL, date, source type, author/publisher, and (where it applies) sample/methodology, primary-vs-secondary, and affiliate or sponsorship disclosure.

Dispatch research workers with read/search/fetch tools and no file edits. Disable delegation tools for ordinary workers where supported; read-only access alone does not prevent delegation, and available tools vary by harness. If a branch needs a coordinator, its brief must name the subtasks, bound all descendants, and define when to stop. Include those descendants in the main agent's allocation.

One focused assignment per worker. Give it a concrete question and a stopping condition. Coordinators receive an explicit decomposition; workers do the assigned research themselves.

The table is a menu. Pick the smallest useful set of complementary perspectives. Briefly state a larger decomposition, including any nesting, and queue work within the runtime concurrency limit. Additional agents do not require approval solely because of their count.

Fetching: prefer mcp__jina__read_url for JS-heavy pages; WebFetch for plain HTML, government PDFs, .gov/.int. See "Web Fetching" in CLAUDE.md. WebSearch/WebFetch are Claude Code's tool names — on another harness, use its equivalent search and fetch tools.

For full agent prompts including the Regional locale playbook (DE/FR/UK/US/AU), see references/agent-prompts.md.

Step 5: Deduplicate and Note Convergence

Wait for agents, deduplicate by URL (keep richest metadata), and note when independent agents found the same source — convergence raises authority. Watch for false convergence: three blogs citing one tweet are one source, not three.

Step 6: Critical Evaluation

Authority:

Recency (depends on topic):

Conflicts: First check if it's a real conflict or different scopes/populations/regions. Otherwise prefer higher authority, then more recent, then primary over secondary. A meta-analysis disagreeing with mainstream news usually wins on the empirical question — but news may correctly capture what people believe.

Step 7: Follow-Up Loop (Standard only)

If a topic area has fewer than 2 sources or the core question is unanswered: identify the gap, generate 1-2 delta queries (alternative terminology, narrower/broader scope, primary-source angle, local-language variant), spawn 1-2 follow-up agents (read-only, same as Step 4), merge.

Max 1 cycle. If the gap persists, mark as low confidence in the synthesis.

Reuse the allocation. Reuse a worker when practical, and keep follow-ups focused on the named gap. Include descendants and advisor calls in the same task accounting; a new round does not reset a spending limit. Stop when further sources only repeat the findings.

Step 8: Adversarial Critique (Standard only)

Brief self-challenge:

• What would a disagreer cite? Did the search find that?
• Over-weighting one source type? (all news, no academic — or vice versa)
• "Independent" sources tracing to a single origin? (3 articles citing one study = 1 source)
• Mistaking what people say is true for what is true?
• Affiliate, sponsorship, or commercial COI in any cited source?
• Assuming a specific country / culture / population? Verify regional applicability.
• Survivorship bias — only hearing from people who succeeded?
• Population/scope/endpoint mismatch between the question and the evidence?

If the critique reveals a blind spot, adjust and lower confidence.

Step 9: Present Results

Lead with the answer, not the research process. Use inline source counts ("(3 sources)", "(1 source, low confidence)") instead of a separate Confidence block.

Structure:

1. Direct answer with inline source counts
2. Key references (1-3) — sources that most shaped the conclusion
3. Supporting Details — only sections that add value beyond the answer

Available detail sections (use only those that add value): Background · Evidence · News & Reporting · Comparison · Regional details · Claim Verification · Historical Context · Conflicts · Open Questions.

For the full output template, see references/output-format.md.

Examples

Troubleshooting

Agent fails or times out — Continue with remaining agents. Note the gap in the synthesis.

No academic sources found — Try alternative terms (medical/scientific terminology often differs from lay language). If still nothing, note the empirical evidence base is thin.

Sources disagree along ideological lines — Separate the empirical claim from the value judgment. Find the underlying primary source. Present what each side argues, then what primary evidence supports — and note where disagreement is genuinely values-based.

Topic is current and unsettled — Flag explicitly ("active situation as of {date}; details may shift"). Prefer wire services (Reuters, AP) over editorial outlets.

All consumer sources are affiliate-driven — Search for independent test institutions for the locale (Stiftung Warentest, Consumer Reports, Which?, Choice). If none, note that available sources are commercial.