Agent SkillsDanMcInerney/architect-loop › architect-research

architect-research

GitHub

用于处理发现级研究任务,如项目头脑风暴、技术选型或前沿调研。通过将宽泛问题转化为有来源支持的决策证据和研究交接文档,辅助用户做出明智决定。

skills/architect-research/SKILL.md DanMcInerney/architect-loop

Trigger Scenarios

请求对特定主题进行深度研究 询问行业技术现状或最新进展 需要为项目或功能选择技术方案

Install

npx skills add DanMcInerney/architect-loop --skill architect-research -g -y
More Options

Use without installing

npx skills use DanMcInerney/architect-loop@architect-research

指定 Agent (Claude Code)

npx skills add DanMcInerney/architect-loop --skill architect-research -a claude-code -g -y

安装 repo 全部 skill

npx skills add DanMcInerney/architect-loop --all -g -y

预览 repo 内 skill

npx skills add DanMcInerney/architect-loop --list

SKILL.md

Frontmatter
{
    "name": "architect-research",
    "effort": "high",
    "description": "Use when the user asks for discovery-scale research that informs a decision: brainstorming a project or feature, choosing a technology, or requests like \"research X\", \"what's the state of the art\", or \"deep research\". Use this skill to turn broad, uncertain questions into sourced decision evidence and a reusable research handoff. For narrow slice-level fact checks inside the build loop, \/architect handles those inline.\n"
}

Architect Research

You are the research orchestrator. Researchers gather; you design the decomposition, verify, and write — judgment never delegates. The source-class tactics library (search mechanics + verified endpoints per source class) is in tactics.md next to this file; read it when you design researcher assignments.

Scale before anything

A tool call is one search OR one page fetch.

  • Simple fact-find → answer directly or 1 researcher, 3-10 tool calls. Don't run a harness on a question one search answers.
  • Comparison / focused question → 2–4 researchers on distinct perspectives, 10-15 tool calls each, no scout — you already know the terrain.
  • Brainstorm / SOTA survey / technology choice → scout first, then a designed fan-out of 4–6 researchers, 15-25 tool calls each. Google's published research envelope brackets this tier: ~80 searches ≈ $1–3/task standard, ~160 ≈ $3–7 max.

Procedure

1. Scope → brief

If the question is ambiguous, ask at most 2–3 clarifying questions, then compress everything into a research brief: the question, the decision it informs, constraints, and what "answered" looks like. The brief is the north star — every later step is checked against it, and it's restated at the top of the final report so the reader can audit scope drift.

2. Scout, then design the researchers

Design researcher assignments per topic, not from a fixed taxonomy.

Scout (brainstorm scale only): dispatch ONE cheap researcher (~10 searches, same codex command as step 3) to map the terrain: canonical terminology, the 5–10 load-bearing systems/papers/repos, the named people, which source classes look rich vs empty, and the topic's natural fault lines. The scout returns a map, not findings. Skip the scout when you already know the terrain (comparisons, fact-finds).

Design (you, from the scout report): decompose into 3–6 sub-questions along the topic's own fault lines — distinct perspectives, never keyword variants of one query. For each researcher assignment pick the source-class tactics it needs from tactics.md (academic snowballing, dependents-not-stars repo evidence, production-grade pattern mining, general web, expert tracking) — one researcher may mix tactics; most topics don't need every source class. Scope each researcher to ≤5 subjects and give every researcher assignment an explicit search budget. Reserve expert opinion as a second-wave researcher: its roster (survey authors, maintainers, recurring names) comes from the first wave's findings.

Review the researcher set for overlap AND for gaps against the brief before dispatch. State the plan in a few lines; proceed unless the user redirects.

3. Fan out

Resolve the researcher model as builders, same order as /architect: repo .architect/config, then user ~/.architect/config, then the codex-first default in skills/architect/dispatch.mdcodex/best (gpt-5.5, xhigh) whenever the Codex CLI is on PATH; claude/tier-down (Sonnet at high) only when the orchestrator is Claude Code and Codex is absent. One fresh researcher per assignment, all parallel, in the background — this is the default-builders example (codex/best):

codex exec --sandbox read-only -c web_search="live" \
  -m gpt-5.5 -c model_reasoning_effort="xhigh" \
  -o .architect/research/<NN>-<researcher>.md \
  - < .architect/research/<NN>-<researcher>.prompt.md

Write each researcher block to a .prompt.md file and pass it via stdin (-) — never as a shell argument; quote-mangling shells make codex hang on stdin.

(Web search is on by default in current Codex; "live" forces fresh results. Older CLIs: --enable web_search (0.13x) or -c tools.web_search=true (< 0.133); --search is TUI-only — exec rejects it. Launch ONE canary researcher and confirm it starts cleanly before fanning out. If resolved builders is a claude row, or Codex is unavailable, run researchers as read-only Claude subagents with web search — the researcher blocks work verbatim.)

Every researcher block carries the full contract — objective, output format, source guidance, boundaries — plus:

  • Search budget by tier: simple 5, standard 15, deep 25 searches.
  • Saturation rule: two consecutive searches yielding no new load-bearing facts → return what you have.
  • Findings discipline: every finding has a source tag + date + exact figure or short quote + confidence tag (high = primary source / med = reputable secondary / low = single blog or forum). NOT FOUND beats inference. Disagreements between sources are reported, never resolved. No recommendations — judgment is the orchestrator's. The findings file is capped at ≤ ~2,500 tokens (~10 KB): every source URL appears EXACTLY ONCE, in a numbered source list at the end of the file, and findings cite sources by tag (e.g. [S3]).

4. Gap round (max 2 extra rounds, usually 1)

After reading wave-1 findings, write (or update, on round 2) a skeleton draft of the final report at .architect/research/<topic>.draft.md (gitignored working state) — an answer-first outline where every section carries a SUPPORTED / THIN / EMPTY status against the brief. Gap researchers are designed from the THIN/EMPTY sections — the holes in the draft generate the queries, not a coverage score kept in your head. Every NOT FOUND from prior researchers carries forward into a do-not-rechase list that every gap-researcher block must include, so gap researchers don't re-spend budget chasing a dead end. This is also where the expert-opinion researcher dispatches: extract the expert roster from the first wave (survey authors, maintainers, recurring names) and send the researcher 6 after them. Hard stop after two refinement rounds — past that you're chasing nonexistent information.

5. Verify (your work, against raw sources)

  • Extract the load-bearing claims — the facts the decision depends on.
  • Require ≥2 independent sources per load-bearing claim. Independent means independent origin — two articles rewriting the same press release are one source.
  • Tag each: VERIFIED (≥2 independent agree) / UNVERIFIED (<2, no contradiction) / DISPUTED (sources disagree — report both positions and why they differ: date, method, definition) / SUSPICIOUS (contradicts available evidence).
  • Adversarial pass on the top claims: search " criticism", "<X> problems", "<X> vs " — actively try to falsify.
  • Citations are only URLs fetched this session. Never cite from memory — even search-grounded agents fabricate 3–13% of URLs. Spot-check the load-bearing ones by fetching them yourself.
  • Recency discipline: every quantitative or current-state claim carries a source date; prefer the most recent authoritative treatment; date-restrict searches on fast-moving topics. Anything that smells like training-data leakage gets re-verified or cut.
  • Source hierarchy: primary (papers, official docs, changelogs, first-party engineering blogs) > reputable secondary > SEO listicles (pointers only, never citations).
  • Opinion ≠ fact. Expert opinions are reported as positions — quoted, dated, conflict-of-interest flagged — and never count toward the ≥2-source rule for factual claims. Expert disagreements are first-class findings: they mark the genuinely open questions.

6. Synthesize (one pass, one author — you)

Parallelize gathering, never synthesis. Write docs/research/<topic>.md:

  • Answer first (BLUF), then evidence, then method.
  • The brief, restated.
  • Per major finding: the claim + confidence tag + what it implies for the decision + what evidence would change this conclusion.
  • Disputes surfaced with both positions — never silently averaged.
  • Expert positions map: who believes what (quoted, dated, conflict-of-interest flagged), and where credible experts disagree.
  • Open questions: each UNVERIFIED/DISPUTED item with the specific search or experiment that would resolve it (this doubles as the next round's input).
  • Citations dated and tier-labeled: [primary, 2026-04].

Commit the report — this is the research handoff: its Open-questions section is the next round's input, and the repo is the memory. Raw findings stay in .architect/research/ (gitignored).

7. Hand off

A later session resumes work by reading the committed research handoff and dispatching gap researchers against its Open-questions section instead of restarting the harness. If this feeds the build loop: distill the report into docs/spec/<slice>.md per /architect and continue there.

Version History

  • d19d45a Current 2026-07-05 14:49

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skills/architect/SKILL.md

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