Deep Research Agent Team
Imbad0202/academic-research-skills
Runs a 13-agent pipeline for rigorous academic research, from forming the question through systematic search, synthesis, bias checks and an APA 7.0 report.
A skill your agent uses 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…
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install DanMcInerney/architect-loop architect-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/architect-research .claude/skills/architect-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .claude/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install DanMcInerney/architect-loop architect-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/architect-research .agents/skills/architect-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .agents/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install DanMcInerney/architect-loop architect-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/architect-research .cursor/skills/architect-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .cursor/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/DanMcInerney/architect-loop.git --path skills/architect-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install DanMcInerney/architect-loop architect-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/architect-research .gemini/skills/architect-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .gemini/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install DanMcInerney/architect-loop architect-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/architect-research .github/skills/architect-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .github/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add DanMcInerney/architect-loop --skill architect-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install DanMcInerney/architect-loop architect-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DanMcInerney/architect-loop.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/architect-research .opencode/skills/architect-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "architect-research" agent skill from https://github.com/DanMcInerney/architect-loop/tree/main/skills/architect-research into .opencode/skills/architect-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "architect-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
architect-researchA skill your agent uses 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…
Architect Research is an agent skill from DanMcInerney/architect-loop. 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.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `tactics.md`).
It sits in Research & Science, covering Brainstorming, Deep research and Literature review. The repository describes itself as: Super optimized /goal loop. Massive token savings and higher quality. Smart model designs and reviews, cheaper model builds.. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 28dca7d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
codexFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Architect Research loads about 2.3k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 1,158 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from DanMcInerney/architect-loop at commit 28dca7d, republished under its MIT licence (© DanMcInerney). 1,158 words, ~2,297 tokens.
.claude/skills/architect-research/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.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.
A tool call is one search OR one page fetch.
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.
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 3–10 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.
Resolve the researcher model as builders, same order as /architect: repo
.architect/config, then user ~/.architect/config, then the
config-resolved default in skills/architect/dispatch.md — codex/best
(gpt-5.5 at xhigh) via the codex CLI; the Claude-native rows
(builders = claude/...) are the config-selected alternative. One fresh
researcher per assignment, up to 10 in parallel for CLI launches — this is the
default codex/best form:
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.mdWrite 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, respecting the built-in harness cap (currently 5) —
the researcher blocks work verbatim.)
Every researcher block carries the full contract — objective, output format, source guidance, boundaries — plus:
[S3]).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 a
targeted researcher after them. Hard stop after two refinement rounds —
past that you're chasing nonexistent information.
<claim> criticism",
"<X> problems", "<X> vs <alternative>" — actively try to falsify.Parallelize gathering, never synthesis. Write docs/research/<topic>.md:
[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).
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.
© DanMcInerney, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/architect-research of DanMcInerney/architect-loop.
Open the folder on GitHubat commit 28dca7d
Architect Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Architect Research this skillDanMcInerney/architect-loop | 626 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Deep Research Agent TeamImbad0202/academic-research-skills | 51k | — | ~13k | Automated safety check: Pass | Custom licence | |
| Deep Researchbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~8k | Automated safety check: Pass | Custom licence | |
| Lead Researchtamdogood/builder-essential-skills | 220 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Deep Research WorkflowTokenRhythm/opensquilla | 7.1k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Deep Researchsanjay3290/ai-skills | 431 | 9 repos | ~683 | Automated safety check: Notes | Apache-2.0 |
Imbad0202/academic-research-skills
Runs a 13-agent pipeline for rigorous academic research, from forming the question through systematic search, synthesis, bias checks and an APA 7.0 report.
brycewang-stanford/Auto-Empirical-Research-Skills
Universal deep research agent team. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.
tamdogood/builder-essential-skills
Provider-neutral deep-research orchestration for brainstorming, technology choices, comparisons, and state-of-the-art surveys.
TokenRhythm/opensquilla
Runs multi-round research in three stages with a persisted state file, evidence tracking and a long-form report with per-claim citations.
sanjay3290/ai-skills
Execute autonomous multi-step research using Google Gemini Deep Research Agent.
Imbad0202/academic-research-skills
Orchestrates a ten-stage academic workflow from research to finished manuscript, including integrity checks, two rounds of peer review and revision.
DanMcInerney/architect-loop
A skill your agent uses when the architect factory orchestrator dispatches a fresh strategist subagent to harden a draft spec: falsify it with file:line evidence, fold the surviving findings into a…
DanMcInerney/architect-loop
A skill your agent uses when the user asks to architect, run or continue the autonomous software factory, turn a goal into a hardened tracker issue plan, dispatch builder jobs, grade finished work…
DanMcInerney/architect-loop
A skill your agent uses when the user asks to architect-fast a change, run the light factory lane, or factory-build a small goal — a few files, roughly one sitting, at most ~3 parallel issues — into…
DanMcInerney/architect-loop
A skill your agent uses for the closing whole-run review in the architect factory — the only model review in the loop: dispatched by the orchestrator, at finish, to one fresh strategist subagent…
DanMcInerney/architect-loop
A skill your agent uses when the strategist drafts per-issue graded checks after decomposition and before builder dispatch.
DanMcInerney/architect-loop
Test-driven development for factory builders. An agent skill from DanMcInerney/architect-loop.
Categories
A skill your agent uses 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…. Architect Research is an agent skill from DanMcInerney/architect-loop. 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".
Architect Research fits situations like: the user asks for discovery-scale research that informs a decision: brainstorming a project; choosing a technology; requests like research X; whats the state of the art.
Run `npx skills add DanMcInerney/architect-loop --skill architect-research -a claude-code`. Or copy the skill folder (skills/architect-research in DanMcInerney/architect-loop) into .claude/skills/architect-research in your project. Claude Code loads it when a task matches its description.
Run `npx skills add DanMcInerney/architect-loop --skill architect-research -a codex`. Or copy the skill folder (skills/architect-research in DanMcInerney/architect-loop) into .agents/skills/architect-research in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DanMcInerney/architect-loop --skill architect-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/architect-research, .gemini/skills/architect-research, .github/skills/architect-research and .opencode/skills/architect-research in your project.
Going by SKILL.md and its folder, Architect Research needs the command-line tools its instructions call (codex).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Architect Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Architect Research: Deep Research Agent Team (Imbad0202/academic-research-skills, 51k stars), Deep Research (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars), Lead Research (tamdogood/builder-essential-skills, 220 stars) and Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
DanMcInerney (a GitHub user) maintains it in DanMcInerney/architect-loop, which has 626 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on September 13, 2026.
Source: DanMcInerney/architect-loop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.