Perplexity Web Search
davila7/claude-code-templates
Runs web-grounded searches through Perplexity's Sonar models over OpenRouter for current events, recent literature and cited facts beyond the model's training cutoff.
Plan and execute multi-step research, surveys, feasibility studies, and evidence-heavy analyses with adaptive planning, source verification, critic review, and cross-task learning.
$ npx skills add microsoft/ArgusAgent --skill research-workflow -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/ArgusAgent research-workflow --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/microsoft/ArgusAgent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/contrib/pi-research-workflow-skill .claude/skills/research-workflow && 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 "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .claude/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skillType 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 microsoft/ArgusAgent --skill research-workflow -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/ArgusAgent research-workflow --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ArgusAgent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/contrib/pi-research-workflow-skill .agents/skills/research-workflow && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .agents/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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 microsoft/ArgusAgent --skill research-workflow -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/ArgusAgent research-workflow --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ArgusAgent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/contrib/pi-research-workflow-skill .cursor/skills/research-workflow && 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 "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .cursor/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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/microsoft/ArgusAgent.git --path contrib/pi-research-workflow-skill--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 microsoft/ArgusAgent --skill research-workflow -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/ArgusAgent research-workflow --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ArgusAgent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/contrib/pi-research-workflow-skill .gemini/skills/research-workflow && 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 "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .gemini/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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 microsoft/ArgusAgent research-workflowInstalls 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 microsoft/ArgusAgent --skill research-workflow -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/ArgusAgent.git skills-src && mkdir -p .github/skills && cp -r skills-src/contrib/pi-research-workflow-skill .github/skills/research-workflow && 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 "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .github/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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 microsoft/ArgusAgent --skill research-workflow -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/ArgusAgent research-workflow --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ArgusAgent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/contrib/pi-research-workflow-skill .opencode/skills/research-workflow && 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 "research-workflow" agent skill from https://github.com/microsoft/ArgusAgent/tree/main/contrib/pi-research-workflow-skill into .opencode/skills/research-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-workflow", 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.
research-workflowPlan and execute multi-step research, surveys, feasibility studies, and evidence-heavy analyses with adaptive planning, source verification, critic review, and cross-task learning.
Research Workflow is an agent skill from microsoft/ArgusAgent, published by the product's own GitHub organization. Plan and execute multi-step research, surveys, feasibility studies, and evidence-heavy analyses with adaptive planning, source verification, critic review, and cross-task learning. Use when a request needs multiple dependent investigations or a durable evidence trail; do not use for simple factual questions or small one-step edits.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `README.md`).
It sits in Research & Science, covering Fact-checking and source verification. The repository describes itself as: A persistent, reviewed multi-agent runtime for long-horizon research and engineering. The licence is MIT.
9 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 746f76b. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From 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.
Research Workflow loads about 2.7k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 1,262 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 microsoft/ArgusAgent at commit 746f76b, republished under its MIT licence (© microsoft). 1,262 words, ~2,706 tokens.
.claude/skills/research-workflow/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Run an evidence-driven research workflow inside the current agent. Plan only as much as the objective requires, gather real evidence, produce inspectable artifacts, review material claims, and carry forward only durable learning.
Use this workflow when the request has at least one of these properties:
For a simple question or one-step edit, answer or execute directly. Do not create a multi-role ceremony.
Before planning, inspect the current workspace and any existing deliverable or workflow state. Determine:
Ask the user only when an unresolved ambiguity would materially change the work or requires authorization. Otherwise state the assumption and proceed.
For work likely to span several tasks or sessions, use the following project-local state directory unless the user or repository specifies another location:
.research-workflow/
├── STATE.md # objective, task graph, status, current next action
├── EVIDENCE.md # claim-level source and measurement registry
├── DECISIONS.md # consequential choices and rejected alternatives
├── LEARNINGS.md # durable cross-task knowledge with applicability limits
└── reviews/ # material critic verdicts onlyDo not create these files for a small task. Before writing, inspect existing files and preserve unrelated content. Do not put secrets, credentials, private source text, or large raw outputs in workflow state.
STATE.md minimum schema# Research Workflow State
## Objective
<current user objective>
## Completion criteria
- [ ] <criterion and decisive evidence>
## Constraints and non-goals
- <constraint>
## Task graph
| ID | Question / action | Depends on | Required artifact or evidence | Status |
|---|---|---|---|---|
| T1 | ... | — | ... | pending |
## Current focus
- Task: T1
- Open uncertainty: ...
- Next action: ...EVIDENCE.md minimum schemaRecord only evidence used for a decision or material claim.
| ID | Claim tested | Source / command / path | Version or date | Result | Limits |
|---|---|---|---|---|---|
| E1 | ... | URL, file path, or exact command | ... | supports / contradicts / mixed | ... |For experiments, include the benchmark or dataset version, environment, relevant configuration, seed policy, metric, baseline, and raw-result path. For literature, include the real title, URL or identifier, publication/version date, and which claim the source supports. Distinguish direct observation from inference.
Create tasks with explicit dependencies. Each task must have:
Do not create separate tasks merely to imitate the role names. Prefer one coherent implementation task over planning, coding, and verification paperwork that could be performed together. Reorder or replace tasks when new evidence changes their value.
Before acting, read relevant project files, prior evidence, and durable learnings. Search externally only when external information can change the decision.
When using external sources:
If web search or a required database is unavailable, continue with available local or user-provided evidence when that can answer the question, and disclose the coverage gap. Do not invent an “external enrichment” round.
Implement, calculate, inspect, measure, or write the requested deliverable. Prefer first-hand evidence over commentary about what could be done.
Update durable state at meaningful checkpoints, not after every trivial action.
Review the artifact from a fresh acceptance perspective. Re-open the objective, completion criteria, relevant files, and decisive evidence. Do not rely only on the Executor's summary.
Use this verdict format:
VERDICT: ACCEPT | REVISE | REPLAN | BLOCKED
MATERIAL_FINDINGS:
- <criterion, defect or uncertainty, and evidence reference>
NEXT_ACTION:
- <smallest action or decisive check that can resolve the finding>
CLAIM_LIMITS:
- <what the current evidence does not establish>Verdict rules:
If an isolated subagent or context is available and proportionate to the stakes, it may perform the critic pass. Record that fact. Otherwise do not call the review independent.
A revision must resolve a named material finding and produce new evidence. Stop the loop when the artifact is accepted, a replan is needed, or a real blocker remains.
After two attempts that add no decision-relevant information, do not continue the same tactic. Diagnose the bottleneck and choose one of:
Round count is a budget ceiling, never a quality target. Do not force every task through R1/R2/R3 or require a fixed number of challenges or citations.
After a task reaches a terminal verdict, ask:
If nothing durable changed, make no learning entry. Otherwise append a bounded entry
to LEARNINGS.md:
## L<N>: <specific learning>
- Evidence: E2, E5
- Applies to: <tasks/conditions>
- Does not establish: <boundary>
- Plan impact: <changed task, criterion, dependency, or “none”>Then update STATE.md before starting the next task. This is the cross-task replan
gate: evidence may adjust, split, merge, add, remove, or reprioritize remaining
work. Preserve the original user objective unless the user explicitly changes it.
Build the requested final deliverable from accepted artifacts and registered evidence, not from role transcripts. The synthesis must:
Before declaring completion, verify:
Return the deliverable and a concise account of the strongest evidence, material limitations, and any remaining action. Do not dump internal role-play transcripts unless the user asks for them.
© microsoft, 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 contrib/pi-research-workflow-skill of microsoft/ArgusAgent.
Open the folder on GitHubat commit 746f76b
Research Workflow 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 |
|---|---|---|---|---|---|---|
| Research Workflow this skillmicrosoft/ArgusAgent | 135 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Perplexity Web Searchdavila7/claude-code-templates | 32k | 12 repos | ~3.5k | Automated safety check: Notes | MIT | |
| Citation Verification GuideGalaxy-Dawn/claude-scholar | 5.7k | 3 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Article Fact Checkerdigoal/blog | 8.6k | — | ~939 | Automated safety check: Pass | GPL-2.0 | |
| Deep Research Agent TeamImbad0202/academic-research-skills | 51k | — | ~13k | Automated safety check: Pass | Custom licence | |
| Docs Grounding Verifiermicrosoft/apm | 4k | — | ~1.9k | Automated safety check: Pass | MIT |
davila7/claude-code-templates
Runs web-grounded searches through Perplexity's Sonar models over OpenRouter for current events, recent literature and cited facts beyond the model's training cutoff.
Galaxy-Dawn/claude-scholar
Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references.
digoal/blog
三层审查模型,逐段逐句验证文章真伪、证据链与逻辑结构。Use when the user asks to fact-check, verify, audit, or evaluate the credibility of an article, essay, report, opinion piece, social-media post, or any written claim —…
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.
microsoft/apm
A skill your agent uses to verify CLAIM-LEVEL grounding of a documentation page (or set of pages) against the source code.
bradygaster/squad
Review and validate claims using counter-hypothesis testing.
microsoft/ArgusAgent
Portable outer-operator procedure for durable Argus missions across five hosts.
microsoft/ArgusAgent
A skill your agent uses for Argus implementation, research, document, planning, review, and orchestration work that must stay evidence-driven and lean.
microsoft/ArgusAgent
A skill your agent uses when researching a biomedical target and disease relationship, mechanism, human evidence, clinical translation, safety, failed programs, competitive trials, or an auditable…
microsoft/ArgusAgent
A skill your agent uses when work needs persistent multi-step execution, independent review, resumable project state, or long-running research and engineering coordination through Argus.
microsoft/ArgusAgent
A skill your agent uses when checking an Argus project's progress, pending questions, active role, diagnostics, selected artifacts, intervention state, recovery options, or graceful stop status.
Categories
Plan and execute multi-step research, surveys, feasibility studies, and evidence-heavy analyses with adaptive planning, source verification, critic review, and cross-task learning. Research Workflow is an agent skill from microsoft/ArgusAgent, published by the product's own GitHub organization. Plan and execute multi-step research, surveys, feasibility studies, and evidence-heavy analyses with adaptive planning, source verification, critic review, and cross-task learning.
Research Workflow fits situations like: A request needs multiple dependent investigations; A durable evidence trail; do not use for simple factual questions; small one-step edits.
Run `npx skills add microsoft/ArgusAgent --skill research-workflow -a claude-code`. Or copy the skill folder (contrib/pi-research-workflow-skill in microsoft/ArgusAgent) into .claude/skills/research-workflow in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microsoft/ArgusAgent --skill research-workflow -a codex`. Or copy the skill folder (contrib/pi-research-workflow-skill in microsoft/ArgusAgent) into .agents/skills/research-workflow 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 microsoft/ArgusAgent --skill research-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-workflow, .gemini/skills/research-workflow, .github/skills/research-workflow and .opencode/skills/research-workflow in your project.
SKILL.md names no scripts, command-line tools or credentials: Research Workflow is instructions for the agent only.
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.
Research Workflow is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k 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 Research Workflow: Perplexity Web Search (davila7/claude-code-templates, 32k stars), Citation Verification Guide (Galaxy-Dawn/claude-scholar, 5.7k stars), Article Fact Checker (digoal/blog, 8.6k stars) and Deep Research Agent Team (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/ArgusAgent, which has 135 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 2, 2026.
Source: microsoft/ArgusAgent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.