research-software
The research-software skill systematically investigates software tools and libraries by cloning their latest stable repository version, exploring CLI commands and configuration options, analyzing recent GitHub activity, and synthesizing findings into a structured markdown output with commands, config options, environment variables, and known issues. Use this when you need current, code-focused technical specifications for a tool released or updated in 2025-2026, prioritizing actual implementation details over documentation.
git clone --depth 1 https://github.com/boshu2/agentops /tmp/research-software && cp -r /tmp/research-software/images/gemini/skills/research-software ~/.claude/skills/research-softwareSKILL.md
# research-software — Software Research > **Rules:** Latest STABLE tag (not main). Filter to 2025-2026. Code > Docs. Skip Stack Overflow. ## Output First Every research produces this structure: ```markdown ## [Tool] vX.Y.Z (YYYY-MM-DD) **Repo:** github.com/org/repo @ abc123 ### Commands | Task | Command | Notes | |------|---------|-------| ### Config | Option | Default | Notes | |--------|---------|-------| ### Env Vars | Variable | Purpose | |----------|---------| ### Gotchas - [problem]: [fix]. Source: [PR/issue/code] ### Sources - Code: [file:line] - PRs: #123, #456 - Posts: [url] ``` --- ## THE PROMPT ``` Research [TOOL] for [PURPOSE]. Clone to /tmp, checkout latest stable tag. Spawn Explore agent on source. Find: CLI, config, hidden flags, env vars. Parallel: GitHub PRs/issues, web search "[tool] 2025". Output: skill-ready markdown. ``` --- ## Pipeline ```bash # 0. Detect context (if in a project) # Check package.json, Cargo.toml, pyproject.toml for existing versions # 1. Clone + stable tag git clone --depth 1 https://github.com/[org]/[repo] /tmp/[repo]-research cd /tmp/[repo]-research && git fetch --tags && git checkout $(git describe --tags --abbrev=0) # 2. Spawn Explore agent (parallel with step 3-4) # → "Find all CLI commands, config options, hidden flags, env vars in /tmp/[repo]-research" # 3. GitHub activity gh pr list -R [org]/[repo] --state merged --limit 30 --json title,mergedAt gh issue list -R [org]/[repo] --label question --limit 20 # 4. Web search # → "[tool] 2025" "[tool] 2026" "[tool] tutorial" # 5. Synthesize → Output structure above # 6. Cleanup rm -rf /tmp/[repo]-research ``` --- ## Checklist - [ ] **Detect context:** Check package.json/Cargo.toml/pyproject.toml for versions - [ ] **Clone repo** to /tmp, checkout latest stable tag - [ ] **Explore agent:** CLI commands, config schema, hidden flags, env vars - [ ] **GitHub:** Recent merged PRs, issues tagged "question"/"documentation" - [ ] **Web search:** "[tool] 2025", "[tool] 2026", skip pre-2025 - [ ] **Synthesize:** Commands table, config table, gotchas, patterns - [ ] **Cite sources:** repo@commit, PR numbers, blog URLs - [ ] **Clean up:** `rm -rf /tmp/[repo]-research` --- ## Source Priority ``` 1. Source code (actual behavior) 2. Recent PRs (features being added) 3. GitHub issues (real problems) 4. Blog posts 2025-2026 (practical patterns) 5. Official docs (baseline, often outdated) ``` **Skip:** Stack Overflow, anything pre-2025, basic tutorials --- ## Top Mistakes | Mistake | Fix | |---------|-----| | Using beta/canary | Checkout latest stable TAG, not main | | Old content (pre-2025) | Always add year to search queries | | Trusting docs over code | Code wins: check actual defaults in source | | Missing env vars | Search `process.env`, `std::env`, `os.environ` | | Forgetting cleanup | `rm -rf /tmp/[repo]-research` when done | --- ## Key Searches ```bash # Hidden/experimental flags rg "hidden|experimental|unstable" /tmp/[repo]-research # Environment variables by language rg "process\.env\." /tmp/[repo]-research --type ts # TypeScript rg "std::env::" /tmp/[repo]-research --type rust # Rust rg "os\.environ" /tmp/[repo]-research --type py # Python rg "os\.Getenv" /tmp/[repo]-research --type go # Go # Recent changes git log --oneline --since="2025-06-01" | head -30 ``` --- ## Done When - [ ] Have version number from stable tag - [ ] Commands table has 5+ entries - [ ] Config table covers main options - [ ] Gotchas section has 3+ real issues from GitHub/code - [ ] All sources cited with links --- ## Decision Tree ``` What are you researching? │ ├─ CLI tool (wrangler, cargo, bun) │ Focus: src/cli/, commands, flags, env vars │ ├─ Library/Framework (React, Next.js) │ Focus: packages/*/src/, exported APIs, deprecations │ ├─ Runtime (Bun, Deno, Node) │ Focus: built-ins, runtime flags, compat layers │ └─ Database/Service (D1, R2, Postgres) Focus: query syntax, config, limits, gotchas ``` ### Key Searches by Type | Type | Where to look | Key searches | |------|---------------|--------------| | CLI | `src/cli/`, `bin/` | `hidden.*true`, `#[arg(`, `process.env` | | Library | `packages/*/src/`, `index.ts` | `export `, `deprecated`, `experimental` | | Runtime | `src/`, built-ins | `flag`, `--`, `compat` | | Database | queries, limits | `limit`, `max`, `error` | **Deep strategies:** [STRATEGIES.md](references/STRATEGIES.md) --- ## Subagent: Code Investigator ``` Investigate /tmp/[repo]-research for [TOOL]. Find: CLI commands, config options, hidden/experimental flags, env vars. Check git log --oneline -30 for recent changes. Output as markdown tables. ``` Use model: `sonnet` (balance of speed + depth) --- ## Subagent: Web Researcher ``` Search "[TOOL] 2025" and "[TOOL] 2026". Find 5-10 recent tutorials, blog posts, announcements. Extract: patterns, gotchas, tips. Skip: Stack Overflow, anything pre-2025, basic tutorials. ``` Use model: `haiku` (fast, web-focused) --- ## References | Need | File | |------|------| | Output templates by tool type | [OUTPUT-TEMPLATES.md](references/OUTPUT-TEMPLATES.md) | | Example research sessions | [EXAMPLES.md](references/EXAMPLES.md) | | Tool-specific deep strategies | [STRATEGIES.md](references/STRATEGIES.md) |
Switch a caller-selected coding-agent Triggers: "switch account", "rotate coding-agent account".
Use when operating ACFS flywheel health checks, init, and agent loop tooling from ~/acfs/bin/acfs.
Use Agent Mail as an optional messaging and Triggers: "coordinate writers", "reserve files".
Operate explicit orchestrator, implementer Triggers: "agent-native factory", "role-shaped agent panes", "persistent workers".
Run AGY headlessly via scheduled ticks or `agy -p`, capture agentapi JSONL evidence, and validate automated AGY loops or event streams.
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Use an explicitly selected AGY runtime for Triggers: "agy", "antigravity", "AGY evidence".
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