Results for “find”

Plans and executes complex, multi-step research by decomposing questions, orchestrating subagents, and synthesizing findings into reports.

Identify disruption opportunities and architect business model innovation. Use when the user says "lets create an innovation strategy" or "I want to find disruption opportunities"

Finds the open GitHub PR for the current branch and helps address review comments using the gh CLI.

Audit an existing processkit skill against the 5 Skill Killers, the Agent Skills standard, and Anthropic's troubleshooting playbook, producing a categorized findings report and draft Gotchas.

Data analysis workflow from import through modeling and communication. Use when analyzing a dataset, exploring data, building a statistical model, selecting features, or communicating findings to stakeholders.

Discovers, finds, audits, repairs, adapts, crafts, runs, debriefs, saves, and prepares repeatable AI-agent loops for publication, treating loops as bounded feedback systems.

Legal contract analysis using CUAD dataset (41 risk categories). Supports NDA, SaaS, M&A, employment, payment/merchant, and finder/broker agreements. Identifies red flags, suggests redlines, compares to market standards.

Mines git history to find files and test suites that historically change together with specified target files (co-change relations). Use before making changes or running tests to discover coupled code.

Three-phase vulnerability chain analysis — parallel agents find individual weaknesses, then a synthesis step identifies which combinations escalate to critical impact. Inspired by Strix (usestrix/strix) "Graph of Agents" pentesting model.

Use when a human asks to connect to or enter Agent Internet or AI Internet, get their agent online, or open Agent Internet Browser, Bot Browser, a Bot page, a Bot homepage, a domain alias, a chain pin, a MetaApp, a MetaFile, or a map through the existing local Browser entrypoint, including opening a resource in a new Browser tab; also use when the human wants to find or discover on-chain MetaApps by topic, tag, publisher, or time range — such as "what on-chain mini-games exist", "apps published in the last 30 days", or "open the on-chain buzz app" — list the remixes of a known app, read what an app does, or remix and republish an existing MetaApp; also use when the human wants to find or discover on-chain users or Bots by name, personality, skill, or recency — such as "view Alice's bot page", "find cheerful users to chat with", or "find a bot that can translate" — or read an identity's full on-chain profile.

Find Earth2Studio models, data sources, and examples for weather/climate use cases by consulting live documentation and verifying compatibility via the lexicon system.

Performs advanced algebra design tasks such as computing derivatives, finding eigenvalues, and proving theorems using numerical methods and mathematical best practices.

Code review skill — auto-scopes from git changes, reads DOJO.md for project conventions, and produces structured findings with priority levels. Supports quick single-pass review and deep 3-agent parallel audit.

Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

Find out why a coding-agent skill won't fire — grade each SKILL.md A–F on activation, simulate which skill a prompt triggers, and flag collisions where one silently shadows another.

Discovers and installs agent skills from the open ecosystem when users ask for help with specific tasks or express interest in extending capabilities.

Finds gaps between documented intent and actual implementation in codebases, catching bugs that generic scanners miss because they lack a model of intent.

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Run GGUF models locally with llama.cpp, including finding the right file on the Hugging Face Hub, installing, quantizing, serving, and using Python bindings.

Scan and audit AI agent skills for security risks before installation, producing a PASS/WARN/FAIL verdict with findings and remediation guidance.

Queries Hugging Face benchmark leaderboards to find the best AI models for a task, filters by device constraints, and returns a ranked comparison table with scores.

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Deduplicates against CRM (Google Sheets). Supports Apollo API and MCP tools.

Perform a read-only, defect-first review of a specified code change and return every actionable finding. Use when another agent delegates review of uncommitted changes, a base-branch diff, a commit, or custom review instructions.

Orients researchers to an unfamiliar academic field by searching Consensus, building a strategic search plan with PICO or other frameworks, and synthesizing findings into a formatted Word document.

Assesses NumPy code for cuPyNumeric migration readiness by analyzing source code against an API support manifest and GPU-scaling idioms, producing a structured verdict with per-finding reasoning.

Extract structured best-selling product data from Amazon, including titles, prices, ratings, reviews, sales volume, and promotions, using the BrowserAct API.

Runs a plan file through the Codex CLI as an independent adversarial reviewer, then folds accepted findings back into the plan. Read-only sandbox; Codex never edits.

Discovers and evaluates community skills from skills.sh and awesome-openclaw-skills when local skills don't cover a need, scoring credibility and installing top recommendations with permission.

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

Discover, evaluate, install, and wrap external agent skills from ClawHub registry, skillflag-compliant CLI tools, and GitHub repos. Use when asked to find new capabilities, install a skill, browse what's available, or package a local skill for sharing.

Perform a read-only, defect-first review of a specified code change and return every actionable finding. Use when another agent delegates review of uncommitted changes, a base-branch diff, a commit, or custom review instructions.

Runs the current git diff through the Codex CLI for an independent, read-only second-opinion review, then triages findings back into the session for Claude to apply fixes.

Search and analyze news articles with media bias context, get balanced perspectives, access live stock/ETF/crypto data with AI analysis, and find memes by semantic meaning.

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.

Automatically discovers social media profiles for individuals or brands across platforms like Facebook, Twitter, Instagram, LinkedIn, and TikTok, returning profile URLs, follower counts, and bio snippets as a downloadable CSV.