Agent Builder Stack

Cross-platform executive operations skill for the IronClaw agent. The agent operates as chief of staff to a C-suite executive, coordinating across email, calendar, code, projects, and outbound partner messaging via Google Workspace, GitHub, GitLab, ClickUp, and WhatsApp. Designed for one-click deploy demos to enterprise partners (financial services, banking groups, software firms) with proper OAuth and System User credentials provisioned at deploy time. Pairs prose guidance for the LLM with deterministic Python scripts in `python_scripts/` for the canonical recurring workflows.

Microsoft 365 business workflow patterns for the IronClaw agent. Covers Outlook email, Excel data operations, Teams channel communication, Word and PowerPoint document generation, and SharePoint and OneDrive file management via Microsoft Graph.

Triage open GitHub pull requests across one or more repositories and produce a prioritized, bucketed review digest. Scores each PR on CI status, mergeability, staleness, size, and review state, then groups them into Blockers, Quick wins, First contributors, Aging, and Normal so the reviewer knows what to look at first instead of paging through the GitHub UI. Read-only — never comments, labels, closes, or merges.

API documentation, user guides, READMEs, SOPs, knowledge base articles, release notes, and docs-as-code workflows.

Architect high-performing email campaigns with list segmentation, subject line optimization, drip sequence design, A/B testing, automation workflows, deliverability management, and CAN-SPAM/GDPR compliance.

Reads the 25 most recent Bitcoin posts from r/cryptocurrency via the public RSS feed (no API key — Reddit's JSON API is blocked but RSS works), classifies each post's sentiment as positive, negative, or neutral from its title and description, and returns a Telegram summary with the counts and an overall mood label: BULLISH if positives lead by 5+, BEARISH if negatives lead by 5+, otherwise MIXED, plus the most striking post it found.

Watches specific web pages and reports the day anything changes — pricing, job postings, product updates. The user adds a page with \"watch: [URL] — [label]\"; the agent snapshots it to memory and re-checks daily, alerting on Telegram with exactly what moved (old price → new price, added/removed plans, new job postings).

Logs the user's decisions in memory and confronts them with the outcome later, so they actually learn from their own track record instead of remembering only their wins. The user logs a decision with \"decision: [what you decided] | check in [timeframe]\"; the agent stores it and, on the follow-up date, sends the exact decision back on Telegram and asks for a verdict. Verdicts build a running track record (right / wrong / mixed) and surface patterns over time.

Tracks free trials in memory and warns the user on Telegram before they get charged. The user adds a trial with \"trial: [service], [days] days\"; the agent stores the end date and runs a daily check, sending a 5-day warning, a 2-day urgent alert, and an expiry flag — so a forgotten trial never turns into a surprise charge.

Microsoft Graph integration. 14 actions across Outlook, Excel, Teams, OneDrive, SharePoint, Calendar, plus Word and PowerPoint document generation. OAuth via Microsoft Entra ID.

NEAR Protocol JSON-RPC integration. 27 actions covering account state, access keys, contract storage and code, view function calls, blocks, chunks, validators, transaction lifecycle, gas and protocol config, state changes, network status, and light-client proofs. No credentials required for read actions.

Captures brain-dumped tasks into a structured Obsidian vault as task notes whose frontmatter properties link them to domains, clients, and projects. Maintains a centralized, always-current task ledger. The agent infers the domain and entities from how the user speaks and asks rather than guesses.

At the start of a planning cycle (monthly or quarterly), the agent walks the active project list, scores each against the organization's stated strategic priorities from the vision doc, surfaces projects that don't ladder up to a priority, and produces a prioritization brief leadership reviews. Recommendations are inputs to a human decision, not the decision.

Stores messages and yearly self-interviews in memory and delivers them back to the user on Telegram on a future date they choose — months or years later — so their past self speaks to their future self, unedited. The user seals a letter with \"capsule: [message] | deliver in [timeframe]\" or runs a yearly self-interview with \"interview me\". Sealed content is never shown before its delivery date; on that date the agent sends it back verbatim.

Holds the user to their own trading plan when emotions take over. The user writes a plan with \"plan for [TOKEN]: [rules]\" (exit targets, stop losses, no-buy zones); the agent stores it and checks the price every 4 hours, and when a level is hit it sends the exact rule back — in the user's own words, with the date they wrote it — so the plan made by their rational self reaches them at the moment they're most likely to abandon it. Each level fires once, no spam. It is the user's own plan, never advice.

Master pandas, NumPy, and data wrangling at scale covering I/O optimization, dtype strategy, cleaning workflows, EDA patterns, aggregations, joins, and memory-efficient pipelines for large datasets.

Production Python guidance covering type safety, Pydantic v2, FastAPI services, async patterns, pytest testing, virtual environments, and performance profiling.

Systematic code review methodology covering security vulnerabilities, performance bottlenecks, SOLID principles, refactoring techniques, and PR review workflows.