Write professional, persuasive complaint letters to US airlines on behalf of passengers. Emphasizes loyalty status, DOT regulations, and the airline's own published commitments. Use when: user wants to complain to an airline, request compensation, write a complaint letter, dispute an airline's response, escalate an airline issue, file a DOT complaint, or mentions a bad flight experience they want to act on. Also trigger when user describes: flight delay, cancellation, lost baggage, damaged baggage, denied boarding, downgrade, poor service, broken amenities, tarmac delay, missed connection, or any airline service failure they want addressed.

How an LLM agent reads and updates the shared travel-credits inventory at ~/.claude/travel-credits/ — flight credits, vouchers, upgrade certificates, and airline or hotel compensation, tracked for a whole family across every carrier and brand. Actions: check store readiness and bootstrap it; migrate the store to the current record shape; list credits; show what is expiring; match credits against a booking scenario; show compensation history; add a credit; update one; mark one used; handle errors. Use whenever a question turns on what credits, vouchers, or certificates are on hand — before searching flights, when presenting an itinerary, after a booking, or when an airline grants compensation.

Use when the user asks to check, review, look at, or act on a pull request by number — "check PR 5", "review PR 12", "what's going on with PR 7", "look at this PR". Classifies the PR as same-repo or fork. Fork PRs are skipped by the policy reviewer's fork-guard; this skill offers to adopt the fork branch into the base repo as a same-repo PR the reviewer can run on, preserving the contributor's commits. Same-repo PRs pass straight through to the existing reviewer.

Hold a daily standup with the named Herdr agents and print a table the operator can find while scrolling back through a long session: ask each idle worker for four lines (DONE / PLAN / BLOCKED / REPORT), fill the busy ones from the round log, and render a banner-topped fixed-width block plus a Markdown record. Use when the user wants a standup, a daily status round, a summary of what each agent is doing, "what is everyone working on", or a status table for the team. Requires HERDR_ENV=1.

Run one task round as the team lead of three coding agents inside Herdr (https://herdr.dev): measure each worker's subscription headroom, assign the developer / tester / reviewer roles to the workers that can afford them, clear each worker's context and send it a fresh role brief, wait for the report files, gate the round, and hand the merge to the `release` skill. Use when the user wants to run a team round, dispatch a task to the agent team, assign roles to the Herdr agents, load-balance the agents by usage or headroom, brief the developer / reviewer / tester, or collect the workers' reports. Requires HERDR_ENV=1.

Route and calibrate research drawn from socially noisy web communities so agents do not mistake crowd mood for truth. Use when research notes, summaries, or quoted material come from Moltbook, Hacker News, Reddit, or Product Hunt and the job is to decide how much weight that material deserves, separate concrete weak signals from vibe/noise, or choose the right source-specific calibration skill before carrying findings forward.

Calibrate research done on Hacker News so agents do not mistake experienced technical cynicism, anti-hype sentiment, or comment-thread confidence for balanced evidence. Use when summarizing Hacker News reactions, extracting concerns from HN threads, citing HN as part of research, or deciding how much weight to give repeated negative or skeptical Hacker News comments.

Interpret and calibrate already-collected research material derived from Moltbook so agents do not mistake noise, spam, novelty, or social heat for reliable evidence. Use when weighing notes, summaries, or quoted material from Moltbook as part of research, deciding whether a Moltbook claim is worth following up, checking source reliability or evidence quality, or separating concrete weak signals from social-performance noise. Prefer when Moltbook is being used as a weak-signal discovery source rather than as authoritative proof. This skill classifies gathered Moltbook material as concrete report, vibe signal, or noise; flags evidence strength and uncertainty; and suggests whether the claim is follow-up-worthy. This is an informational calibration skill, not a browsing or execution workflow.