According to AlphaMoat, as of 2026-09, Air France - KLM has 3,359 downloads and 2 stars — ranked #3,358 of 5,078 AI skills overall, and #252 of 399 in Data Analysis.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 106 | 3.4K | 2 | - |
| SkillHub ↗ | 106 | 3.3K | 2 | — |
Platforms count differently and update at different times.
The primary describes status queries by flight number and departure date, alerts for meaningful delay, gate, or aircraft changes, previous-flight relations, polling guidance, and optional aircraft-registration, cabin-recency, and Wi-Fi enrichment. these enrichments and delay heuristics are best-effort and may not reflect the final operational state. Keep API credentials narrowly scoped and secure, and verify important travel decisions with official airline or airport sources.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 3.4K | — | 2 |
| 2026-08 | 3.2K | +4.6% | 2 |
| 2026-07 | 3.1K | +9.4% | 2 |
| 2026-06 | 2.8K | — | 2 |
| 2026-03 | 2.1K | — | 2 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: airfrance-afkl description: Track Air France flights using the Air France–KLM Open Data APIs (Flight Status). Use when the user gives a flight number/date (e.g., AF007 on 2026-01-29) and wants monitoring, alerts (delay/gate/aircraft changes), or analysis (previous-flight chain, aircraft tail number → cabin recency / Wi‑Fi). Also use when setting up or tuning polling schedules within API rate limits. --- # Air France (AFKL Open Data) flight tracker ## Quick start (one-off status) 1) Create an API key (and optional secret)
- Register on: https://developer.airfranceklm.com - Subscribe to the Open Data product(s) you need (at least **Flight Status API**) - Generate credentials (API key; some accounts also provide an API secret) 2) Provide API credentials (do not print them): - Preferred: env vars `AFKL_API_KEY` (and optional `AFKL_API_SECRET`) - Or files in your state dir (`CLAWDBOT_STATE_DIR` or `./state`): - `afkl_api_key.txt` (chmod 600) - `afkl_api_secret.txt` (chmod 600, optional) 2) Query flight status: - Run: `node skills/airfrance-afkl/scripts/afkl_flightstatus_query.mjs --carrier AF --flight 7 --origin JFK --dep-date 2026-01-29` Notes: - Send `Accept: */*` (API returns `application/hal+json`). - Keep within limits: **<= 1 request/sec**. When making multiple calls, sleep ~1100ms between them. ## Start monitoring (watcher) Use when the user wants proactive updates. - Run: `node skills/airfrance-afkl/scripts/afkl_watch_flight.mjs --carrier AF --flight 7 --origin JFK --dep-date 2026-01-29` What it does: - Fetches the operational flight(s) for the date window. - Emits a single message only when something meaningful changes. - Also follows the **previous-flight chain** (`flightRelations.previousFlightData.id`) up to a configurable depth and alerts if a previous segment is delayed/cancelled. Polling strategy (default): - >36h before departure: at most every **60 min** - 36h→12h: every **30 min** - 12h→3h: every **15 min** - 3h→departure: every **5–10 min** (stay under daily quota) - After departure: every **30 min** until arrival Implementation detail: run cron every 5–15 min, but the script self-throttles using a state file so it won’t hit the API when it’s not time. The watcher prints **no output** when nothing changed (so cron jobs can send only when stdout is non-empty). ## Input shorthand Preferred user-facing format: - `AF7 demain` / `AF7 jeudi` Interpretation rule: - The day always refers to the **departure date** (not arrival). Implementation notes: - Convert relative day words to a departure date in the user’s timezone unless the origin timezone is explicitly known. - When ambiguous (long-haul crossing midnight), prefer the departure local date at the origin if origin is known. (For scripts, still pass `--origin` + `--dep-date YYYY-MM-DD`.) ## Interpret “interesting” fields See `references/fields.md` for: - `flightRelations` (prev/next) - `places.*` (terminal/gate/check-in zone) - `times.*` (scheduled/estimated/latest/actual) - `aircraft` (type, registration) - “parking position” / stand-type hints (when present) - Wi‑Fi hints and how to reason about cabin recency ## Cabin recency / upgrade heuristics When aircraft registration is available: - Use tail number to infer **sub-fleet** and likely cabin generation. - If data suggests older config (or no Wi‑Fi), upgrading can be more/less worth it. Be conservative: - Open Data often doesn’t expose exact seat model; treat this as **best-effort**.
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.