iclems

Air France - KLM

Data Analysisv1.0.1
By iclemsUpdated 2026-05-172 versions · latest released 2026-01-29airfrance-afkl@clawhub_iclems/airfrance-afkl
Data InsightsWeb Scraping

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.

Installs
106
Downloads
3.4K
Stars
2
Overall Rank
#3,358
Top 67% overall · Top 64% in Data Analysis
PlatformInstallsDownloadsStarsComments
ClawHub ↗1063.4K2-
SkillHub ↗1063.3K2—

Platforms count differently and update at different times.

What this skill does

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

What you can do with it

  • Check the current status of a specified flight
  • Plan flight-change alerts and polling intervals
  • Review previous-flight relations and optional aircraft information

When to use it

  • When the user supplies a flight number and requests a lookup or monitor
  • When API credentials can be protected and query frequency kept within service limits
  • When important travel decisions can be checked against official airline or airport information

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Check this flight and verify the result against the airline’s official page
Plan low-frequency status monitoring that alerts only on meaningful changes
Explain that previous-flight and Wi-Fi enrichment is advisory

Monthly Trend

Downloads3.4K
2.0K2.7K3.5K2026-03 · Downloads 2.1K2026-06 · Downloads 2.8K2026-07 · Downloads 3.1K2026-08 · Downloads 3.2K2026-09 · Downloads 3.4K26-0326-09
Stars2
1232026-03 · Stars 22026-06 · Stars 22026-07 · Stars 22026-08 · Stars 22026-09 · Stars 226-0326-09

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.

MonthDownloadsMoMStars
2026-093.4K—2
2026-083.2K+4.6%2
2026-073.1K+9.4%2
2026-062.8K—2
2026-032.1K—2

SKILL.md (original)

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.

3.4 KB · ClawHub v1.0.1
---
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)
Show all (80 lines)
- 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**.

Popular in Data Analysis

Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.