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Agent Skill · 研究检索

super-flight(超级飞行)

super-flight 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

super-flight 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 24,758。

总安装 3,930周安装 159GitHub Stars 公开资料未说明下载 1,234核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:super-flight(超级飞行)
来源仓库:https://github.com/zhangxchao/super-flight
安装命令:
openclaw skills install super-flight
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install super-flight

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过基于角色的硬约束比较 7 天内的多日期单程航班价格,按历史排序并提供可解释的建议。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install super-flight;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

super-flight 怎么安装?

在终端执行 openclaw skills install super-flight。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

super-flight 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

super-flight 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install super-flight 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

super-flight 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

super-flight 用的人多吗?

公开数据是累计安装 3,930 次,近一周安装 159 次,下载 1,234 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

super-flight 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
super-flight

超级飞行 · 本页

3,930—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
super-flight
description
Multi-date flight price comparison assistant. Supports one-way multi-date (≤7 days) comparison via a two-stage flow — discover candidate flights, then lock 1–2 flights and run a date×price matrix. Binds hard constraints to personas (亲子/商务/学生/老人/蜜月 — family/business/student/senior/honeymoon), defaults sort order from historical orders, and provides explainable recommendations. Triggers on: 机票查询/多日期比价/拼假/周末比价/最便宜几天/同航班不同日价格/家庭出行机票/商务票比价/蜜月机票, flight search, multi-date price comparison, cheapest days, same flight across dates, family/business/honeymoon flight planning.
compatibility
Requires flyai-cli to be installed (npm i -g @fly-ai/flyai-cli)
license
MIT

✈️ Multi-Date Flight Price Comparison Assistant

Built on flyai search-flight, this skill is designed around the "one-way multi-date price comparison" scenario via a two-stage flow: Discover → Lock & Compare. It does not blindly recommend the lowest price — it filters by persona hard constraints, then ranks with reference to historical orders and explains every recommendation.

Triggers

Activate when the user talks about comparing flight prices, contrasting the same route across different dates, stitching together long weekends, asking "which days are cheap", "Fridays this month", "around Qingming", the price of a specific flight across multiple days, or planning a trip with children / for business / with seniors / for a honeymoon / as a student.

Quick Examples

  • "比一比这个月周五北京去上海,哪天最便宜" / "Compare Beijing→Shanghai on Fridays this month, which is cheapest" → Stage 1 + Stage 2
  • "4/26 北京到上海,推荐几趟" / "Recommend some flights Beijing→Shanghai on 4/26" → Stage 1
  • "CA1883 这周还有哪天便宜" / "Which days are cheap for CA1883 this week" → Stage 2 (skip Stage 1)
  • "带娃下周去三亚,哪天合适" / "Traveling with kids to Sanya next week, which day works" → Persona=亲子 (family) + Stage 1
  • "商务,4/22 早上到上海" / "Business trip, arrive Shanghai morning 4/22" → Persona=商务 (business) + Stage 1 + time-window filter

Prerequisites

  • flyai-cli: npm i -g @fly-ai/flyai-cli
  • Verify: flyai search-flight --origin "北京" --destination "上海" --dep-date 2026-04-26 returns JSON

Optional for better results:

flyai config set FLYAI_API_KEY "your-key"

Get the key at https://flyai.open.fliggy.com/. If a CLI method is missing, upgrade with: npm i -g @fly-ai/flyai-cli.

Data Files

super-flight/
├── SKILL.md                      ← this file
├── references/
│   └── search-flight.md          ← flyai search-flight params & response schema
└── assets/
    ├── personas.json             ← hard constraints for 5 personas (read-only)
    ├── preferences.json          ← long-term user preferences (location/companions/airlines/sort)
    └── history.json              ← selection history (append-only)

This skill only reads/writes assets/preferences.json and assets/history.json. Do not touch any other paths.

Input Safety Validation (pre-execution checks)

All user inputs must pass the following validation before being spliced into a flyai search-flight command, to prevent shell injection:

ParameterAllowed character setMax length
City name (origin/destination/transfer-city)Chinese characters, letters, digits, spaces20
Dates (dep-date/back-date and start/end variants)digits + -, must match YYYY-MM-DD10
Hours (dep-hour-start/end, arr-hour-start/end)integer 0–232
Flight number (transport-no)uppercase letters + digits, comma-separated200
Cabin class (seat-class-name)Chinese characters, letters, commas30
journey-typeonly 1 or 21
sort-typeonly 1–81
max-price / total-duration-hourpositive integer6

Rejection policy: if any of the following characters appear → reject immediately, ask the user to re-enter, and do not execute any command: ` ` $ ( ) { } ; & | \ < > ! ' "` newline.

All parameter values must be wrapped in double quotes when passed to the command, e.g. --origin "北京".

Global Workflow

User input
  ↓
1. Detect persona (optional) → load hard constraints
  ↓
2. Decide the stage:
   - "recommend a few flights" only → Stage 1
   - "which days are cheap" / "compare multiple dates" → Stage 1 + Stage 2
   - user gave a specific flight number → jump to Stage 2
  ↓
3. Run Stage 1 (Discover) or Stage 2 (Lock & Compare)
  ↓
4. Append to history.json

Persona Detection

Personas are keyed in personas.json by their Chinese canonical key (亲子, 商务, 学生, 老人, 蜜月). Each entry also carries an aliases array of English aliases. Both Chinese and English trigger words are supported — match either and resolve to the same canonical key.

User trigger words (CN + EN)Canonical keyAlias
带娃, 带孩子, 带宝宝, 亲子, 儿童票 / with kids, kids, children, family, parent-child, child ticket亲子family
出差, 商务, 开会, 短差 / business, business trip, work trip, meeting商务business
学生, 预算, 便宜, 穷游 / student, budget, cheap, backpacking学生student
带爸妈, 带爷爷, 带老人, 老人家 / with parents, with grandparents, senior, seniors, elderly老人senior
蜜月, 婚假, 度假, 渡假 / honeymoon, wedding leave, vacation, holiday蜜月honeymoon

Lookup rule: when matching a user phrase, check both the canonical Chinese key and every value in aliases (case-insensitive, whitespace/hyphen-tolerant). Always store and reference the canonical Chinese key internally (e.g. in history.json's persona_tag, preferences.per_persona_overrides). Display can use either form or both (e.g. 【亲子 / family】).

  • When matched, load the corresponding hard constraints from personas.json and call them out in the first output, e.g. "Applied 【亲子 / family】 defaults: no red-eye + transfer ≥ 60min."
  • No match → do not force a persona; proceed with the generic flow (no hard constraints).
  • If the user volunteers "this trip is our honeymoon" or "we're on our honeymoon", accept it directly and resolve to 蜜月.

Stage 1: Discover

1.1 Input Collection

Required core parameters:

ParameterMeaningWhat to do when missing
Origin--originIf preferences.home_city has a value, first ask "Depart from {home_city} by default?"; otherwise ask directly
Destination--destinationAsk directly
Departure date--dep-dateParse natural language ("tomorrow", "next Friday", "4/26"), convert to YYYY-MM-DD; if unparseable, ask

Batch the question: ask for everything missing in a single turn; avoid multi-round pinging.

1.2 Hard-Constraint Pre-Filter + Explicit Label

Map persona hard constraints to CLI parameters:

Hard constraintMaps to
journey_type: 1--journey-type 1
reject_redeye_departure: true--dep-hour-start 6 --dep-hour-end 23
reject_overnight_arrival: true--arr-hour-start 6 --arr-hour-end 23
min_transfer_minutes: 60filter out results with transfer wait < 60min in post-processing (the API does not support this directly)

The output header must make the filter explicit, e.g.:

Applied 【老人 / senior】 filter: direct only + daytime departure (6:00–23:00) + daytime arrival. Reply "不过滤 / no filter" to see all results.

1.3 Default Sort (derived from historical orders)

Before querying, read history.json:

  1. Filter records with the same origin→destination route (most recent 20).
  2. If there are matching records:

- Compute the distribution of sort_used across them → pick the most frequent as this turn's default. - Example prompt: "Last time for 北京→上海 you sorted by 【price ascending】; keep it? (yes / switch to recommended / switch to direct-first)"

  1. If there are no matching records: default to --sort-type 2 (platform recommended) and note in the recommendation reason: "First query on this route, using platform recommended sort."

1.4 Call search-flight

flyai search-flight \
  --origin "{origin}" \
  --destination "{destination}" \
  --dep-date "{YYYY-MM-DD}" \
  [--journey-type 1] \
  [--dep-hour-start N --dep-hour-end N] \
  [--arr-hour-start N --arr-hour-end N] \
  [--seat-class-name "经济舱"] \
  [--max-price N] \
  --sort-type {N}

1.5 Output Top 3–5

Take the first 3–5 rows of itemList (after secondary filtering by hard constraints):

### ✈️ 4/26 (Sun) 北京→上海 · Top 3 picks
> Applied 【亲子 / family】 filter: no red-eye (dep 23:00–06:00) | Sort: price ascending (carried over from last time)

| # | Flight | Dep → Arr | Duration | Cabin | Price | Reason |
|---|--------|-----------|----------|-------|-------|--------|
| A ⭐ | CA1883 (Air China) | 21:00→23:20 | 2h20m | Economy | from ¥580 | Lowest price + you picked this last time |
| B   | MU5137 (China Eastern) | 08:00→10:15 | 2h15m | Economy | from ¥620 | Morning daytime flight, good with kids |
| C   | CZ3104 (China Southern) | 15:30→17:50 | 2h20m | Economy | from ¥650 | Afternoon departure, no early wake-up |

[Book A]({jumpUrl_A}) [Book B]({jumpUrl_B}) [Book C]({jumpUrl_C})

Always end with: "Want to pick 1–2 flights and compare their prices across other dates? (enter multi-date comparison)"

1.6 International Long-Haul Fallback: Direct → Connecting

If the first search (direct, --journey-type 1) returns too few qualifying results on a long-haul international route, automatically retry with a connecting search and filter out unsuitable transfers. This is a fallback, not a default — most domestic routes should stay direct-only.

Trigger conditions (all must hold):

  1. Qualifying results (after persona hard-constraint filtering) < 3.
  2. Route is international: origin country ≠ destination country. Heuristic — if either city resolves to a non-mainland-China airport code (common cues: HKG, TPE, NRT/HND, ICN, BKK, SIN, KUL, CDG, LHR, FRA, JFK/LAX, SYD, DXB, …) or the depCityCode/arrCityCode returned by the first call straddles mainland China and anywhere else.
  3. Route is long-haul: any of

- straight-line distance roughly ≥ 3,000 km (e.g. Asia↔Europe/North America/Oceania/Middle East/Africa), - or the direct totalDuration returned by the first call is ≥ 6h, - or no direct results at all on a cross-region pair (e.g. 上海→伦敦, 北京→纽约, 广州→巴黎).

Short intra-Asia hops (北京→首尔, 上海→东京, 香港→曼谷) do not qualify — keep them direct-only unless the user explicitly asks for transfers.

Retry call:

flyai search-flight \
  --origin "{origin}" \
  --destination "{destination}" \
  --dep-date "{YYYY-MM-DD}" \
  --journey-type 2 \
  [--seat-class-name ...] \
  [--max-price ...] \
  --sort-type {N}

Do not pre-set --transfer-city — let the API surface options, then filter in post-processing.

Transfer filter rules (post-process itemList):

RuleThresholdReason
Max segments≤ 2 (one transfer only)Two transfers on long-haul = fatigue + missed-connection risk
Transfer wait time90 min ≤ wait ≤ 6 h<90 min too tight for international customs/immigration; >6 h wastes the day
Total duration penaltyreject if total > 1.6 × direct totalDuration (or > 2 × if no direct baseline)Avoid absurd detours
Overnight transferreject if transfer window fully covers 00:00–05:00 at the transfer citySleeping in airport hurts, especially for 老人/亲子
Persona-specific老人 (senior) / 亲子 (family): min transfer ≥ 120 min + no overnight transfer + same terminal preferred when data availableSlower pace, kids/elderly need buffer
Visa risk (advisory, not filter)flag transfer-city in US / UK / Canada / Australia as "may require transit visa"Inform user; don't silently drop

Output format (distinguish direct vs. transfer):

### ✈️ 6/12 (Fri) 上海→伦敦 · Top picks
> Direct flights matching 【商务 / business】 filter: only 1 → expanded to connecting (long-haul international).
> Transfer filter: ≤1 stop | wait 90min–6h | no overnight | total ≤ 1.6× direct duration.

**Direct (1)**
| # | Flight | Dep → Arr | Duration | Cabin | Price |
|---|--------|-----------|----------|-------|-------|
| A ⭐ | CA855 (Air China) | 13:30→18:55 | 12h25m | Economy | from ¥4,800 |

**Connecting (2, filtered from 14)**
| # | Route | Dep → Arr | Total | Transfer | Cabin | Price |
|---|-------|-----------|-------|----------|-------|-------|
| B | CX367→CX251 (Cathay, via HKG) | 08:40→翌日 06:55 | 16h15m | HKG 2h10m | Economy | from ¥3,650 |
| C | EK303→EK001 (Emirates, via DXB) | 23:55→翌日 07:30 | 14h35m | DXB 2h50m | Economy | from ¥3,980 |

🚫 Filtered out: 5 × overnight transfers, 4 × wait >6h, 3 × two-stop itineraries.

Degradation:

  • If connecting search also returns 0 after filtering → show the unfiltered top 3 with a warning banner ("No itinerary fully satisfies the transfer rules; showing the closest matches — please check the transfer carefully").
  • If the retry call itself fails → keep the direct-only result and tell the user "Connecting search unavailable, showing direct results only".

Do not retry with connecting when: user explicitly said "直飞 / direct only", or persona hard constraint has journey_type: 1 marked strict: true in personas.json (honor it).

Stage 2: Lock & Compare

2.1 Inputs

  • Candidate flights: 1–2 flight numbers (chosen from Stage 1 picks, or supplied directly).
  • Date set: in the user's own words.

2.2 Date Parsing & Confirmation (critical)

User's natural language → candidate date list → ask the user to confirm selection (never silently merge):

User saysParsed as
"Fridays this month"all remaining Fridays in the current month
"around Qingming"holiday date ± 2 days + adjacent weekend
"4/22, 4/25, 4/26"the three listed dates
"next weekend"next Saturday and Sunday
"May Day holiday"5/1–5/5

Display format:

I parsed the following candidate dates (N total) — please confirm:
- [ ] 4/22 (Tue)
- [ ] 4/29 (Tue)
- [ ] 5/6  (Tue)
- [ ] 5/13 (Tue)
(Last time on this route you picked 4/22 and 5/6 — carry over?)

**At most 7 dates are kept.** Reply with the dates to keep, or say "全选 / all".

Historical reference: which dates the user picked last time on the same route, used as the default suggested tick.

2.3 Call Strategy: One Call Per Day, In Parallel

  • At most 7 days × 2 flights = 14 parallel calls.
  • Per call:
  flyai search-flight \
    --origin "{origin}" \
    --destination "{destination}" \
    --dep-date "{YYYY-MM-DD}" \
    --transport-no "{flight_no}" \
    [pass through persona hard constraints]
  • A single failure or sold-out day → mark as "—", do not abort the whole flow.
  • From each response's itemList, take the adultPrice for the matching flight number (if multiple rows, take the lowest).

2.4 Output: Flight × Date Matrix + Recommendation

### 📊 Multi-Date Price Matrix
> Applied 【亲子 / family】 filter: no red-eye | Flights: CA1883, MU5137 | Dates: 4/22, 4/29, 5/6, 5/13

| Flight | 4/22(Tue) | 4/29(Tue) | 5/6(Tue) | 5/13(Tue) | Flight's lowest |
|--------|-----------|-----------|----------|-----------|-----------------|
| CA1883 (Air China 21:00→23:20) | ¥580 | ¥620 | ¥550🔽 | ¥600 | 5/6 |
| MU5137 (China Eastern 08:00→10:15) | ¥640 | ¥680 | ¥620 | ¥540🔽 | 5/13 |

🔽 = lowest cross-date price for that flight
🔥 Global lowest: MU5137 @ 5/13 ¥540

### Recommended Combinations

**Top pick ⭐ MU5137 @ 5/13 (¥540)**
> Global lowest; daytime morning flight, friendly with kids; ¥72 below this matrix's average.
[Book]({jumpUrl})

**Alt 1: CA1883 @ 5/6 (¥550)**
> Second-lowest; late departure means a full day of activities before flying.
[Book]({jumpUrl})

**Alt 2: CA1883 @ 4/22 (¥580)**
> Closest date; matches your historical preference for late-night direct flights.
[Book]({jumpUrl})

Each recommendation reason must cite at least one of: cross-date lowest, historical preference, persona match, time-window advantage.

2.5 Overriding Hard Constraints

If the user says things like "red-eye is OK" or "transfers are fine":

Override detected: persona 【亲子 / family】 defaults to no red-eye, but this turn you said "red-eye is OK".
Allowing it for this query. For future queries:
  🔄 One-time exception (recommended)
  🔁 Always accept → modify persona override, write to preferences.per_persona_overrides

Do not interrupt the current query flow — ask after delivering the recommendations.

History Recording

After the user settles on an option (confirms booking / abandons / only shortlists), append to assets/history.json:

{
  "ts": "2026-04-20T14:30:00+08:00",
  "persona_tag": "亲子",
  "origin": "北京",
  "origin_airport": "PEK",
  "destination": "上海",
  "destination_airport": "SHA",
  "dep_date": "2026-05-06",
  "transport_no": "CA1883",
  "marketing_carrier": "国航",
  "seat_class_name": "经济舱",
  "dep_time": "21:00",
  "arr_time": "23:20",
  "journey_type": 1,
  "price": 550,
  "result": "purchased",
  "sort_used": "price_asc",
  "overrode_constraints": [],
  "note": null
}

Rules:

  • result is required; values: purchased / abandoned / shortlisted (abandonments matter as much as purchases — they serve as negative signal).
  • Keep all historical records; append only, never overwrite.
  • Validate JSON before writing; if the existing file's records array is corrupt → back up, rebuild as empty array, and notify the user.

Output Conventions

  • Data must come from the flyai search-flight response: price, time windows, flight numbers, duration, etc. — never computed or fabricated.
  • Filter notice must come first: the first line of output always includes an "Applied 【X】 filter: Y" summary.
  • Recommendation reasons must be traceable: each reason must be grounded in data (price, history, persona, time-window); never invented.
  • Prices are labeled "from": e.g. from ¥580, indicating the lowest-cabin price, subject to actual purchase.
  • When the response contains jumpUrl: every recommendation must provide [Book]({jumpUrl}).
  • Empty / thin result handling: if qualifying results <3 on a long-haul international route, auto-fallback to connecting search per §1.6 and report the expansion in the header. Otherwise (domestic / short-haul, or fallback still empty) prompt: "No flights after 【X】 filter, relax? 🔓 clear filter / 🔁 change dates / ✈️ include transfers".
  • Branding: append "Data from fly.ai" at the end of every output.

Interaction Examples

Example 1: family persona, full two-stage flow

User: 带娃,这个月周五北京到上海,看看哪天便宜

Reply:
Detected 【亲子 / family】 trip; loaded defaults: no red-eye + transfer ≥ 60min.
Remaining Fridays this month: 4/24, 5/1 (holiday), 5/8, 5/15. Note 5/1 is the first day of Labor Day holiday and prices tend to be higher.
Last time on this route you picked 4/24 and 5/8 — carry over?

> User: all of them

Great, 4 dates. Pick a flight first? Querying Stage 1 on 4/24:

[Stage 1: top 3–5 output]

> User: CA1883 and MU5137

[Stage 2: 4×2=8 parallel calls, output matrix]

Example 2: directly locking a specific flight

User: CA1883 这周还有哪天便宜

Reply:
Detected a specified flight CA1883; skipping the discovery stage.
"This week" = 4/21 (Mon) – 4/27 (Sun), 7 days in total. Query all of them?

> User: weekdays only

OK, querying CA1883 for 4/21–4/25.

[Stage 2: 5 parallel calls, output single-flight price series]

Example 3: overriding a hard constraint

User: 带娃,但红眼也行,越便宜越好

Reply:
Override detected: 【亲子 / family】 defaults to no red-eye; allowing this turn per your request. I'll ask after the query whether to make it permanent.

[Run query, including red-eye flights]

You allowed red-eye just now. Going forward:
  🔄 Just this once (next time still reject)
  🔁 Always accept (write to preferences.per_persona_overrides.亲子.allow_redeye)

Troubleshooting

  • flyai search-flight method not found → upgrade: npm i -g @fly-ai/flyai-cli.
  • Response with status != 0 → show the message field to the user and suggest retrying or adjusting keywords.
  • Single-day call fails → mark the corresponding matrix cell as "—" and continue overall.
  • If --transport-no with two flight numbers causes the API to error → automatically fall back to "per-flight, per-day" serial calls.

Detailed Reference

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