Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/deepskyai/agent-tools/flight-ops-calculatorsnpx skills add deepskyai/agent-tools --skill flight-ops-calculatorsgit clone --depth 1 https://github.com/deepskyai/agent-toolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/deepskyai/agent-tools/flight-ops-calculators)<a href="https://agentmods.dev/skills/deepskyai/agent-tools/flight-ops-calculators"><img src="https://agentmods.dev/badge/skills/deepskyai/agent-tools/flight-ops-calculators.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00305 | $0.02350 |
| Opus 5 | $0.00152 | $0.01175 |
| Sonnet 5 | $0.00061 | $0.00470 |
| Haiku 4.5 | $0.00030 | $0.00235 |
Grade A, and why
flight-ops-calculators scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flight Ops Calculators
Ten deterministic command-line tools in scripts/. All JSON-by-default, all
with --pretty for humans, all pure Python stdlib (no deps, no network, no
API keys). Run any with --help for usage.
scripts/
├── gradient.py climb/descent geometry solver
├── fuel_uplift.py Jet A-1 uplift reconciliation (3% rule)
├── wind_components.py crosswind / headwind
├── altitude.py PA / DA / ISA-dev
├── airspeed.py CAS / TAS / Mach
├── pet_psr.py Point of Equal Time & Point of Safe Return
├── descent.py Top-of-Descent (3× rule + tax)
├── weight_balance.py W&B + CG + %MAC
├── etops.py EDTO / ETOPS diversion radius
└── holding.py direct / parallel / teardrop entry
tests/
└── test_all.py 34 zero-dep assertions; `python3 tests/test_all.py`
See references/formulas.md for derivations, constants, and edge cases.
Run the test suite any time you edit a script: python3 tests/test_all.py.
1. gradient.py — climb/descent solver
Eight variables — distance_nm, time_min, gs_kt, altitude_ft,
rate_fpm, angle_deg, gradient_pct, gradient_ft_per_nm — and six
relationships. Supply any sufficient subset (typically 3 values), solves for
the rest. Sign convention: + climb, − descent for altitude, rate, angle, and
gradient.
Triggers: "climb gradient", "ROC required", "3-to-1 descent", "TOD distance", "angle vs %", "ft/NM", obstacle clearance, any 3 of the variables above.
# Required gradient to clear 1500 ft in 5 NM at 140 kt
python3 scripts/gradient.py --distance-nm 5 --altitude-ft 1500 --gs-kt 140 --pretty
# 3° descent from FL100 at GS 250 — how far out is TOD, what's the ROD?
python3 scripts/gradient.py --altitude-ft -10000 --angle-deg -3 --gs-kt 250 --pretty
# ROC for 5% gradient at GS 180
python3 scripts/gradient.py --gradient-pct 5 --gs-kt 180 --pretty
2. fuel_uplift.py — Jet A-1 uplift reconciliation
Compares mass ordered vs mass actually delivered (volume × SG × temp correction), flags >3% deltas (the Jet A-1 SG-band rule).
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/formulas.md 8.2 KB
- scripts/airspeed.py 4.5 KB runs code
- scripts/altitude.py 3.6 KB runs code
- scripts/descent.py 4.6 KB runs code
- scripts/etops.py 3.0 KB runs code
- scripts/fuel_uplift.py 6.6 KB runs code
- scripts/gradient.py 8.5 KB runs code
- scripts/holding.py 4.0 KB runs code
- scripts/pet_psr.py 4.4 KB runs code
- scripts/weight_balance.py 5.7 KB runs code
- scripts/wind_components.py 3.4 KB runs code
- tests/test_all.py 14 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 202 lines · 305 tokens per session scan A cc01b0e87e93
flight-ops-calculators is a skill published in the GitHub repository deepskyai/agent-tools (1 stars, last pushed 1mo ago), licensed MIT. It adds 305 tokens to every session and 2,350 once invoked, about $0.0015 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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