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 skills add xuansenpa1/skillrevise --skill ortools-pickup-delivery-routinggit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/ortools-pickup-delivery-routing)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/ortools-pickup-delivery-routing"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/ortools-pickup-delivery-routing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/ortools-pickup-delivery-routing"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/ortools-pickup-delivery-routing.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00064 | $0.01630 |
| Opus 5 | $0.00032 | $0.00815 |
| Sonnet 5 | $0.00013 | $0.00326 |
| Haiku 4.5 | $0.00006 | $0.00163 |
Grade A, and why
ortools-pickup-delivery-routing 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 9d 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.
This is a copy
100% identical to ortools-pickup-delivery-routing — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pickup And Delivery Routing
Use this skill when each job has related pickup and dropoff or delivery events that must be served together. Apply it after the base routing model has a time dimension and before solving.
Implementation Flow
- Create one pickup node and one dropoff node per job.
- Add same-vehicle and precedence constraints for every pair.
- Apply the customer-facing time windows and service-time convention from the problem statement.
- Choose optional-service handling: independent pairs, or connected request sets.
- After solving, postprocess connected sets, rebuild route sequences if needed, and re-audit feasibility before counting served jobs or writing output.
Pair Structure
- Represent pickup and dropoff as separate service nodes connected by a shared job ID.
- Pickup demand is positive; dropoff demand is negative. Depot nodes have zero demand and zero service time.
- Add
routing.AddPickupAndDelivery(pickup_index, dropoff_index)for each pair. - Add explicit constraints for the actual business rules:
- same vehicle:
routing.VehicleVar(pickup_index) == routing.VehicleVar(dropoff_index) - pickup before dropoff:
time_dimension.CumulVar(pickup_index) <= time_dimension.CumulVar(dropoff_index)
- same vehicle:
Time Windows And Service Times
- Apply customer time windows to the service event promised to the customer. Appointment and dial-a-ride problems often constrain dropoff arrival; pickup windows can be derived by subtracting direct pickup-to-dropoff travel time from the dropoff window.
- If a problem statement gives explicit pickup and dropoff time-window formulas, implement those formulas directly. Service time belongs in the time transit from a node to the next node; do not change the stated window formula to compensate for service time unless the problem explicitly says to.
Pair Constraint Skeleton
Use this pattern after adding the time dimension. It enforces the paired-service relationship for each job. Add optional-service logic separately after deciding whether jobs are independent pairs or members of connected request sets.
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.
- 9d ago First seen · 129 lines · 64 tokens per session scan A cad3ae9d92bd
ortools-pickup-delivery-routing is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 7d ago), licensed MIT. It adds 64 tokens to every session and 1,630 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ortools-pickup-delivery-routing, differing in 0 lines, and is treated as a copy.
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