SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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 benchflow-ai/skillsbench --skill ortools-routing-modelinggit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/benchflow-ai/skillsbench/ortools-routing-modeling)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/ortools-routing-modeling"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/ortools-routing-modeling/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/benchflow-ai/skillsbench/ortools-routing-modeling"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/ortools-routing-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.02350 |
| Opus 5 | $0.00021 | $0.01175 |
| Sonnet 5 | $0.00008 | $0.00470 |
| Haiku 4.5 | $0.00004 | $0.00235 |
Grade A, and why
ortools-routing-modeling 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ortools-routing-modeling — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OR-Tools Routing Modeling
Use this skill for vehicle-routing models built with ortools.constraint_solver.pywrapcp.RoutingModel.
Modeling Flow
- Normalize integer data and map external nodes to routing-manager nodes.
- Build transit, cost, and demand matrices or vectors before registering callbacks.
- Add time and capacity dimensions, including vehicle start/end ranges and span limits.
- Add problem-specific visits, time windows, optional-node penalties, and pairing constraints.
- Solve with an internal time limit, extract ordered routes, then audit them independently before reporting.
Data And Indexing
- Convert travel times, service times, demands, and time bounds to integers before registering callbacks or transit matrices. Avoid floats and
NaN; OR-Tools can silently treat bad values as usable arcs. - Assert that matrix dimensions, node counts, vehicle counts, and declared record counts agree before building the model. Shape mistakes often produce plausible but meaningless routes.
- Keep a clear distinction between external node IDs, routing manager node IDs, and internal routing indices. Convert with
manager.NodeToIndex(node)andmanager.IndexToNode(index). - When vehicles need distinct starts or ends but the input has shared depots, copy the depot into one internal start node and one internal end node per vehicle. Prefer these internal depot copies over reusing the same shared depot node for every vehicle, then map the copies back to the shared external depot IDs when reporting.
- A common cloned-depot layout is: solver job nodes first, then one start depot per vehicle, then one end depot per vehicle. External shared depot IDs can be stripped from the job matrix and restored only when reporting.
- Treat negative, missing, or sentinel travel times as invalid arcs. Either forbid them with explicit constraints or give them a prohibitive transit cost and reject any final route that uses them. Choose invalid-arc sentinels large enough to dominate feasible legs, but small enough to avoid integer overflow when service times and route spans are added.
- For static integer data, prefer precomputed
RegisterTransitMatrixandRegisterUnaryTransitVectorcalls over Python callbacks. Routing callbacks are called very often during local search and can consume solve time on large instances.
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 · 147 lines · 42 tokens per session scan A c563c6cdd94a
ortools-routing-modeling is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 2,350 once invoked, about $0.0002 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 2026-09-03.
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