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 Zhang-Henry/CoEvoSkills --skill evo-civ6-adjacencygit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-civ6-adjacency)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-civ6-adjacency"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-civ6-adjacency/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/zhang-henry/coevoskills/evo-civ6-adjacency"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-civ6-adjacency.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 | $0.00071 | $0.00790 |
| Opus 5 | $0.00036 | $0.00395 |
| Sonnet 5 | $0.00014 | $0.00158 |
| Haiku 4.5 | $0.00007 | $0.00079 |
Grade A, and why
evo-civ6-adjacency 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 12d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Civ6 District Adjacency Bonus Optimizer
Overview
Solves Civilization 6 district placement optimization problems. Given a map file and scenario parameters, finds optimal city center and district placements to maximize total adjacency bonuses.
Quick Start
import sys
sys.path.insert(0, '/app/environment/skills/evo-civ6-adjacency/scripts')
from main import solve_scenario, validate_output
# Caller must supply runtime paths from the task instruction
scenario_path = '/data/scenario_3/scenario.json' # adapt per task
output_path = '/output/scenario_3.json' # adapt per task
solve_scenario(scenario_path, output_path)
validate_output(output_path, scenario_path)
Architecture
Scripts
- hex_utils.py: Hex grid math (odd-r offset neighbors, cube distance)
- map_reader.py: SQLite reader for .Civ6Map files, terrain/feature/river helpers, runtime resource classification (strategic/luxury/bonus derived from name patterns)
- placement.py: District placement validation;
build_district_categories()derives specialty/non-specialty/no-bonus sets from the public Gathering Storm ruleset - adjacency.py: Per-district adjacency bonus calculation with flooring rules
- optimizer.py: Greedy optimizer that scores candidate placements; derives district priorities and search breadth from categories and map size at runtime
- main.py: End-to-end entry point (requires scenario_path and output_path arguments)
- validator.py: Solution validation
Key Design Decisions
- Odd-r offset coordinates: Even rows use different neighbor offsets than odd rows
- River detection: Must check both own flags AND complementary neighbor flags
- Feature destruction: Placing districts (except CC) destroys forests/jungles/marshes
- Minor bonus flooring: Each source type floored independently
- Non-specialty districts are powerful: Aqueduct/Dam/Neighborhood boost neighbors for free
- Runtime resource classification: Resources classified as strategic/luxury/bonus from name patterns at runtime rather than hardcoded lists
- Runtime-derived priorities: District search priorities derived from categories; search breadth scales with map size
- Greedy search: Iteratively adds best (district, position) pair; supports multiple neighborhoods via indexed keys
What ships with it
8 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.
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.
- 12d ago First seen · 74 lines · 71 tokens per session scan A 3b543d0ae414
evo-civ6-adjacency is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 22d ago), licensed Apache-2.0. It adds 71 tokens to every session and 790 once invoked, about $0.0004 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 2026-08-30.
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