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/docxology/template/infrastructure-modulenpx skills add docxology/template --skill infrastructure-modulegit clone --depth 1 https://github.com/docxology/templateWhat 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 | $0.00069 | $0.00546 |
| Opus 5 | $0.00034 | $0.00273 |
| Sonnet 5 | $0.00014 | $0.00109 |
| Haiku 4.5 | $0.00007 | $0.00055 |
Grade A, and why
template-infrastructure-module 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 2d 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.
What it actually says
Infrastructure module
Natural invoke
- "Add infrastructure/foo/ package with CLI and tests"
- "Extend infrastructure/validation with a new gate"
- "New generic utility reusable across projects"
Inputs to confirm
- Module name — under
infrastructure/<package>/. - Public API — functions/classes to export in
__init__.pyand__all__.
Workflow
-
Layout —
__init__.py, core logic module(s), optionalcli.py,AGENTS.md,README.md,SKILL.mdwith YAML frontmatter. -
Implement — generic (no project-specific paths hard-coded); type hints;
TemplateErrorhierarchy. -
Tests —
tests/infra_tests/<package>/; no mocks; ≥60% oninfrastructure/. -
Exports — re-exporting
__init__.pymust declare__all__(MED5). -
Register skill —
uv run python -m infrastructure.skills writeafter addingSKILL.md. -
Wire docs — update
infrastructure/AGENTS.mdmodule map if significant.
Deliverables
- Package tree + test path
- Coverage snippet from pytest
Verification commands
uv run pytest tests/infra_tests/<area>/ -v --cov=infrastructure --cov-fail-under=60
uv run python -m infrastructure.skills check
uv run python -m infrastructure.skills check --all-exports
When NOT to use
- Project-specific domain code → code-development in
projects/*/src/
References
infrastructure/AGENTS.mddocs/rules/api_design.md—__all__for re-exporters
What ships with it
2 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.
- 2d ago First seen · 69 lines · 69 tokens per session scan A b1fe6a4f4366
template-infrastructure-module is a skill published in the GitHub repository docxology/template (19 stars, last pushed 2d ago), licensed Apache-2.0. It adds 69 tokens to every session and 546 once invoked, about $0.0003 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.
Other skills, from other repositories
exa-search
Use Exa MCP for current web, code/docs, company, people, and page-fetch research. Prefer current hosted tool schemas and note deprecated tools.
ontoly-software-graph
Use Ontoly's deterministic Software Graph and MCP capabilities for repository architecture, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source search.
product-decision-agent
中文产品决策 Agent。用于中国大陆互联网产品、运营、增长、商业化、数据、项目推进和组织协作场景：产品规划、需求分析、PRD、需求优先级、排期、版本规划、Roadmap、MVP、灰度、上线、迭代、增长停滞、拉新、投放、渠道、裂变、CAC、LTV、ROI、留存、转化、DAU/MAU、GMV、漏斗、社区运营、内容供给、创作者、用户运营、活动运营、私域、会员、定价、指标异常、数据口径、埋点、A/B…
kimi-webbridge
Kimi WebBridge lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real…
telegram-patterns
Telegram-specific patterns and Telethon library usage.
async-python-patterns
When writing Python asyncio code — picking between gather / TaskGroup / wait, structured concurrency, timeouts, cancellation, sync-bridging — decision framework only, cookbook externalized.