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 LamantinAI/mayak --skill add-verticalgit clone --depth 1 https://github.com/LamantinAI/mayakWrote 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/lamantinai/mayak/add-vertical)<a href="https://agentmods.dev/skills/lamantinai/mayak/add-vertical"><img src="https://agentmods.dev/badge/skills/lamantinai/mayak/add-vertical/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/lamantinai/mayak/add-vertical"><img src="https://agentmods.dev/badge/skills/lamantinai/mayak/add-vertical.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 346 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Agent Snooping · line 434 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00067 | $0.05136 |
| Opus 5.5 | $0.00027 | $0.02054 |
| Sonnet 5.5 | $0.00013 | $0.01027 |
| Haiku 4.5 | $0.00007 | $0.00514 |
Grade A, and why
add-vertical 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 24d 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 — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Vertical
This repository ships one worked vertical, reference_task, purely to be copied. Read its files
before writing your own — every constraint below is already satisfied in them.
The twelve files of a vertical
| # | File | What it holds |
|---|---|---|
| 1 | project/domain/<name>.py |
Frozen dataclass, business constants, and the field checks every writer meets (check_title, check_status). No framework imports. |
| 2 | project/domain/ports.py |
A Protocol per aggregate, speaking only in domain types. |
| 3 | project/infrastructure/persistence/orm_models.py |
The table, for Alembic's metadata only — nothing reads the ORM at runtime. |
| 4 | alembic/versions/<rev>_add_<name>s.py |
Autogenerated from #3, then read before it is trusted. |
| 5 | project/infrastructure/persistence/<name>_repository.py |
SQL, driver types, and the row → domain mapper. |
| 6 | project/application/<name>_service.py |
Orchestration and business rules. Depends on the Protocol, never on the repository. |
| 7 | project/application/<name>_dtos.py |
Request and response models — types only, the bounds are the domain's — plus from_domain. |
| 8 | project/infrastructure/api/endpoints/<name>s.py |
Router and handlers. Parse, delegate, convert. |
| 9 | tests/application/test_<name>_vertical.py |
What the service decides before writing — bounds, closed sets, an empty or null patch — over a stub of the port that stores nothing; and the wiring. No database. |
| 10 | tests/db/test_<name>_repository.py |
The queries against a real PostgreSQL (the db tier, inside make test): the whole row back, filter, order, page, the write condition, id spellings, the spans. |
| 11 | tests/db/test_<name>s_api.py |
HTTP in process over the real repository — status codes, a non-default filter, a staged race. |
| 12 | tests/functional/src/test_<name>s_api.py |
One smoke path through the built image, in make test-e2e. |
Every file here is type-checked — MYPY_TARGETS covers every test suite, so a hand-written fake
that drifts from the Protocol fails make gate-types even though pytest cannot see the drift.
Copying the reference vertical keeps you clear of it.
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.
- 24d ago Changed · +10 lines 38e5297bb0f3
- 27d ago Changed · +2 lines 4df74f883624
- 29d ago Changed · +12 lines 8dded86fc077
- 1mo ago Changed · +2 lines 1b59cf67d329
- 1mo ago Changed · -263 lines 63489941e8f0
- 1mo ago Changed · +51 lines 82bd53f9248c
- 1mo ago Changed · +43 lines 42d8cf1cff9b
- 1mo ago Changed · +58 lines e6ca68cca13d
- 1mo ago Changed · +35 lines 627ee25a5572
- 1mo ago First seen · 371 lines · 67 tokens per session scan A 6b8bb2bb175c
add-vertical is a skill published in the GitHub repository LamantinAI/mayak (5 stars, last pushed 23d ago), licensed MIT. It adds 67 tokens to every session and 5,136 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
pytest-suite
Write or extend the backend test suite following this project's conventions. Use when adding tests for a new service/route/repository, when coverage is missing, or when asked to test a feature. Knows the mocked-session + httpx AsyncClient setup so tests run with no database.
check
Run the full local quality gate (prek hooks + tox test matrix) before committing or opening a pull request. Use when asked to "check", "lint", "run CI locally", or verify a change is ready.
maintain-python-template
Extend or repair the Python Template repository while keeping its catalog, Copier questions, templates, generated references, and tests synchronized. Use for adding a framework, provider, database, interface, ML tool, deployment target, preset, compatibility rule, or generated-project capability.
validate-python-stack
Validate the Python Template repository or a project generated from it. Use before committing, publishing, deploying, or reviewing a stack to check catalog compilation, rendering, dependencies, formatting, tests, security workflows, skills, and representative runtime behavior.
project-workflow
Develop, test, and maintain this generated Python project using its recorded Copier choices and uv toolchain. Use for any code, dependency, configuration, documentation, or test change in this project, including simple libraries, CLIs, APIs, and layered AI or ML applications.
operate-ai-stack
Develop, test, and troubleshoot this generated AI or ML workload across its framework, model and embedding providers, retrieval stores, interfaces, training, serving, and observability layers. Use when changing prompts, tools, agents, RAG, MCP, inference, fine-tuning, evaluations, or provider integration.