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 dungnotnull/standalone-solar-deep-station-agent-skill --skill configgit clone --depth 1 https://github.com/dungnotnull/standalone-solar-deep-station-agent-skillWrote 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/dungnotnull/standalone-solar-deep-station-agent-skill/config)<a href="https://agentmods.dev/skills/dungnotnull/standalone-solar-deep-station-agent-skill/config"><img src="https://agentmods.dev/badge/skills/dungnotnull/standalone-solar-deep-station-agent-skill/config/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/dungnotnull/standalone-solar-deep-station-agent-skill/config"><img src="https://agentmods.dev/badge/skills/dungnotnull/standalone-solar-deep-station-agent-skill/config.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 | $0.00000 | $0.03290 |
| Opus 5 | $0.00000 | $0.01645 |
| Sonnet 5 | $0.00000 | $0.00658 |
| Haiku 4.5 | $0.00000 | $0.00329 |
Grade A, and why
config 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 10d 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 — 504 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL.md — Skill Registry Documentation
Overview
The standalone-solar-deep-station skill uses a modular, registry-based architecture that enables dynamic skill resolution, chain-of-thought routing, and graceful fallback. This document explains how skills are registered, resolved, executed, and validated.
Architecture Overview
User Query
│
▼
[Intent Router] → Detect Intent + Domain Tier
│
▼
[Skill Registry] → Resolve Best Agent
│
▼
[Agent Execution] → Pre-Hooks → Execute → Post-Hooks
│
▼
[Quality Gates] → Validate → Auto-Fix → Fallback
│
▼
[Output] → Result with Metadata
Skill Registration
Registration Process
Skills are registered through the SkillRegistry class:
from config.agent_registry import get_registry, BaseAgent, SkillMetadata
# Create agent metadata
metadata = SkillMetadata(
name="sub-core-analysis",
version="1.0.0",
description="Design standalone solar system for remote station",
author="standalone-solar-deep-station",
intent_types=[IntentType.ANALYSIS, IntentType.VALIDATION],
domain_tiers=[DomainTier.INTERMEDIATE, DomainTier.ADVANCED, DomainTier.EXPERT],
input_schema=get_schema("CoreAnalysisInput"),
output_schema=get_schema("CoreAnalysisOutput"),
dependencies=["sub-evidence-collector"],
requires_tools=["WebFetch", "Read", "Arithmetic"],
quality_gates=["G1", "G2", "G3", "G4"],
tags=["solar", "pv-sizing", "battery"]
)
# Register the agent
registry = get_registry()
registry.register(agent_instance)
Metadata Requirements
Every skill must provide:
| Field | Type | Required | Description |
|---|---|---|---|
name |
string | ✓ | Unique skill identifier (kebab-case) |
version |
string | ✓ | Semantic version |
description |
string | ✓ | One-line summary (used in triggering) |
author |
string | ✓ | Author or system identifier |
intent_types |
list | ✓ | Supported intents (see IntentType enum) |
domain_tiers |
list | ✓ | Supported complexity levels |
input_schema |
dict | ✓ | JSON Schema draft-07 for input validation |
output_schema |
dict | ✓ | JSON Schema draft-07 for output validation |
dependencies |
list | ✗ | Skills that must run first |
requires_tools |
list | ✗ | Tools required for execution |
quality_gates |
list | ✗ | Quality gates to apply |
tags |
list | ✗ | Search/metadata tags |
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.
- 10d ago First seen · 504 lines · 0 tokens per session scan A 703f3a8ec3f0
config is a skill published in the GitHub repository dungnotnull/standalone-solar-deep-station-agent-skill (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,290 tokens. 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.
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