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 gabrielmoreira/agent-skills-mirror --skill templategit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/template)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/template"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/template/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/gabrielmoreira/agent-skills-mirror/template"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/template.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 | $0.00036 | $0.01052 |
| Opus 5 | $0.00018 | $0.00526 |
| Sonnet 5 | $0.00007 | $0.00210 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
your-skill-name 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 6d 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.
This is a copy
100% identical to your-skill-name — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your Skill Name
What this skill does in 2-3 sentences. Focus on the outcome, not the process.
Stage
This skill belongs to Stage SX: StageName
When to Use
- Scenario 1
- Scenario 2
- Scenario 3
Input Schema
{
required_field: { # (required) Description
name: string # Example value
}
optional_field: string # (optional, default: "value") Description
}
Workflow
Step 1: Gather Context
What to check first. How to handle missing inputs.
Step 2: Execute Core Task
The main work the skill does.
Step 3: Format and Deliver
How to structure the output.
Output Schema
Other skills can consume these fields from conversation context:
{
primary_output: string # Main result for downstream chaining
secondary_output: string # Additional data for downstream skills
}
Output Format
## [Skill Name]: [Context]
### Section 1
[Main content]
### Section 2
[Supporting content]
Error Handling
- Missing required input: How to recover gracefully.
- External data unavailable: Fallback strategy.
- Edge case: How to handle unexpected scenarios.
Examples
Example 1: [realistic user prompt] → [step-by-step what the skill does] → [expected output summary]
Example 2: [different scenario] → [step-by-step] → [expected output summary]
Example 3: [edge case or beginner scenario] → [step-by-step] → [expected output summary]
Flywheel Connections
Feeds Into
[skill](S[X]) — [what data/output flows forward to this skill]
Fed By
[skill](S[X]) — [what data/output flows back from this skill]
Feedback Loop
- [analytics metric or data point that improves this skill's next run]
Quality Gate
Include this section for content-producing skills (S2, S3, S4, S5, S7). Remove for non-content skills.
Before delivering output, verify:
- Would I share this on MY personal social?
- Contains specific, surprising detail? (not generic)
- Respects reader's intelligence?
- Remarkable enough to share? (Purple Cow test)
- Irresistible offer framing? (if S4 offer skills ran)
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.
- 6d ago First seen · 164 lines · 36 tokens per session scan A 6db6e693e6aa
your-skill-name is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 1,052 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to your-skill-name, differing in 0 lines, and is treated as a copy.
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