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 self-improvergit 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/self-improver)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/self-improver"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/self-improver/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/self-improver"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/self-improver.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 | $0.00087 | $0.02376 |
| Opus 5 | $0.00044 | $0.01188 |
| Sonnet 5 | $0.00017 | $0.00475 |
| Haiku 4.5 | $0.00009 | $0.00238 |
Grade A, and why
self-improver 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 7d 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 self-improver — 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Improver
Review affiliate campaign results, diagnose what worked and what didn't, and generate a prioritized improvement plan. Uses affiliate-specific diagnostic frameworks (offer-market fit, traffic-content match, funnel leak analysis) to identify root causes and actionable fixes.
Stage
S8: Meta — Most affiliates repeat the same mistakes because they never do structured retrospectives. Self-Improver closes the feedback loop: it takes your results, compares them to expectations, diagnoses gaps using affiliate-specific frameworks, and produces concrete actions that feed back into S1-S7 for the next iteration.
When to Use
- User has run a campaign and wants to understand results
- User's affiliate content isn't converting and wants to diagnose why
- User wants to compare actual vs expected results
- User says "what went wrong?", "why no conversions?", "how to improve?"
- User wants a structured retrospective on their affiliate efforts
- Chaining from S6.3 (performance-report) — analyze the data and plan improvements
Input Schema
campaign:
description: string # REQUIRED — what was done (e.g., "Published 3 blog reviews
# of AI video tools, shared on LinkedIn and Reddit")
duration: string # OPTIONAL — how long (e.g., "2 weeks", "1 month")
skills_used: string[] # OPTIONAL — which Affitor skills were used
channels: string[] # OPTIONAL — where content was distributed
results:
clicks: number # OPTIONAL — total clicks on affiliate links
conversions: number # OPTIONAL — total signups/purchases
revenue: number # OPTIONAL — total commission earned
traffic: number # OPTIONAL — total page views / impressions
feedback: string # OPTIONAL — qualitative feedback received
expectations:
expected_clicks: number # OPTIONAL — what was expected
expected_conversions: number # OPTIONAL
expected_revenue: number # OPTIONAL
benchmark: string # OPTIONAL — "industry average" or specific number
context:
niche: string # OPTIONAL — product category
experience: string # OPTIONAL — "first campaign" | "experienced"
budget: string # OPTIONAL — money spent (if any)
What ships with it
1 file 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.
- 7d ago First seen · 229 lines · 87 tokens per session scan A a087a51ae3e4
self-improver is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 87 tokens to every session and 2,376 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to self-improver, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
self-improver
Review affiliate campaign results and improve strategy. Triggers on: "review my results", "what went wrong", "how to improve conversions", "analyze my campaign", "affiliate retrospective", "why am I not converting", "improve my strategy", "what should I change", "campaign review", "optimize my approach", "learn from…
self-improver
Review affiliate campaign results and improve strategy. Triggers on: "review my results", "what went wrong", "how to improve conversions", "analyze my campaign", "affiliate retrospective", "why am I not converting", "improve my strategy", "what should I change", "campaign review", "optimize my approach", "learn from…
category-designer
Define a new category where your product wins by default. Reframe the buying decision. Triggers on: "create a category", "category design", "define my category", "category of one", "reframe the market", "position as category king", "new category", "category creation", "own a category", "category strategy"…
compliance-checker
Check affiliate content for FTC compliance and platform rules. Triggers on: "check my content for compliance", "FTC disclosure check", "is this legal", "review for compliance", "check affiliate disclosure", "am I FTC compliant", "audit my content", "compliance review", "legal check", "platform rules check", "check…
funnel-planner
Plan a complete affiliate funnel from research to revenue. Triggers on: "plan my affiliate funnel", "create a funnel strategy", "affiliate business plan", "how to start affiliate marketing", "full funnel roadmap", "plan from scratch", "week by week affiliate plan", "chain skills together", "build my funnel"…
skill-finder
Find the right Affitor skill for your goal. Triggers on: "which skill should I use", "find me a skill", "what skills are available", "help me choose a skill", "skill for SEO", "skill for email", "explore skills", "I'm new to Affitor", "what can Affitor do", "search skills", "skill for blog writing", "skill for landing…