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 AntonioBlago/peec-ai-skills --skill peec-agentgit clone --depth 1 https://github.com/AntonioBlago/peec-ai-skillsWrote 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/antonioblago/peec-ai-skills/peec-agent)<a href="https://agentmods.dev/skills/antonioblago/peec-ai-skills/peec-agent"><img src="https://agentmods.dev/badge/skills/antonioblago/peec-ai-skills/peec-agent/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/antonioblago/peec-ai-skills/peec-agent"><img src="https://agentmods.dev/badge/skills/antonioblago/peec-ai-skills/peec-agent.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 | $0.00099 | $0.02600 |
| Opus 5.5 | $0.00040 | $0.01040 |
| Sonnet 5.5 | $0.00020 | $0.00520 |
| Haiku 4.5 | $0.00010 | $0.00260 |
Grade A, and why
peec-agent 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 2mo 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Growth Agent
Role
Pick the single next move for a Peec AI project. One decision, one skill handoff, one measurable 4-week target. Nothing else.
Input
project_id— resolve viamcp__peec-ai__list_projectsif unknown- optional
focus— force a specific gap type (taxonomy|cluster|content|citation|learning)
Output
One markdown document matching the schema in §5, plus one appended entry in <project>/growth_loop/decisions_log.md. Nothing else is produced.
When to use
- Weekly 30-min ritual: "what is the one thing this week?"
- When multiple priorities compete and clarity is missing
- Quarterly strategy refresh
Do not use when:
- The answer is already known — call the target skill directly
- Peec project has <7 days of data — run
peec-setupfirst
The loop
┌─────────────────────────────────────────────────┐
│ │
│ 1. UNDERSTAND │
│ peec-setup (prompts + taxonomy) │
│ peec-content-intel (demand signals) │
│ ↓ │
│ 2. ANALYZE │
│ peec-cluster (zones) │
│ peec-content-intel (source intel) │
│ ↓ │
│ 3. DECIDE │
│ → THIS SKILL: one zone + one action │
│ ↓ │
│ 4. EXECUTE │
│ content-write (new content) │
│ peec-outreach (external citations) │
│ ↓ │
│ 5. LEARN │
│ peec-report │
│ ↓ │
└───────→ feedback into step 1 ────────────────────┘
One full cycle: 1 week for active projects, 4 weeks for maintenance.
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.
- 2mo ago First seen · 243 lines · 99 tokens per session scan A d28c0881cc32
peec-agent is a skill published in the GitHub repository AntonioBlago/peec-ai-skills (10 stars, last pushed 6mo ago), licensed MIT. It adds 99 tokens to every session and 2,600 once invoked, about $0.0004 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
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seo-content-collection-page
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seo-content-comparison-page
Spec, audit, competitor benchmark and build for the bottom-funnel pages that capture buyers at the decision moment: 'X vs Y', 'alternatives to X', 'best X for Y', the comparison hub, and audience or segment pages ('for agencies', 'for freelancers'). Runs four phases: the CMP spec with stable IDs on top of the common…
seo-content-product-page
Spec, audit, competitor benchmark and build for e-commerce product pages (PDPs), so they rank in Google and get recommended by the AI assistants that now link products directly. Input: a product page URL or a product brief (Shopify, WooCommerce, Magento, BigCommerce, PrestaShop, Wix, Webflow or custom). Runs four…
seo-content-service-page
Spec, audit, competitor benchmark and build for service pages and service landing pages (agencies, consultants, coaches, trades, clinics, law firms, SaaS), plus region and city pages. Input: a service, the business, a target area, the page URL if any. Runs four phases: the spec (SVC-01 to SVC-24 on top of the common C…
seo-local
Run spec, audit, competitor benchmark and build for local visibility, on the two assets a local business owns: the location page and the Google Business Profile, plus reviews and NAP citations. Spec: LOC, GBP, REV and CIT requirements with IDs. Audit: seoaudit.py and sectionaudit.py --type location on the page, a…