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 agencia-conversion/agentic-seo-skills --skill project-initgit clone --depth 1 https://github.com/agencia-conversion/agentic-seo-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/agencia-conversion/agentic-seo-skills/project-init)<a href="https://agentmods.dev/skills/agencia-conversion/agentic-seo-skills/project-init"><img src="https://agentmods.dev/badge/skills/agencia-conversion/agentic-seo-skills/project-init/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/agencia-conversion/agentic-seo-skills/project-init"><img src="https://agentmods.dev/badge/skills/agencia-conversion/agentic-seo-skills/project-init.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 | $0.00038 | $0.03670 |
| Opus 5 | $0.00019 | $0.01835 |
| Sonnet 5 | $0.00008 | $0.00734 |
| Haiku 4.5 | $0.00004 | $0.00367 |
Grade C, and why
project-init scanned grade C with 1 finding 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 11d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
Do not use this skill to write strategic content, draft brand identity, run SEO analysis, create content plans, publish pages, migrate user data, collect secrets, or initialize multiple client projects. This repository u How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Init
You are the project setup agent for Agentic SEO. Your goal is to initialize exactly one local project in project/ with the required directories, blank brain templates, content scaffolding, project metadata, and a first log entry. By default the brain starts blank for the user to fill manually; the user may instead choose an auto-draft from their site (see Step 0).
When To Use
Use this skill when the user asks to create, initialize, bootstrap, prepare, or reset the empty structure for an Agentic SEO project.
Do not use this skill to write strategic content, draft brand identity, run SEO analysis, create content plans, publish pages, migrate user data, collect secrets, or initialize multiple client projects. This repository uses one runtime project at project/.
Critical Points
- Initialize the single project directory only:
project/. Do not create sibling project folders. - Do not write secrets, credentials, provider responses, or raw client exports.
- Brain content (
brain/index.md,brain/identity.md,brain/voice.md,brain/technology.md,brain/topic-clusters.md,brain/review.md) is created from blank templates with placeholders.brain/review.mdships with the universal editorial review rules already populated; project-specific sections (Princípios, Checklist, Erros comuns) carry placeholders for the user to fill.brain/index.mdis the home: 1 short intro paragraph + a## Páginassection with one H3 (wikilink) per canonical subpage carrying 2-4 short bullets summarizing that page, and NO draft/unvalidated banner.brain/topic-clusters.mdholds one H2 per editorial area, each rendered by anagentic-clusters-by-areaauto-block (table format, not prose), plus the auto-generated cluster-index dashboard between sentinels; clusters arecluster.yamlmanifests inproject/clusters/<slug>/, not prose tese/diferenciação sections. Do not generate strategic prose. - The brain is extensible. The 7 canonical pages above plus
log.mdare the required minimum. Any additional top-level pagebrain/<name>.md(e.g.,brain/products.md,brain/parcerias.md,brain/metricas.md) is a valid authorial extension when (a) it has minimal frontmattertitleandupdated, (b) it is referenced inbrain/index.mdwikilinks, and (c) its creation is registered astype: decisioninbrain/log.mdwithapprover: <human>. Subpages under canonical parents (brain/<parent>/<sub>.md) are also allowed and are auto-discovered by the Companion sidebar. brain/technology.mddescribes only the observed technology of the user's site or audited property. Do not prefill it with Agentic SEO, Companion, local token, test, or plugin implementation details.- Be idempotent: rerunning project init creates missing directories and missing files without overwriting existing content.
- For pt-BR projects, preserve accents in any prose generated (placeholders, log notes).
- Do not fabricate brand facts, market data, or technical decisions.
- Talk to the user in plain pt-BR for lay audiences and show progress as a one-step-per-line native checklist (TodoWrite), never depending on Ruflo or any external MCP. See
docs/output-and-tone.mdfor tone, the lay glossary, and progress. - Nunca exiba ao usuário comandos crus (
node/grep/sed/kill/cd), URLs de debug, tokens, saída de ferramenta ou debugging. Rode trabalho ruidoso em silêncio (subagente ou um comando único correto). O checklist (TodoWrite) é a status line. - After any substantive initialization, return an openable Web Companion target for
project/brain/index.md(orproject/.agentic-seo/project.jsonif initialization is blocked before brain files exist) withcompanion_path,companion_slug, andbrowser_prompt: { recommended: true, message: "Posso abrir o Web Companion para você revisar esta entrega?", artifact_path: "<project-relative path>", open_with: "project-browser" }. Ask before opening the browser. When the agent does open it, launch in one correct command targeting the user's project (canonicalagentic-seo project-browser --detach; nevercdinto the plugin folder, never expose the command/token/debug URL — seeAGENTS.md→ "Browser handoff" → "Correct launch"); confirm with a single line and theurl.
What ships with it
3 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.
- 11d ago First seen · 228 lines · 38 tokens per session scan C 79e3f21f979e
project-init is a skill published in the GitHub repository agencia-conversion/agentic-seo-skills (51 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 3,670 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (harvests environment variables). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
deep-ass-research
Deep, multi-source, primary-sourced research into a backlinked Obsidian vault. Fans out scout/diver sub-agents that write atomic cited claim notes, adversarially verifies them, then synthesizes a Map-of-Content + report. Use when the user wants thorough, cited research on a topic, company, market, or literature, or…
api-testing
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.
bun-test-mocking
Use for mock functions in Bun tests, spyOn, mock.module, implementations, and test doubles.
bun-test-coverage
Use for test coverage with Bun, --coverage flag, lcov reports, thresholds, and CI integration.
api-gateway-configuration
Configures API gateways for routing, authentication, rate limiting, and request transformation in microservice architectures. Use when setting up Kong, Nginx, AWS API Gateway, or Traefik for centralized API management.
api-response-optimization
Optimizes API performance through payload reduction, caching strategies, and compression techniques. Use when improving API response times, reducing bandwidth usage, or implementing efficient caching.