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 ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool --skill answerfirstgit clone --depth 1 https://github.com/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-toolWrote 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/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/answerfirst)<a href="https://agentmods.dev/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/answerfirst"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/answerfirst/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/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/answerfirst"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/answerfirst.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 | $0.00020 | $0.00525 |
| Opus 5.5 | $0.00008 | $0.00210 |
| Sonnet 5.5 | $0.00004 | $0.00105 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
answerfirst 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- answerfirst — 88% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Answer-first rewrite
Turn sections that warm up slowly into ones that answer first, so an AI engine can lift them as they are.
When to use
- "Make this page answer-first", "Rewrite our intro so AI quotes it", "Why doesn't AI quote this page?"
- For a whole page, work section by section, the summary first.
What to read
get_draftwhen the person names a draft: its passages, and which ones AI quotes now (locked).list_promptsorget_fanoutsfor the page's topic: the questions each section should answer.- When a live page is named,
get_site_audit_summaryandlist_site_audit_issuesfor its latest audit: the direct-answer and bottom-line-up-front checks.
If the person pasted the text, work from it and read nothing else unless needed.
Steps
- Write a summary for the top of the page: two or three sentences that answer the page's main question, the way an AI Overview would.
- Under each H2, put a direct answer first: one or two sentences, 50 words or fewer, that answer the heading on their own. Detail, reasons and caveats come after.
- One question per section; its heading says the question or its answer.
- Define a term where it is first used, in the same sentence. Steps as a numbered list, options as a table.
- Keep every fact, figure and claim exactly as the source has it, and the brand's voice: change the order, not the personality. A passage AI quotes now stays word for word.
Output
For each section: Before, After, and one line on what changed. Then the full rewritten text in one block, ready to paste. When the person wants it kept, save it as a new draft with create_draft; the app asks them first when it should. In an agent's run nobody is there to ask: always save it with its tool, and the app holds it for approval where the agent's mode needs it.
Don't
- Don't add facts, figures or promises that weren't in the text.
- Don't shorten an answer until it is no longer true.
- Don't touch locked passages without saying so.
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.
- yesterday First seen · 44 lines · 20 tokens per session scan A fd95f94061c5
answerfirst is a skill published in the GitHub repository ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool (449 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 525 once invoked, about $0.0001 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 2026-11-05.
answerfirst compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| answerfirstai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool | Skill | 449 | yesterday | MIT | A | 20 | Claude Code, Codex |
| geo-platform-optimizerasale-ai/seo-geo-skill | Skill | 6 | 2mo ago | none | A | 34 | Claude Code |
| ansvisor-aeo-coach-standaloneansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 148 | Claude Code, Codex |
| geo-loopmverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 62 | Claude Code |
| content-scoringmverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 34 | Claude Code |
| competitive-analysismverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 29 | Claude Code |
| schema-generatormverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 35 | Claude Code |