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 manishiitg/coding-agent-loop --skill seo-intelligencegit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/seo-intelligence)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/seo-intelligence"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/seo-intelligence/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/manishiitg/coding-agent-loop/seo-intelligence"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/seo-intelligence.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 | $0.00022 | $0.00755 |
| Opus 5.5 | $0.00009 | $0.00302 |
| Sonnet 5.5 | $0.00004 | $0.00151 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
seo-intelligence 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 20d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO Intelligence
Outcome
Produce a validated technical issue list and buyer-question map for an approved site. The first outcome is an owner-reviewed action.
When to use
Use for two-Crew search review, including a new site without Search Console history. Reuse Growth Data Foundation when available; otherwise mark demand and ranking unknown. Website Growth Loop handles publication and measurement.
Discovery and user direction
Inspect existing Crews, access and source coverage. Propose distinct SEO Analyst and Search Opportunity Mapper bindings, boundaries, validators, a manual case and owner review. Record the owner's direction. Installation does not approve execution.
Required inputs
Confirm canonical site, approved host/page scope, locale, device, offer, buyer, market, one sourced buyer question, crawl limits and page-change owner. Record an authorized Search Console property and comparable-window policy when available; otherwise record a baseline-first choice. Competitor and rank-tracker sources are optional.
Plan and AgentWorks tools
SEO Analyst saves seo-issue-list/v1 at the Crew step's path. Builder runs the blocking issue validator before Search Opportunity Mapper reads that exact artifact. The mapper combines it with buyer-question and page evidence, then saves seo-opportunity-list/v1. Builder validates this second file before reporting or creating an action. Ask Builder to repair a missing output path or validator. Prove one manual run before proposing paused recurrence. Page edits and publication need separate approval.
Knowledge and persistence
Store site and metric policy, Crew IDs, artifact paths, source revisions, validator results, owner decisions and stable issue/opportunity IDs. Retain the action ledger across runs. Re-read changed pages and buyer sources before reopening a case. Keep observed issue, proposed update, approved edit, verified publication and measured result as separate states.
Validation and reporting
What ships with it
10 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.
- examples/invalid-seo-opportunity-list.json 1.4 KB
- examples/seo-issue-list.json 1.1 KB
- examples/seo-opportunity-list.json 1.5 KB
- examples/seo-opportunity.json 1.1 KB
- playbook.json 5.4 KB
- references/seo-intelligence-workflow.md 2.8 KB
- references/team-and-handoffs.md 2.9 KB
- scripts/test_validate_handoff.py 3.6 KB runs code
- scripts/validate_handoff.py 11 KB runs code
- SETUP.json 3.5 KB
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.
- 20d ago Changed · -20 tokens per session 08d736e4b9bb
- 1mo ago First seen · 51 lines · 42 tokens per session scan A a880ac88d56f
seo-intelligence is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 22 tokens to every session and 755 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 2026-09-15.
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