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 joaoguirunas/team-os --skill seo-localgit clone --depth 1 https://github.com/joaoguirunas/team-osWrote 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/joaoguirunas/team-os/seo-local)<a href="https://agentmods.dev/skills/joaoguirunas/team-os/seo-local"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/seo-local/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/joaoguirunas/team-os/seo-local"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/seo-local.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 | $0.00086 | $0.03939 |
| Opus 5.5 | $0.00034 | $0.01576 |
| Sonnet 5.5 | $0.00017 | $0.00788 |
| Haiku 4.5 | $0.00009 | $0.00394 |
Grade A, and why
seo-local 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.
This is a copy
97% identical to seo-local — 20 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local SEO Analysis (March 2026)
Key Statistics
| Metric | Value | Source |
|---|---|---|
| GBP signals share of local pack weight | 32% | Whitespark 2026 |
| Proximity share of ranking variance | 55.2% | Search Atlas ML study |
| Review signals share (up from 16%) | ~20% | Whitespark 2026 |
| Google searches seeking local info | 46% | Industry data |
| Mobile "near me" searches leading to visit in 24h | 76% | Google confirmed |
| ChatGPT/AI usage for local recommendations | 45% (up from 6%) | BrightLocal LCRS 2026 |
| ChatGPT local conversion rate | 15.9% | Seer Interactive |
| Google organic local conversion rate | 1.76% | Seer Interactive |
| Local pack ads growth (Jan 2025 to Jan 2026) | 1% to 22% | Sterling Sky |
Business Type Detection
Detect from page signals before analysis. This determines which checks apply.
Brick-and-Mortar
- Physical street address visible in page content or footer
- Google Maps embed with pin/directions
- "Visit us at", "Located at", "Come see us"
- Structured address in LocalBusiness schema
Service Area Business (SAB)
- No visible physical address
- Service area mentions: "serving [city/region]", "service area includes"
- "We come to you", "On-site service", "Mobile [service]"
areaServedin schema withoutaddress.streetAddress
Hybrid
- Both physical address AND service area language present
- "Visit our showroom" combined with "We also serve [areas]"
Impact on checks: SABs skip embedded map verification and physical address consistency. Brick-and-mortar gets full NAP + map checks.
Industry Vertical Detection
Detect from page signals and GBP category patterns. Routes to industry-specific checks from ../seo/references/local-schema-types.md.
| Vertical | Detection Signals |
|---|---|
| Restaurant | /menu, menu items, reservations, cuisine types, food ordering, "dine-in", "takeout" |
| Healthcare | insurance accepted, patients, appointments, NPI, medical terms, "Dr.", HIPAA notice |
| Legal | attorney, lawyer, practice areas, bar admission, case results, "free consultation" |
| Home Services | service area, emergency service, "free estimate", licensed/insured/bonded, "24/7" |
| Real Estate | listings, MLS, properties for sale/rent, agent bio, brokerage, "open house" |
| Automotive | inventory, VIN, test drive, dealership, service department, "new/used/certified" |
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.
- 20d ago Changed · -5 lines · -12 tokens per session 4547cd5adc66
- 25d ago First seen · 316 lines · 98 tokens per session scan A 8d4a8cadba37
seo-local is a skill published in the GitHub repository joaoguirunas/team-os (4 stars, last pushed 2d ago), licensed MIT. It adds 86 tokens to every session and 3,939 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to seo-local, differing in 20 lines, and is treated as a copy.
Other skills, from other repositories
jsonl-log-analyzer
Analyze large JSONL log files using schema-aware partitioned analysis. Discovers field schema, generates tailored jq extraction recipes, and orchestrates parallel chunk analysts with synthesis. Use when processing JSONL logs exceeding context limits, performing log analytics, or investigating incident logs.
orchestration-patterns
Apply proven orchestration patterns for agent teams including parallel specialists, pipelines, swarms, research+implementation, plan approval, and multi-file refactoring. Use when choosing a team structure, designing workflows, or implementing specific coordination patterns.
task-system
Manage shared task lists for agent teams including creating tasks, setting dependencies, claiming work, and tracking progress. Use when creating work items, building task pipelines, coordinating task ownership, or managing task dependencies.
spawn-backends
Configure how teammate agents run including in-process, tmux, and iTerm2 backends. Use when choosing a display mode, setting up split panes, troubleshooting backend issues, or configuring teammateMode.
error-handling
Debug and recover from agent team errors including common errors, hooks for quality gates, known limitations, and recovery strategies. Use when encountering team errors, enforcing quality gates with hooks, understanding limitations, or debugging agent issues.
messaging
Send messages between agents using SendMessage including direct messages, broadcasts, shutdown requests/responses, and plan approvals. Use when communicating between agents, understanding message formats, or handling structured protocol messages.