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 mblode/agent-skills --skill seogit clone --depth 1 https://github.com/mblode/agent-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/mblode/agent-skills/seo)<a href="https://agentmods.dev/skills/mblode/agent-skills/seo"><img src="https://agentmods.dev/badge/skills/mblode/agent-skills/seo/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/mblode/agent-skills/seo"><img src="https://agentmods.dev/badge/skills/mblode/agent-skills/seo.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 | $0.00076 | $0.01496 |
| Opus 5 | $0.00038 | $0.00748 |
| Sonnet 5 | $0.00015 | $0.00299 |
| Haiku 4.5 | $0.00008 | $0.00150 |
Grade A, and why
seo 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 today.
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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO
- IS: one entry point for search visibility: evidence-led audits, implementation, demand research, writer briefs, and performance measurement across search and answer engines.
- IS NOT: writing the article (
ghostwriter), standalone marketing copy (copywriting), visual redesign (ui-design), or tenant infrastructure (multi-tenant-architecture). Fix SEO copy and markup when they are part of the requested implementation.
Route the task
| Request | Load | Deliverable |
|---|---|---|
| Audit a site, diagnose indexing, review a migration | references/audit.md and references/validation-evidence.md |
Prioritized findings with URLs, observed evidence, impact, and correction |
| Fix or implement SEO | Audit references, then applicable implementation references below | Code changes, scoped checks, and served-page evidence for the changed behavior |
| Research demand, choose a target, brief a page | references/research-protocol.md; references/brief-template.md for a brief |
Sourced demand table and decision, or a durable writer brief |
| Explain traffic movement, measure AI visibility, monitor SEO | references/monitoring.md |
Property-scoped diagnosis or configured monitoring with explicit data gaps |
For a combined request, reuse one property and URL inventory across modes. An audit request produces findings; a request to fix them proceeds through implementation and verification within the user's authorized scope. A research-only request does not require crawling every URL or changing code.
Establish the evidence boundary
Identify the exact public host, URL-prefix or domain property, production environment, project/subpath, audience, and business outcome. On a shared domain, filter each project's path separately. In analytics, verify hostname, path, conversion event and attribution window before interpreting a number.
Discover connected tools and existing project bindings first. Prefer the established reporting source, then an available equivalent, then a signed-in browser. No vendor is required. Ownership verification, API consent and a successful scoped query are separate states. An export for a neighboring property is not a fallback.
What ships with it
12 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.
- evals/evals.json 5.8 KB
- references/answer-engines.md 3.4 KB
- references/audit.md 3.5 KB
- references/brief-template.md 2.4 KB
- references/indexing-policy.md 2.1 KB
- references/internationalisation.md 1.5 KB
- references/monitoring.md 3.8 KB
- references/nextjs-implementation.md 5.5 KB
- references/research-protocol.md 3.6 KB
- references/sources.md 2.5 KB
- references/technical-hardening.md 1.6 KB
- references/validation-evidence.md 2.3 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.
- today First seen · 81 lines · 76 tokens per session scan A 394c2a39348d
seo is a skill published in the GitHub repository mblode/agent-skills (106 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 1,496 once invoked, about $0.0004 per session on Opus 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 2026-09-08.
Other skills, from other repositories
spawn-reviewers
Spawn and collect the reviewer fleet at stage20spawnreviewers. Consumes spawn.json.spec (the authoritative spawn spec from derive-spawn-spec / derive-static-spec), resolves GRAPHPROJECT, builds per-agent prompts from the per-agent template + role suffixes (Bug Hunter A/B, Unified Auditor, Domain Critics, Impact…
design-inventory
Use to run the Claude Design to ClosedLoop pipeline against the current web-ui. Stage A inventories a design export zip into schema-validated findings (typed design units - screens, regions like nav bars, standalone components like a chat dialog; UX and behavioral changes; Storybook component reuse mapping; token…
verify-findings
Dispatch and collect the finding-verifier fleet at stage23verifyfindings (PLN-722). Reads verifymanifest.json (written by stage22bverifyprepare), spawns one falsify-oriented verifier Task per toverify[] entry with mode-specific Task scheduling (GitHub mode dispatches verifiers synchronously; local mode uses parallel…
artifact-type-tailored-context
Compresses artifacts for judge evaluation. Reads a single raw artifact, applies tiered summarization within a token budget, and returns compacted content with metadata. Isolation via forked context prevents pollution of agent context.
codex-review
Run Codex to review a plan file and return structured feedback with a verdict. Triggers on: debate loop Codex review rounds. Returns VERDICT:APPROVED or VERDICT:NEEDSCHANGES plus CODEXSESSION token.
learning-quality
Structured format for capturing high-quality learnings during ClosedLoop runs.