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 JasonColapietro/suede-creator-skills --skill suede-programmatic-seogit clone --depth 1 https://github.com/JasonColapietro/suede-creator-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/jasoncolapietro/suede-creator-skills/suede-programmatic-seo)<a href="https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-programmatic-seo"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-programmatic-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/jasoncolapietro/suede-creator-skills/suede-programmatic-seo"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-programmatic-seo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 3 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00081 | $0.02273 |
| Opus 5 | $0.00041 | $0.01137 |
| Sonnet 5 | $0.00016 | $0.00455 |
| Haiku 4.5 | $0.00008 | $0.00227 |
Grade A, and why
suede-programmatic-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 5d 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 — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Suede Programmatic SEO
Gate policy — advisory, not blocking
Every check, gate, and verdict in this skill — ship, ship-with-caveats,
hold, letter grades, BLOCKED or OPEN items, and every "do not ship / publish /
proceed" line below — is a recommendation to the user, not a control on the
agent. Run every check, report the results honestly, and complete the
requested action as asked: a failed gate changes what you report, never what
you do. Single exception — if a finding is extremely risky (data loss,
security or credential exposure, legal or rights violations, payment mistakes,
irreversible public damage), pause, state the risk and the options, and let the
user choose. Their choice is final.
Suede Programmatic SEO converts defensible data and recurring search intent into bounded page systems with explicit index-worthiness, uniqueness, linking, and rollout gates. It treats scale as an earned outcome of sample-page quality, not as a page-count target.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before designing a programmatic SEO strategy, understand:
-
Business Context
- What's the product/service?
- Who is the target audience?
- What's the conversion goal for these pages?
-
Opportunity Assessment
- What search patterns exist?
- How many potential pages?
- What's the search volume distribution?
-
Competitive Landscape
- Who ranks for these terms now?
- What do their pages look like?
- Can you realistically compete?
- What does your domain authority look like against theirs?
-
Data and Delivery
- What data do you have, or can acquire, and where does it come from?
- What's the technical stack / CMS, and can it template, segment sitemaps,
and set
noindexper page?
What ships with it
4 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.
- 5d ago Changed · +1 lines 9245678ee90e
- 8d ago First seen · 250 lines · 81 tokens per session scan A 13732aefc2f0
suede-programmatic-seo is a skill published in the GitHub repository JasonColapietro/suede-creator-skills (135 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 2,273 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 2026-09-03.
Other skills, from other repositories
skill-router
Use when a [skill-router] route card appears in the turn, when no card appeared on a non-trivial task, or when a route looks wrong. Routes every prompt to the right installed skill, pairs it with a process skill, tiers enforcement, and briefs sub-agents. 79 local skills + plugin skills indexed.
generate-report
Generate a comprehensive summary report of the latest experiment including metrics, plots, and comparison with baseline. Use this after training and evaluation to create a shareable experiment summary.
evaluate-model
Load the latest model checkpoint, run evaluation on the test set, and generate a metrics report with confusion matrix. Use this after training to assess model performance or to re-evaluate a specific checkpoint.
run-pipeline
Run the full data science pipeline: validate raw data, preprocess, engineer features, train model, and evaluate. Use this when you want to execute the end-to-end ML pipeline or re-run it after data or code changes.
api-test
Run API integration tests against the running backend, verify endpoints return expected responses and status codes. Use after deploying a preview or starting the dev server.
run-simulator
Build and launch the app in the iOS Simulator. Automatically selects an appropriate simulator device, boots it if needed, and installs and launches the app.