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-competitorsgit 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-competitors)<a href="https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-competitors"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-competitors/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-competitors"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-competitors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00089 | $0.02417 |
| Opus 5 | $0.00044 | $0.01208 |
| Sonnet 5 | $0.00018 | $0.00483 |
| Haiku 4.5 | $0.00009 | $0.00242 |
Grade A, and why
suede-competitors 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 13d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Suede Competitor and Alternative Pages
Use this Suede comparison-page playbook to serve competitive search intent while keeping every product claim current, sourced, and fair.
Initial Assessment
Check for .agents/product-marketing.md (or .claude/product-marketing.md, or the legacy product-marketing-context.md) and read it if present — your value proposition, ICP, pricing model, and honest weaknesses decide which comparisons are even defensible, and they are usually already written down there.
Then work the intake list under Task-Specific Questions below; ask only what the context file did not already answer. Current competitor evidence — pricing, features, ratings — comes from suede-competitor-profiling, not from memory.
Page Formats
Format 1: [Competitor] Alternative (Singular)
Search intent: User is actively looking to switch from a specific competitor
URL pattern: /alternatives/[competitor] or /[competitor]-alternative
Target keywords: "[Competitor] alternative", "alternative to [Competitor]", "switch from [Competitor]"
Page structure:
- Why people look for alternatives (validate their pain)
- Summary: You as the alternative (quick positioning)
- Detailed comparison (features, service, pricing)
- Who should switch (and who shouldn't)
- Migration path
- Social proof from switchers
- CTA
Format 2: [Competitor] Alternatives (Plural)
Search intent: User is researching options, earlier in journey
URL pattern: /alternatives/[competitor]-alternatives
Target keywords: "[Competitor] alternatives", "best [Competitor] alternatives", "tools like [Competitor]"
Page structure:
- Why people look for alternatives (common pain points)
- What to look for in an alternative (criteria framework)
- List of alternatives (you first, but include real options)
- Comparison table (summary)
- Detailed breakdown of each alternative
- Recommendation by use case
- CTA
Important: Include 4-7 real alternatives. Being genuinely helpful builds trust and ranks better.
What ships with it
5 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.
- 13d ago First seen · 257 lines · 89 tokens per session scan A 9ff2d990c13b
suede-competitors is a skill published in the GitHub repository JasonColapietro/suede-creator-skills (135 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 2,417 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 2026-08-30.
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.