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.
git clone --depth 1 https://github.com/athola/skrillsWrote 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/commands/athola/skrills/suggest-skills)<a href="https://agentmods.dev/commands/athola/skrills/suggest-skills"><img src="https://agentmods.dev/badge/commands/athola/skrills/suggest-skills/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/commands/athola/skrills/suggest-skills"><img src="https://agentmods.dev/badge/commands/athola/skrills/suggest-skills.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 | $0.00017 | $0.00273 |
| Opus 5 | $0.00009 | $0.00137 |
| Sonnet 5 | $0.00003 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
suggest-skills 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 11d 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.
What it actually says
Suggest Skills
Get suggestions for new skills to create using the skrills MCP server.
Use the mcp__plugin_skrills_skrills__suggest-new-skills tool with:
project_dir: Project directory for context analysisfocus_areas: Specific areas to focus on (e.g., testing, deployment)
Parse $ARGUMENTS for:
--focus <area>or-f <area>: Focus on specific area (can be repeated)--project-dir <path>or-p <path>: Project to analyze
Analyze the current project context and identify:
- Missing skills based on project technologies
- Gaps in workflow coverage
- Skills that similar projects typically have
Report suggestions including:
- Suggested skill name and purpose
- Why this skill would be useful
- Estimated complexity
- Similar existing skills that could be adapted
Handle errors:
- If project directory invalid: Use current directory or prompt for path
- If no context available: Provide generic suggestions based on focus area
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.
- 11d ago First seen · 33 lines · 17 tokens per session scan A 4da89bacabfd
suggest-skills is a command published in the GitHub repository athola/skrills (69 stars, last pushed 7d ago), licensed MIT. It adds 17 tokens to every session and 273 once invoked, about $0.0001 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 commands, from other repositories
send
Send a message to a running agent session. Use this to correct or direct a live agent mid-stream without killing and respawning it.
ship-an-mcp-server
Workflow recipe — make your product agent-usable by chaining 4 skills, spec to pricing.
rescue-an-account
Workflow recipe — diagnose an at-risk customer and build the full save play through to renewal by chaining 4 skills.
prompt-optimizer
Analyze and rewrite a prompt to maximize clarity, specificity, and output quality.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.