Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add lttr/claude-marketplace/plugin install ccWrote 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/lttr/claude-marketplace/skill-creator)<a href="https://agentmods.dev/skills/lttr/claude-marketplace/skill-creator"><img src="https://agentmods.dev/badge/skills/lttr/claude-marketplace/skill-creator/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/lttr/claude-marketplace/skill-creator"><img src="https://agentmods.dev/badge/skills/lttr/claude-marketplace/skill-creator.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 | $0.00058 | $0.02191 |
| Opus 5 | $0.00029 | $0.01095 |
| Sonnet 5 | $0.00012 | $0.00438 |
| Haiku 4.5 | $0.00006 | $0.00219 |
Grade A, and why
skill-creator scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**List prerequisites.** If the skill relies on external programs/CLIs (jq, ffmpeg, a vendored binary, etc.), add a short **Prerequisites** section near the top listing them — with install hints when non-obvious. An unsta How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator
Official docs: https://code.claude.com/docs/en/skills.md. Fetch when unsure about frontmatter semantics, subagent forking, hook integration, or recent features.
Process
1. Gather requirements
Ask the user:
- What task/domain does the skill cover?
- What specific use cases should it handle?
- Does it need executable scripts or just instructions?
- Any reference materials to include?
If the user's description is already clear, skip straight to drafting.
2. Determine placement
Infer from context, ask only if ambiguous:
- Global (
~/.claude/skills/) - across all projects - Project (
<project>/.claude/skills/) - repo-specific - Plugin (
<plugin>/plugins/<name>/skills/) - distributed via marketplace
3. Assess complexity
Simple (just write the SKILL.md):
- Purely instructional (workflow, guidelines, domain knowledge)
- No supporting files needed
Full (skill with bundled resources):
- Needs scripts for deterministic/repeated operations
- Needs reference docs (schemas, API docs, large knowledge bases)
- Needs assets (templates, images, fonts)
4. Draft the skill
Simple path: Create the directory and write SKILL.md directly.
Full path:
- Plan supporting files (what scripts/references/assets are needed)
- Create the skill directory and subdirs
- Write supporting files first (may need user input for assets/docs)
- Write SKILL.md last, referencing the supporting files
5. Review with user
Present draft and iterate. Skills improve most after real usage.
Skill Structure
skill-name/
├── SKILL.md # Main instructions (required)
├── references/ # Docs loaded into context on demand (optional)
│ ├── api-reference.md
│ └── schema.md
├── scripts/ # Deterministic code (optional)
│ └── helper.py
└── assets/ # Files used in output (optional)
└── template.html
Reference supporting files from SKILL.md so Claude knows they exist:
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.
- 10d ago First seen · 188 lines · 58 tokens per session scan A 0a72f2259552
skill-creator is a skill published in the GitHub repository lttr/claude-marketplace (2 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 2,191 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows.
hook-factory
Generate production-ready Claude Code hooks with interactive Q&A, automated installation, and enhanced validation. Supports 10 templates across 7 event types for comprehensive workflow automation.
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
r3f-best-practices
React Three Fiber (R3F) and Poimandres ecosystem best practices. Use when writing, reviewing, or optimizing R3F code. Triggers on tasks involving @react-three/fiber, @react-three/drei, zustand, @react-three/postprocessing, @react-three/rapier, or leva.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
development
An index of programming guidance for Python, Go, Rust, TypeScript, Java, C++, and shell scripting.