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 agentmods add skills/matrixfounder/agentic-development/skill-creatornpx skills add MatrixFounder/Agentic-development --skill skill-creatorgit clone --depth 1 https://github.com/MatrixFounder/Agentic-developmentWhat 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 | $0.00045 | $0.05098 |
| Opus 5 | $0.00023 | $0.02549 |
| Sonnet 5 | $0.00009 | $0.01020 |
| Haiku 4.5 | $0.00005 | $0.00510 |
Grade A, and why
skill-creator 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 2d 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 — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator Guide
This skill provides the authoritative standard for creating and iteratively improving Agent Skills. It combines the Anthropic Skills Standard with our local architecture rules.
Core loop: Draft skill → Write test cases → Run evals (with-skill + baseline) → Review with user → Improve → Repeat.
Your job is to figure out where the user is in this process and help them progress. Maybe they want to create a skill from scratch — help narrow intent, write a draft, create tests, run them, iterate. Maybe they already have a draft — go straight to eval/iterate. Be flexible.
Red Flags (Anti-Rationalization)
STOP and READ THIS if you are thinking:
- "I'll skip the eval step, the skill looks fine" → WRONG. Run evals — untested skills fail silently in production.
- "I can write the whole skill without talking to the user" → WRONG. Capture Intent first — assumptions cause rewrites.
- "The description is descriptive enough" → WRONG. CSO triggers are mechanical. Follow the schema.
- "This skill is too simple for a script" → WRONG. If logic > 5 lines, text instructions fail 30% of the time. Use a script.
- "I'll skip the viewer and evaluate outputs myself" → WRONG. Generate the eval viewer BEFORE evaluating — get results in front of the human ASAP.
Purpose
Enable agents to create, test, and iteratively improve Agent Skills following the Gold Standard. This skill provides both the quality standards (what makes a good skill) and the workflow engine (how to iterate to get there).
Capabilities
- Create new skills from scratch with validated structure
- Run structured evals with baseline comparison (with-skill vs without-skill)
- Grade, benchmark, and review eval results via interactive viewer
- Iteratively improve skills based on user feedback
- Optimize skill descriptions for better triggering accuracy
- Package skills into distributable
.skillfiles - Adapt workflow to different environments (Claude Code, Codex, Antigravity, Claude.ai, Cowork)
What ships with it
34 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.
- agents/analyzer.md 3.4 KB
- agents/comparator.md 2.6 KB
- agents/grader.md 5.5 KB
- assets/eval_review.html 6.9 KB
- assets/SKILL_TEMPLATE.md 3.2 KB
- eval-viewer/generate_review.py 16 KB runs code
- eval-viewer/viewer.html 44 KB
- examples/SKILL_EXAMPLE_LEGACY_MIGRATOR.md 2.6 KB
- references/advanced-eval-patterns.md 7.2 KB
- references/default_parameters.md 2.8 KB
- references/eval_schemas.md 14 KB
- references/output-patterns.md 1.8 KB
- references/persuasion-principles.md 5.8 KB
- references/skill_design_patterns.md 2.4 KB
- references/testing-skills-with-subagents.md 12 KB
- references/workflows.md 818 B
- references/writing_skills_best_practices_anthropic.md 40 KB
- scripts/__init__.py 0 B runs code
- scripts/aggregate_benchmark.py 20 KB runs code
- scripts/generate_report.py 6.6 KB runs code
- scripts/improve_description.py 11 KB runs code
- scripts/init_skill.py 5.6 KB runs code
- scripts/package_skill.py 5.2 KB runs code
- scripts/run_eval.py 24 KB runs code
- scripts/run_loop.py 14 KB runs code
- scripts/skill_standards_default.yaml 1.9 KB
- scripts/skill_utils.py 11 KB runs code
- scripts/tests/__init__.py 0 B runs code
- scripts/tests/fixtures/fake_cli_claude_code.py 3.9 KB runs code
- scripts/tests/test_eval_tooling.py 11 KB runs code
- scripts/tests/test_frontmatter_strict.py 3.3 KB runs code
- scripts/tests/test_trigger_detection.py 15 KB runs code
- scripts/validate_skill.py 19 KB runs code
- scripts/verify_pin.py 5.6 KB runs code
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.
- 2d ago First seen · 409 lines · 45 tokens per session scan A 88584bbfe5a6
skill-creator is a skill published in the GitHub repository MatrixFounder/Agentic-development (5 stars, last pushed 19d ago), licensed Apache-2.0. It adds 45 tokens to every session and 5,098 once invoked, about $0.0002 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 2026-08-31.
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