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 arvindand/agent-skills --skill skill-craftinggit clone --depth 1 https://github.com/arvindand/agent-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/arvindand/agent-skills/skill-crafting)<a href="https://agentmods.dev/skills/arvindand/agent-skills/skill-crafting"><img src="https://agentmods.dev/badge/skills/arvindand/agent-skills/skill-crafting.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Rogue Agent · line 127 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- high Rogue Agent · line 310 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00122 | $0.03421 |
| Opus 5 | $0.00061 | $0.01710 |
| Sonnet 5 | $0.00024 | $0.00684 |
| Haiku 4.5 | $0.00012 | $0.00342 |
Grade A, and why
skill-crafting 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 8d 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 — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Crafting
Create effective, discoverable skills that work under pressure.
When to Use
Creating:
- "Create a skill for X"
- "Build a skill to handle Y"
From Session History:
- "Create a skill from this session"
- "Turn what we just did into a skill"
- "Can the database setup we did become a skill?"
- "Could we create a skill from this?" (evaluate first)
- "Should this be a skill?" (evaluate first)
Fixing:
- "This skill isn't working"
- "Why isn't this skill triggering?"
- "Skill didn't trigger when it should have"
Analyzing:
- "Analyze my skill for issues"
- "Run skill analysis"
- "Check this skill's quality"
- "Audit all my skills"
- "Check character budget across skills"
Analyzing a Skill
When user asks to analyze a skill:
-
Run scripts first when available for mechanical checks:
python3 ${CLAUDE_SKILL_DIR}/scripts/analyze-all.py path/to/skill/If scripts fail because of environment or tooling issues, state the blocker clearly and continue with manual review.
-
Read the skill files for qualitative review:
- Read SKILL.md
- Read REFERENCES.md (if exists)
- Read directly linked
references/,scripts/, oragents/openai.yamlfiles when they materially affect behavior
-
Provide holistic feedback covering:
- Script results (CSO, structure, tokens) or explicit blocker if scripts could not run
- Does
allowed-toolsmatch what the skill needs to do? - Does the analysis cover the files that actually define the skill's behavior?
- Is the workflow clear and actionable?
- Are references appropriate and sized correctly?
- Missing sections or anti-patterns?
-
Give verdict with prioritized recommendations
Validation Scripts
| Script | Purpose | Usage |
|---|---|---|
analyze-all.py |
Run all checks | python3 ${CLAUDE_SKILL_DIR}/scripts/analyze-all.py path/to/skill/ |
analyze-cso.py |
Check CSO compliance | python3 ${CLAUDE_SKILL_DIR}/scripts/analyze-cso.py path/to/SKILL.md |
analyze-tokens.py |
Count tokens | python3 ${CLAUDE_SKILL_DIR}/scripts/analyze-tokens.py path/to/SKILL.md |
analyze-triggers.py |
Find missing triggers | python3 ${CLAUDE_SKILL_DIR}/scripts/analyze-triggers.py path/to/SKILL.md |
check-char-budget.py |
Check description caps | python3 ${CLAUDE_SKILL_DIR}/scripts/check-char-budget.py path/to/skills/ |
What ships with it
10 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.
- LICENSE 1.0 KB
- REFERENCES.md 22 KB
- scripts/analyze-all.py 9.8 KB runs code
- scripts/analyze-compatibility.py 6.6 KB runs code
- scripts/analyze-cso.py 5.1 KB runs code
- scripts/analyze-structure.py 6.3 KB runs code
- scripts/analyze-tokens.py 5.1 KB runs code
- scripts/analyze-triggers.py 5.9 KB runs code
- scripts/check-char-budget.py 6.4 KB runs code
- scripts/frontmatter.py 6.2 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.
- 8d ago First seen · 436 lines · 122 tokens per session scan A 356c46858473
skill-crafting is a skill published in the GitHub repository arvindand/agent-skills (16 stars, last pushed 11d ago), licensed MIT. It adds 122 tokens to every session and 3,421 once invoked, about $0.0006 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
spec-work
A workflow skill for completing todo items through written plans and progress records. It follows a sequence of writing a plan, getting approval, implementing the work, recording an update, and reporting completion.
spec-todo
A Korean-language skill for turning a project specification into requirements and a task list. Spec-Driven Development means planning the required behaviour before implementing it.
spec-init
A project setup skill for spec-driven development, a way of building software from written requirements before implementation. It creates a feature folder under ai-spec/projects with a requirement template and docs folder.
rework-rate
Measure and interpret PR rework rate — the emerging 5th DORA metric.
tokf-discover
Find missed token savings by scanning AI coding session files for commands that ran without tokf filtering.
skillnote
Self-hosted skill registry for OpenClaw. Stores procedures your team writes (name, description, body), syncs them to disk before each task, and collects which-helped/which-failed signals from the agent so the registry improves over time.