Claude With Skills is a progressive course that teaches developers to create reusable, portable Agent Skills for Claude Code, from basic SKILL.md files to advanced automation and plugin packaging. It is intended for developers who want repeatable instructions and workflows instead of repeatedly pasting the same guidance. The catalogue contains the course's skills, agents, and instruction.
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 davila7/claude-with-skills --skill deep-analysisgit clone --depth 1 https://github.com/davila7/claude-with-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/davila7/claude-with-skills/deep-analysis)<a href="https://agentmods.dev/skills/davila7/claude-with-skills/deep-analysis"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/deep-analysis/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/davila7/claude-with-skills/deep-analysis"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/deep-analysis.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 | $0.00035 | $0.00723 |
| Opus 5 | $0.00017 | $0.00362 |
| Sonnet 5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
deep-analysis 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 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.
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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep analysis
ultrathink
Perform a thorough analysis of the described problem or codebase area. Do not skip steps under time or context pressure. This skill intentionally uses extended reasoning — use it.
Step 1: Gather all relevant context
Before forming any hypothesis, collect the raw material:
- Read all files directly involved in the problem area
- Check git history for the relevant files:
git log --oneline --follow -20 <file>for each key file, thengit show <hash>for commits that look relevant - Look for tests that cover the area: they describe the intended behavior
- Look for related configuration (environment variables, feature flags, build configuration)
- Check for any documentation: comments, ADRs, or README sections that mention the area
Do not stop gathering context when you think you understand the issue. The full picture often requires reading more than the most obvious files.
Step 2: Identify the core issue or question
State, in one or two sentences, what the fundamental question or problem is. Separate it from symptoms. For example:
- Symptom: "The API returns 500 errors intermittently"
- Core question: "Is this a race condition in the connection pool, an unhandled exception in a specific code path, or an infrastructure issue?"
If you are doing an architectural analysis, state the specific decision or tradeoff being evaluated.
Step 3: Consider multiple hypotheses or approaches
Do not converge on the first plausible explanation. List at least three distinct hypotheses or approaches:
- For bug analysis: three distinct root causes that could explain the observed behavior
- For architecture decisions: three distinct design approaches with different tradeoff profiles
- For security reviews: three distinct vulnerability classes to investigate
For each, note what evidence would confirm or rule it out.
Step 4: Evaluate tradeoffs
For each hypothesis or approach, evaluate:
Evidence for: What in the codebase supports this explanation or approach? Evidence against: What contradicts it or makes it unlikely? Risk: If this hypothesis is wrong or this approach is chosen, what goes wrong? Cost to verify or implement: How much effort would confirming or executing this require?
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 · 71 lines · 35 tokens per session scan A 78a1653dfb82
deep-analysis is a skill published in the GitHub repository davila7/claude-with-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 723 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 2026-08-30.
Other skills, from other repositories
autoreview
Pre-commit/ship code review: Codex default; optional Claude or Pi.
rework-rate
Measure and interpret PR rework rate — the emerging 5th DORA metric.
omh-code-review
This is a Hermes-native code-review workflow skill.
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.