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 parallel-investigatorgit 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/parallel-investigator)<a href="https://agentmods.dev/skills/davila7/claude-with-skills/parallel-investigator"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/parallel-investigator/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/parallel-investigator"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/parallel-investigator.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 | $0.00053 | $0.00449 |
| Opus 5.5 | $0.00021 | $0.00180 |
| Sonnet 5.5 | $0.00011 | $0.00090 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
parallel-investigator 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 2mo 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
Investigate these two topics in parallel using separate Explore subagents:
- Topic 1: $0
- Topic 2: $1
Instructions
-
Spawn two Explore subagents simultaneously — one per topic. Give each a self-contained research prompt that includes:
- The specific topic to investigate
- Instructions to search broadly (Grep, Glob) before reading files deeply
- Instructions to produce a structured report: key files, how it works, notable patterns
Do not run the subagents sequentially. Start both at the same time.
-
Wait for both subagents to return their results.
-
Combine the findings into a single comparison report with these sections:
Topic 1 findings — summary of what the first subagent found
Topic 2 findings — summary of what the second subagent found
Similarities — patterns, libraries, approaches, or design decisions shared between the two topics
Differences — how they diverge: in scale, in architecture, in data model, in error handling, or in how they are tested
Recommendation — if the user is trying to make a decision (e.g., which approach to follow, which subsystem to extend), give a direct recommendation with reasoning. If the topics are purely informational (e.g., understanding two independent systems), omit this section.
Note on architecture
This skill does not use context: fork — it runs inline in your main conversation. This is intentional: a forked skill cannot spawn additional subagents, so any skill that needs to orchestrate multiple workers must run in the main context and delegate the worker tasks from there. The main conversation is the orchestrator; the Explore subagents are the workers.
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.
- 2mo ago First seen · 40 lines · 53 tokens per session scan A 6eb7d98c2262
parallel-investigator is a skill published in the GitHub repository davila7/claude-with-skills (13 stars, last pushed 5mo ago), licensed MIT. It adds 53 tokens to every session and 449 once invoked, about $0.0002 per session on Opus 5.5. 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.
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