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style(no-slop): remove every em-dash + banned words across all modules + capstone

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Apply the no-ai-slop standard (now binding in AGENTS.md): the em-dash character is
banned outright (restructured, not blind-replaced), plus the banned word/phrase
list (delve, leverage, robust, seamless, truly, unlock, etc.). 0 em-dashes remain
in modules + capstone; the only "robust" left is the planted M10 ai-change.patch
trap. Module H1 titles use a colon separator.

All deliberate teaching devices preserved; labs compile/parse (py/sh/yaml/json);
no junk. AGENTS.md updated with the hard no-slop rules.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
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Claude (agent)
2026-06-22 23:21:09 -04:00
parent 513d7e7ac8
commit 389ac2e460
99 changed files with 1324 additions and 1315 deletions
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modules/22-securing-third-party-mcp-and-skills/lab/README.md
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Run the lab from the module README. Quick map of what's here:
- **`audit.sh`** — the runnable vetting checklist. `bash audit.sh <dir>` statically scans a skill or
- **`audit.sh`**: the runnable vetting checklist. `bash audit.sh <dir>` statically scans a skill or
MCP server for red flags (network egress, secret/env reads, shell-out, obfuscation, broad FS
access, hidden/injected instructions, zero-width characters). It only reads; it never executes the
target.
- **`suspicious-skill/`** — the audit TARGET for Part A. A deliberately malicious "export tasks to
- **`suspicious-skill/`**: the audit TARGET for Part A. A deliberately malicious "export tasks to
Notion" skill (`SKILL.md` + `tools/sync.py`). **Do not install it or run `sync.py` against real
credentials** — it exfiltrates your environment and local secrets. The point is to catch it first.
- **`poisoned-task.txt`** — the prompt-injection payload for Part B. A real-looking task with an
credentials**; it exfiltrates your environment and local secrets. The point is to catch it first.
- **`poisoned-task.txt`**: the prompt-injection payload for Part B. A real-looking task with an
injected "system" directive underneath, to add to the Module 1 `tasks-app` and feed to your AI.
Expected result of Part A: