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 jdrhyne/agent-skills --skill last30daysgit clone --depth 1 https://github.com/jdrhyne/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/jdrhyne/agent-skills/last30days)<a href="https://agentmods.dev/skills/jdrhyne/agent-skills/last30days"><img src="https://agentmods.dev/badge/skills/jdrhyne/agent-skills/last30days/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/jdrhyne/agent-skills/last30days"><img src="https://agentmods.dev/badge/skills/jdrhyne/agent-skills/last30days.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 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 Privilege Escalation · line 67 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 78 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 266 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 397 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 79 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Rogue Agent · line 66 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Privilege Escalation · line 78 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00086 | $0.03863 |
| Opus 5 | $0.00043 | $0.01931 |
| Sonnet 5 | $0.00017 | $0.00773 |
| Haiku 4.5 | $0.00009 | $0.00386 |
Grade B, and why
last30days scanned grade B with 1 finding 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 13d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
chmod 600 ~/.config/last30days/.env Copies of this mod
1 near-identical copy found in the catalogue:
- last30days — 88% identical, 64 lines differ
How it starts
The opening of the file, as written. The whole thing — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
last30days: Research Any Topic from the Last 30 Days
Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.
Use cases:
- Prompting: "photorealistic people in Nano Banana Pro", "Midjourney prompts", "ChatGPT image generation" → learn techniques, get copy-paste prompts
- Recommendations: "best Claude Code skills", "top AI tools" → get a LIST of specific things people mention
- News: "what's happening with OpenAI", "latest AI announcements" → current events and updates
- General: any topic you're curious about → understand what the community is saying
CRITICAL: Parse User Intent
Before doing anything, parse the user's input for:
- TOPIC: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation")
- TARGET TOOL (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney")
- QUERY TYPE: What kind of research they want:
- PROMPTING - "X prompts", "prompting for X", "X best practices" → User wants to learn techniques and get copy-paste prompts
- RECOMMENDATIONS - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things
- NEWS - "what's happening with X", "X news", "latest on X" → User wants current events/updates
- GENERAL - anything else → User wants broad understanding of the topic
Common patterns:
[topic] for [tool]→ "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED[topic] prompts for [tool]→ "UI design prompts for Midjourney" → TOOL IS SPECIFIED- Just
[topic]→ "iOS design mockups" → TOOL NOT SPECIFIED, that's OK - "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS
- "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS
IMPORTANT: Do NOT ask about target tool before research.
- If tool is specified in the query, use it
- If tool is NOT specified, run research first, then ask AFTER showing results
What ships with it
19 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.
- _meta.json 129 B
- .clawhub/origin.json 142 B
- scripts/last30days.py 16 KB runs code
- scripts/lib/__init__.py 29 B runs code
- scripts/lib/cache.py 4.1 KB runs code
- scripts/lib/dates.py 3.2 KB runs code
- scripts/lib/dedupe.py 3.2 KB runs code
- scripts/lib/env.py 4.8 KB runs code
- scripts/lib/http.py 4.7 KB runs code
- scripts/lib/models.py 4.5 KB runs code
- scripts/lib/normalize.py 4.7 KB runs code
- scripts/lib/openai_reddit.py 7.2 KB runs code
- scripts/lib/reddit_enrich.py 6.6 KB runs code
- scripts/lib/render.py 13 KB runs code
- scripts/lib/schema.py 11 KB runs code
- scripts/lib/score.py 9.0 KB runs code
- scripts/lib/ui.py 13 KB runs code
- scripts/lib/websearch.py 11 KB runs code
- scripts/lib/xai_x.py 6.5 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.
- 13d ago First seen · 399 lines · 86 tokens per session scan B 322f82c7a3e4
last30days is a skill published in the GitHub repository jdrhyne/agent-skills (241 stars, last pushed 13d ago), licensed MIT. It adds 86 tokens to every session and 3,863 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
ios-simulator
Verify and debug native, React Native, Expo, or Flutter apps on an iOS Simulator with agent-device. Use when an agent needs to launch an app, inspect its live UI, tap, type, scroll, validate a code change, collect failure evidence, or reproduce a workflow on an iPhone or iPad Simulator.
autonomous-run
Prepare, start, inspect, resume, or stop a finite local overnight coding run after a human has accepted a Wayfinder terminal spec; coordinates a declared Claude/Codex maker and independent checker without pushing, merging, or writing to external systems.
adaptive-quality
Per-task execution profile selection based on complexity in Balanced quality mode.
auto-qa
QAMESH project QA mesh — plan, run, report, and publish deterministic QA evidence.
experiment
Experiment loop for iterative metric-driven code optimization using XLOOP.
monitor-patterns
Monitor tool usage patterns and grep --line-buffered compatibility guide.