CSV Data Summarizer
coffeefuelbump/csv-data-summarizer-claude-skill
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Agent skill
Implementing Network Traffic Baselining
Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker…
Install Implementing Network Traffic Baselining
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baselining --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .claude/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .claude/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baseliningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baselining --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .agents/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .agents/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baselining --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .cursor/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .cursor/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/implementing-network-traffic-baselining--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baselining --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .gemini/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .gemini/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baseliningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .github/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .github/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-traffic-baselining --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/implementing-network-traffic-baselining .opencode/skills/implementing-network-traffic-baselining && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "implementing-network-traffic-baselining" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-traffic-baselining into .opencode/skills/implementing-network-traffic-baselining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-traffic-baselining", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
implementing-network-traffic-baselining- GitHub stars
- 34k
- Token cost
- ~652 tokens
- SKILL.md length
- 227 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 639
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker…
- Works in 7 steps: Ingest NetFlow/IPFIX records from CSV or… → Compute hourly and daily traffic volume… → Build per-source-IP baseline profiles… → …
- A SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes
- SKILL.md covers Overview, When to Use, Prerequisites and Steps, plus 1 more section
- Runs Python scripts from its folder
What it does
Implementing Network Traffic Baselining is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker profiles, then flags outliers via z-score and IQR anomaly detection. Use when a SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes, beaconing, or unusual port usage from historical flow data.
Its SKILL.md is about 650 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Data & Analytics, covering DataFrames, Anomaly detection and Statistics. It works with Python and pandas. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
When your agent uses it
- A SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes
- Unusual port usage from historical flow data
Example prompts
- “Use the implementing-network-traffic-baselining skill to build network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas…”
- “/implementing-network-traffic-baselining”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Ingest NetFlow/IPFIX records from CSV or JSON exports
- Compute hourly and daily traffic volume distributions (bytes, packets, flows)
- Build per-source-IP baseline profiles with mean, median, standard deviation
- Calculate protocol and port distribution baselines
- Apply z-score anomaly detection to identify statistical outliers
- Flag flows exceeding IQR-based thresholds as potential anomalies
- Generate baseline report with anomaly alerts
What it can do on your machine
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Implementing Network Traffic Baselining loads about 652 tokens when it runs, and up to ~1.1k if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 227 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 227 words, ~652 tokens.
Download SKILL.mdSave it as
.claude/skills/implementing-network-traffic-baselining/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- implementing-network-traffic-baselining
- description
- Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker profiles, then flags outliers via z-score and IQR anomaly detection. Use when a SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes, beaconing, or unusual port usage from historical flow data.
- domain
- cybersecurity
- subdomain
- network-security
- tags
- netflow, ipfix, traffic-analysis, baselining, anomaly-detection, pandas, network-monitoring
- version
- 1.0
- author
- mahipal
- license
- Apache-2.0
- nist_csf
- PR.IR-01, DE.CM-01, ID.AM-03, PR.DS-02
- mitre_attack
- T1046, T1040, T1557, T1071
Implementing Network Traffic Baselining
Overview
Network traffic baselining establishes normal communication patterns by analyzing historical NetFlow/IPFIX data to create statistical profiles of expected behavior. This skill uses Python pandas to compute hourly and daily traffic distributions, per-host byte/packet counts, protocol ratios, and top-N talker profiles. Anomalies are detected using z-score thresholds and IQR (interquartile range) outlier methods, enabling SOC analysts to identify deviations such as data exfiltration spikes, beaconing patterns, and unusual port usage.
When to Use
- When deploying or configuring implementing network traffic baselining capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- NetFlow v5/v9 or IPFIX flow data exported as CSV or JSON
- Python 3.8+ with pandas and numpy libraries
- Historical flow data (minimum 7 days recommended for baseline)
Steps
- Ingest NetFlow/IPFIX records from CSV or JSON exports
- Compute hourly and daily traffic volume distributions (bytes, packets, flows)
- Build per-source-IP baseline profiles with mean, median, standard deviation
- Calculate protocol and port distribution baselines
- Apply z-score anomaly detection to identify statistical outliers
- Flag flows exceeding IQR-based thresholds as potential anomalies
- Generate baseline report with anomaly alerts
Expected Output
JSON report containing traffic baselines (hourly/daily profiles), per-host statistics, detected anomalies with z-scores, and top talker rankings with deviation indicators.
© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts, references) in skills/implementing-network-traffic-baselining of mukul975/Anthropic-Cybersecurity-Skills.
- SKILL.md
- LICENSE
- references/api-reference.md
- scripts/agent.py
Open the folder on GitHubat commit 54a7988
Compare with similar skills
Implementing Network Traffic Baselining next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Implementing Network Traffic Baselining this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~652 | Automated safety check: Pass | Apache-2.0 | |
| CSV Data Summarizercoffeefuelbump/csv-data-summarizer-claude-skill | 468 | 2 repos | ~1.4k | Automated safety check: Pass | None | |
| Vaex Out-of-Core DataFramesdavila7/claude-code-templates | 32k | 12 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Data Table AnalysisNVIDIA-AI-Blueprints/deep-researcher-agent | 883 | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Bio Reporting Publication TablesGPTomics/bioSkills | 1.2k | 1 repos | ~2.8k | Automated safety check: Pass | MIT | |
| CSV and Excel MergerOneWave-AI/claude-skills | 322 | — | ~1.6k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Implementing Network Traffic Baselining
What does Implementing Network Traffic Baselining do?
Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker…. Implementing Network Traffic Baselining is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker profiles, then flags outliers via z-score and IQR anomaly detection.
When should I use Implementing Network Traffic Baselining?
Implementing Network Traffic Baselining fits situations like: A SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes; unusual port usage from historical flow data.
How do I install Implementing Network Traffic Baselining in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a claude-code`. Or copy the skill folder (skills/implementing-network-traffic-baselining in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-network-traffic-baselining in your project. Claude Code loads it when a task matches its description.
How do I install Implementing Network Traffic Baselining in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a codex`. Or copy the skill folder (skills/implementing-network-traffic-baselining in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-network-traffic-baselining in your project. Codex loads it when a task matches its description.
Can I use Implementing Network Traffic Baselining in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-traffic-baselining -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-network-traffic-baselining, .gemini/skills/implementing-network-traffic-baselining, .github/skills/implementing-network-traffic-baselining and .opencode/skills/implementing-network-traffic-baselining in your project.
What does Implementing Network Traffic Baselining need to run?
Going by SKILL.md and its folder, Implementing Network Traffic Baselining needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Implementing Network Traffic Baselining access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Implementing Network Traffic Baselining safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Implementing Network Traffic Baselining use?
Implementing Network Traffic Baselining is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Implementing Network Traffic Baselining use?
About 652 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 433 tokens, read only when the agent opens those files.
What are the alternatives to Implementing Network Traffic Baselining?
Skills that share tags, products or a category with Implementing Network Traffic Baselining: CSV Data Summarizer (coffeefuelbump/csv-data-summarizer-claude-skill, 468 stars), Vaex Out-of-Core DataFrames (davila7/claude-code-templates, 32k stars), Data Table Analysis (NVIDIA-AI-Blueprints/deep-researcher-agent, 883 stars) and Bio Reporting Publication Tables (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Implementing Network Traffic Baselining?
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,870 GitHub stars. The repository holds 639 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.