sample-strands-agents-agentskills implements the AgentSkills.io standard for Strands Agents SDK, packaging specialized knowledge, workflows, and best practices as modular capabilities that an AI agent can load when needed. It helps developers extend general-purpose Strands agents with reusable domain skills such as document and presentation processing. The catalogue entries are Agent Skills designed for this implementation.
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 aws-samples/sample-strands-agents-agentskills --skill file-processinggit clone --depth 1 https://github.com/aws-samples/sample-strands-agents-agentskillsWrote 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/aws-samples/sample-strands-agents-agentskills/file-processing)<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agents-agentskills/file-processing"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agents-agentskills/file-processing/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/aws-samples/sample-strands-agents-agentskills/file-processing"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agents-agentskills/file-processing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.01617 |
| Opus 5.5 | $0.00010 | $0.00647 |
| Sonnet 5.5 | $0.00005 | $0.00323 |
| Haiku 4.5 | $0.00002 | $0.00162 |
Grade A, and why
file-processing 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 1mo 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
File Processing Skill
Purpose
Process structured data files (CSV, JSON, text) with comprehensive capabilities for data cleaning, transformation, analysis, and export. This skill enables working with data files without requiring users to write code.
When to Use This Skill
Use this skill when you need to:
- Load and parse CSV or JSON files
- Clean and transform data
- Perform statistical analysis
- Filter, sort, or aggregate data
- Merge or join datasets
- Convert between formats (CSV ↔ JSON)
- Generate summary reports
Capabilities
1. Data Loading
Supported formats:
- CSV files: Any delimiter (comma, tab, semicolon, etc.)
- JSON files: Single objects or arrays of objects
- Text files: Custom delimited formats
2. Data Cleaning
Available operations:
- Remove duplicate rows
- Handle missing values (drop, fill, interpolate)
- Normalize text (trim whitespace, standardize case)
- Convert data types
- Remove outliers
- Validate data against rules
3. Data Transformation
Available operations:
- Filter: Select rows based on conditions
- Select: Choose specific columns
- Sort: Order by one or more columns
- Group: Aggregate data by categories
- Pivot: Reshape data (wide ↔ long format)
- Merge: Combine multiple datasets
- Calculate: Add derived columns
4. Data Analysis
Available analyses:
- Descriptive statistics (mean, median, std, etc.)
- Frequency distributions
- Correlation analysis
- Trend detection
- Missing data analysis
- Data quality assessment
5. Export
Output formats:
- CSV files
- JSON files (objects or arrays)
- Markdown tables
- Summary reports
Instructions for Execution
When this skill is activated, follow these steps:
Step 1: Understand the Request
Ask clarifying questions if needed:
- What file(s) need to be processed?
- What specific analysis or transformation is required?
- What output format is desired?
- Are there any specific requirements or constraints?
Step 2: Load the Data
What ships with it
1 file 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.
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.
- 1mo ago First seen · 281 lines · 24 tokens per session scan A ace7949d7e49
file-processing is a skill published in the GitHub repository aws-samples/sample-strands-agents-agentskills (91 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,617 once invoked, about $0.0001 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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