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sourav-spd

aws-s3-connector-mcp

by sourav-spd

read_object

Read and display contents of S3 objects, including text, Excel, Parquet, PDF, and image formats. Supports metadata for binary files.

Instructions

Read and display the contents of an object in the connected S3 bucket. Supported formats:

  • Text: .txt, .csv, .json, .jsonl, .xml, .html, .md, .log, .yaml, .yml

  • Excel: .xlsx, .xls — returns all sheet data as tables

  • Parquet: .parquet — returns schema + first 50 rows

  • PDF: .pdf — extracts text from first 10 pages

  • Images: .png, .jpg, .jpeg, .gif, .webp — returns image content

  • Unknown/binary: returns file metadata only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_charsNoMax characters to return for text files (default: 10000).
object_keyYesThe S3 object key (path/filename) to read.
sheet_nameNoFor Excel: specific sheet name to read. Reads all sheets if not provided.
bucket_nameNoOverride the connected bucket name (optional).
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description provides good behavioral transparency: it explains format-specific behaviors (e.g., PDF first 10 pages, Parquet first 50 rows, unknown returns metadata). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the purpose. It uses a bullet-like structure for formats, maximizing readability with minimal text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool without an output schema, the description adequately covers return behaviors per format. It could mention the overall return structure (e.g., JSON object) but is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already well-documented. The description adds no new semantic details beyond the format list, which is contextual rather than param-specific.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads and displays object contents, and lists supported formats. It is distinct from siblings like list_objects and upload_object.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description focuses on format support rather than usage context or exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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