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BigCactusLabs

dead-letter

get_diagnostics

Inspect email quality and structure to assess conversion quality or troubleshoot problematic .eml files. Returns JSON with state, warnings, and other diagnostics.

Instructions

Inspect email quality and structure without writing permanent files.

Use this to assess conversion quality before committing, or to troubleshoot problematic .eml files.

Returns JSON with: state (normal/degraded/review_recommended), selected_body, segmentation_path, client_hint, confidence, warnings, and stripped_images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presetNodefault
eml_pathYes
thread_modeNolatest
thread_orderNooldest-first
include_raw_htmlNo
strip_signaturesNo
strip_disclaimersNo
embed_inline_imagesNo
include_all_headersNo
no_calendar_summaryNo
strip_quoted_headersNo
strip_tracking_pixelsNo
strip_signature_imagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description correctly indicates the tool is read-only ('without writing permanent files') and lists return fields. It could add more on failure handling or side effects, but the core behavioral trait is disclosed.

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?

Three efficient sentences. The primary purpose is stated first, followed by use cases, then return value summary. No redundant information.

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

Completeness3/5

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

Given the high parameter count (13) and no annotations, the description should cover key parameters but does not. It does explain the output schema adequately and provides use cases. The output schema exists, reducing the need to document return values, but parameter guidance is missing.

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

Parameters2/5

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

Schema description coverage is 0%, yet the description does not explain any of the 13 parameters (preset, thread_mode, stripping options, etc.). Parameter names provide some hints, but the description adds no semantic guidance beyond the schema.

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 verb 'Inspect' and resource 'email quality and structure', and explicitly distinguishes itself from sibling conversion tools by noting it does not write permanent files. This leaves no ambiguity about what the tool does.

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

Usage Guidelines5/5

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

Provides explicit scenarios: 'assess conversion quality before committing' and 'troubleshoot problematic .eml files'. This gives clear when-to-use guidance, and the sibling tools are all about conversion, making the distinction clear.

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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