Skip to main content
Glama

Email Header Analysis

email_header_analysis
Read-onlyIdempotent

Parse raw email headers to reconstruct delivery hops, verify SPF/DKIM/DMARC, measure delays, and flag non-TLS hops—diagnose spoofing, delays, or lost mail after delivery.

Instructions

Parse raw email headers to reconstruct the delivery path (each Received hop in order), extract SPF/DKIM/DMARC authentication results, measure per-hop delays, and flag unencrypted (non-TLS) hops. Use this to diagnose a specific message that was already delivered — spoofing, delays, or where mail was lost. Use email_auth instead to assess a domain's sending configuration before sending. Read-only; requires no API key; rate-limited. INPUT is the full raw header block. OUTPUT is a text report containing: the ordered hop route, per-mechanism auth results (pass/fail), detected inter-hop delays, and the encryption status of each hop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
headersYesThe complete raw email header block, copied verbatim — every line from the first 'Received:'/'From:' down to the blank line before the body. Paste as-is, including folded continuation lines; do not include the message body.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kpisNoKey metrics as label/value pairs
gradeNoLetter grade (A+ to F) when the tool grades the target
scoreNo0-100 score when the tool scores the target
issuesNoDetected problems, severity-rated
statusYesOverall verdict, e.g. 'good' | 'warning' | 'bad' | 'info' | 'unknown'
actionsNoRecommended next actions, most important first
summaryNoOne-paragraph interpretation of the result
receiptsNoSigned observation receipts behind this result, one per lookup: when, from where and under which rules version DechoNet observed it. Each url shows the record and checks its Ed25519 signature.
reportUrlYesHuman-facing interactive report for this exact lookup on dechonet.com
observationNoHow much was actually observed and when. A partial observation means some checks did not answer: missing parts are not verified, never clean.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.5.14
    • addedOutput schema / properties / observation
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "How much was actually observed and when. A partial observation means some checks did not answer: missing parts are not verified, never clean.",
      +  "properties": {
      +    "ageMinutes": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "cached": {
      +      "type": "boolean"
      +    },
      +    "observedAt": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "state": {
      +      "enum": [
      +        "complete",
      +        "partial",
      +        "unknown"
      +      ],
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "state",
      +    "observedAt",
      +    "cached",
      +    "ageMinutes"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / receipts
      Added value: +{
      +  "description": "Signed observation receipts behind this result, one per lookup: when, from where and under which rules version DechoNet observed it. Each url shows the record and checks its Ed25519 signature.",
      +  "items": {
      +    "additionalProperties": false,
      +    "properties": {
      +      "id": {
      +        "type": "string"
      +      },
      +      "tool": {
      +        "type": "string"
      +      },
      +      "url": {
      +        "type": "string"
      +      }
      +    },
      +    "required": [
      +      "tool",
      +      "id",
      +      "url"
      +    ],
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
  2. Changed1 schema field changedv1.1.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "actions": {
      +      "description": "Recommended next actions, most important first",
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "grade": {
      +      "description": "Letter grade (A+ to F) when the tool grades the target",
      +      "type": "string"
      +    },
      +    "issues": {
      +      "description": "Detected problems, severity-rated",
      +      "items": {
      +        "additionalProperties": false,
      +        "properties": {
      +          "key": {
      +            "type": "string"
      +          },
      +          "severity": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "severity",
      +          "key"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "kpis": {
      +      "description": "Key metrics as label/value pairs",
      +      "items": {
      +        "additionalProperties": false,
      +        "properties": {
      +          "label": {
      +            "type": "string"
      +          },
      +          "value": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "label",
      +          "value"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "reportUrl": {
      +      "description": "Human-facing interactive report for this exact lookup on dechonet.com",
      +      "type": "string"
      +    },
      +    "score": {
      +      "description": "0-100 score when the tool scores the target",
      +      "type": "number"
      +    },
      +    "status": {
      +      "description": "Overall verdict, e.g. 'good' | 'warning' | 'bad' | 'info' | 'unknown'",
      +      "type": "string"
      +    },
      +    "summary": {
      +      "description": "One-paragraph interpretation of the result",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "status",
      +    "reportUrl"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changedv1.0.3
    • changedInput schema / properties / headers / description
      Previous value: -"Raw email headers to analyze (paste the full header text)"New value: +"The complete raw email header block, copied verbatim — every line from the first 'Received:'/'From:' down to the blank line before the body. Paste as-is, including folded continuation lines; do not include the message body."
  4. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety bar is lower. The description still adds non-obvious operational context the annotations cannot convey: no API key required and the tool is rate-limited, plus a summary of what the report contains. It stops short of quantifying the rate limit or noting failure modes on malformed input.

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

Conciseness4/5

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

Capability is front-loaded in the first sentence, followed by usage, alternative, and operational notes in a tight sequence with no filler. The trailing INPUT/OUTPUT sentences are somewhat redundant given a full output schema exists, which is the only real slack.

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

Completeness5/5

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

For a single-parameter read-only diagnostic tool with both annotations and an output schema, the description covers purpose, selection criteria against the closest sibling, input expectations, and behavioral constraints. Nothing an agent needs in order to call it correctly is missing.

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 description coverage is 100% and the single parameter's schema text is already detailed (verbatim block, folded lines, no body). The description's 'INPUT is the full raw header block' merely restates that, adding no syntax or format detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 states a precise verb chain (parse, reconstruct, extract, measure, flag) against a specific resource (raw email headers) and enumerates the exact analytical outputs. It explicitly distinguishes itself from the sibling email_auth, so an agent can route between them without opening either schema.

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?

It gives an explicit when-to-use ('diagnose a specific message that was already delivered — spoofing, delays, or where mail was lost') and an explicit alternative with its own condition ('Use email_auth instead to assess a domain's sending configuration before sending'). Both the trigger and the exclusion are spelled out.

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