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Domain Change History

domain_changes
Read-onlyIdempotent

Report what has CHANGED for a domain over time — the security regressions and drift that DechoNet's daily monitoring has recorded across every watch on the domain (SSL grade, headers, DNS, OWASP posture, impersonation exposure, etc.). Use this to answer "what changed on my domain since yesterday/last week?" — a question that requires persistent snapshots and therefore cannot be reconstructed from a single live lookup. Call it FIRST whenever a domain you have looked at before comes up again. Two sources: (a) the daily watch timeline if the domain is watched (start one with watch_domain), and (b) even without a watch, the difference between the last two stored lookups of each tool — so a second lookup already yields a comparison. The point-in-time tools (security_scan, owasp_check, ssl_check) give the current state instead. Read-only; requires no API key; rate-limited. Returns the monitored tools, a newest-first change timeline, lookup-to-lookup changes, and a link to manage monitoring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain whose recorded change history to fetch (e.g., 'example.com'). Scheme and path are stripped.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
changesNoRecorded changes, newest first
watchedYesWhether the domain is under an active daily watch
reportUrlYesWhere a human can start or manage monitoring
changeCountNoNumber of changes recorded
historyChangesNoLookup-to-lookup changes, newest first
historyChangeCountNoChanges found between the last two stored lookups per tool (no watch needed)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / historyChangeCount
      Added value: +{
      +  "description": "Changes found between the last two stored lookups per tool (no watch needed)",
      +  "type": "number"
      +}
    • addedOutput schema / properties / historyChanges
      Added value: +{
      +  "description": "Lookup-to-lookup changes, newest first",
      +  "items": {
      +    "properties": {
      +      "changedAt": {
      +        "type": "string"
      +      },
      +      "endpoint": {
      +        "type": "string"
      +      },
      +      "kind": {
      +        "type": "string"
      +      },
      +      "since": {
      +        "type": "string"
      +      },
      +      "summary": {
      +        "type": "string"
      +      }
      +    },
      +    "required": [
      +      "kind",
      +      "summary"
      +    ],
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already mark this as read-only, open-world, idempotent, and non-destructive, and the description is consistent with those. The description adds value beyond annotations by disclosing 'requires no API key', 'rate-limited', the two sources of change data, and the return contents ('monitored tools, a newest-first change timeline, lookup-to-lookup changes, and a link to manage monitoring'). No annotation contradiction exists.

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?

The description is information-dense but each sentence earns its place: scope, usage timing, data-source mechanics, point-in-time alternative, and operational details. It is somewhat long for a single paragraph, but it is front-loaded with the core purpose and avoids filler, so only minor structure improvements are possible.

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?

With one well-documented parameter, an output schema, and annotations covering safety, the description is complete for invocation. It covers the main use case, the fallback behavior without a watch, the relationship to watch_domain, and what the response contains, so an agent has everything needed to select and call the tool correctly.

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%, so the schema already explains the single 'domain' parameter including that scheme and path are stripped. The description does not need to add parameter-level detail, and adding it would be redundant. Baseline 3 is appropriate.

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 uses a specific verb and resource: 'Report what has CHANGED for a domain over time' and immediately clarifies this is about security regressions and drift from persistent monitoring. It explicitly contrasts itself with 'point-in-time tools (security_scan, owasp_check, ssl_check)', so an agent can distinguish it from sibling tools.

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?

The description explicitly says when to use it: to answer 'what changed on my domain since yesterday/last week?', and instructs to 'Call it FIRST whenever a domain you have looked at before comes up again.' It also names alternatives ('The point-in-time tools ... give the current state instead') and explains the two data sources, so the when/when-not decision is fully specified.

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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