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parse_freshness_signals

Pure parser (no fetching). Given HTML plus optional response headers and a sitemap entry for the same URL, extracts every freshness marker on the page — HTTP Last-Modified, sitemap lastmod, JSON-LD dateModified/datePublished (including @graph), OpenGraph article:modified_time/published_time, meta updated/dc.date.modified/dcterms.modified/itemprop dateModified, and the first labelled visible date (Last updated / Updated / Published). Returns per-source ISO dates, the freshest source, cross-source agreement spread, and heuristic flags (stale year in title, suspicious future date, only-published-not-modified, none-at-all). Powers the geo-aeo-readiness skill's freshness check — Last-Modified headers and dateModified JSON-LD are weighted heavily for AI grounding eligibility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL the HTML was fetched from (for context)
htmlYesFull HTML of the page
headersNoResponse headers as a plain object with lowercased keys (e.g. {"last-modified": "..."})
sitemapEntryNoParsed sitemap entry for this URL, e.g. {"lastmod": "2026-04-15"}

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are provided, so the description bears full responsibility. It fully discloses that the tool is a parser that does not fetch, lists all markers it extracts, and describes what it returns (per-source ISO dates, freshest source, cross-source spread, heuristic flags). This leaves no ambiguity about its behavior.

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 a single paragraph but packs significant information efficiently. It front-loads 'Pure parser (no fetching)' as the key caveat. Every sentence adds value; however, it could be broken into smaller sections for readability.

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?

Given the tool's complexity (four parameters including nested objects, no output schema), the description is remarkably complete. It explains the purpose of each parameter, enumerates all extracted markers, and describes the return value components (per-source dates, freshest source, spread, heuristic flags). It also ties the tool to a specific usage context (geo-aeo-readiness skill).

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

Parameters4/5

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

Schema coverage is 100% with descriptions for all four parameters. The tool description adds context beyond the schema: url is 'for context', headers are expected with 'lowercased keys', and sitemapEntry is a 'parsed sitemap entry'. It does not fully detail the structure of the output object but compensates by listing return fields in free text.

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 it is a 'pure parser (no fetching)' and enumerates exactly which freshness markers it extracts (HTTP Last-Modified, sitemap lastmod, JSON-LD dates, etc.). It identifies the tool's resource (freshness markers in HTML) and distinguishes it from sibling tools like 'get_page' (which fetches) by emphasizing it does not fetch.

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

Usage Guidelines4/5

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

The description specifies the tool is for extracting freshness signals and notes its use in the 'geo-aeo-readiness skill's freshness check'. It implies when to use (when you need to parse freshness markers from already-fetched HTML) but does not explicitly state when not to use it or provide direct comparisons to alternatives among the siblings.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: page SEO vs site AI discovery vs bot checks vs graph computation vs link extraction vs brand info vs page fetching vs listing vs entity lookup vs freshness parsing vs search. No overlapping responsibilities.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in lower_snake_case (e.g., analyze_page, check_bots, compute_link_graph). No mixing of conventions.

Tool Count5/5

11 tools is well-scoped for the server's purpose (SEO/web analysis). Each tool earns its place, covering page, site, bot, link graph, entity, and freshness analysis without unnecessary bulk.

Completeness5/5

The tool surface appears complete for its domain: it covers individual page SEO, site-wide AI discovery, bot accessibility, link graph analysis, entity lookup, and freshness signals. No obvious gaps for the intended analysis workflows.

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