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get_editorial_velocity

get_editorial_velocity

Read an editorial velocity analysis, poll until it is done

Returns the analysis started by POST /api/v1/tools/editorial-velocity. While status is pending or running, call again every 5 seconds; progress gives the current stage (robots, sitemap, pages, summary) and pagesRead out of pagesTotal. When status is failed, failureCode says why (BLOCKED, the site refuses to be read; NO_SITEMAP; NO_DATES, pages read but none shows a readable publication date, neither structured data, nor a date tag, nor a "Published on" mention; UNREACHABLE; TIMEOUT; INTERNAL) and publications is null. A failed analysis is never a zero. A NO_DATES analysis may carry sitemapCeiling, an upper bound read from the sitemap modification dates: at most total pages were published or modified in the window. It is never a count of articles nor a pace, and the status stays failed.

When status is done, publications.total articles were published in window (12 full months, UTC), perMonth is total / 12 and perWeek total / 52.14. ci95 is only meaningful when the analysis was sampled (method.sampled). A total of 0 with ci95 present comes from a sample: it does not prove that the website published nothing, and neither does a 0 with method.undecidedSections not empty (sections whose reading stopped before a verdict, counted nowhere). Otherwise, a 0 covers what was read in full: the whole site, or only its dated sections when method.undatedSections is not empty. A 0 with publications.otherDatedPages above 0 means that dated pages were read, but nothing shows that they are articles (product pages, event calendars): it adds to the meaning of the 0 above, it never replaces it. method.inferredSections names the sections without article markup counted from the dates read in their pages (itemprop attribute or <time> element). method.sameDaySections names the sections where at least 80% of the pages counted share the same day: those pages are counted, the list is only a hint to check the website (grouped publication, or dates changed in bulk). method.discovery says what the news pages linked from the home page and the RSS or Atom feeds added to the sitemap; its articlesCounted is the part of total that comes from addresses absent from the sitemap. When method.discovery.truncated is true, the discovery stopped before the end and total is a minimum (a 0 is then not a proven zero, and ci95 is not an upper bound). total is a minimum too when method.sitemapFilesFailed is above 0 (sitemap files that could not be read, even after a second try). method.rateLimited is true when the website refused page reads and the reading was slowed down. Editorial subdomains (newsroom, blog, news and the like, 3 at most, linked from the home page or answering at newsroom. or blog.) are read too and counted in total (scope.hosts lists the hosts read, the main host first): publications.byHost splits the articles counted by host, main host included, and publications.mainHostOnly gives total, perMonth, perWeek, ci95 and monthly without the subdomains (null when no subdomain has a counted article). In publications.bySection, the sections of a subdomain are prefixed by its host (newsroom.example.com/press-releases). A subdomain that blocked the reading is named in scope.hostsFailed: its articles could not be looked for, so a total of 0 is then not a proven zero. publications.byDeclaredType splits the articles counted by the page type the website declares itself (og:type, as the website writes it (case and accents kept, never translated); types equal but for case and accents are one row; beyond 10 rows the smallest declared types join the null row), null for no declared type; the same split is in publications.mainHostOnly. It does not change what total counts. updates counts the articles updated more than one day after their publication, or says why this is not measurable (DYNAMIC_DATES, dates generated when the page is shown; SOURCES_DISAGREE, page and sitemap dates contradict each other; TOO_FEW_DATES).

When a failed analysis had been paid with tokens, billing says what became of them (tokens, the amount charged for it, refunded, true once they were given back to the account that paid). It names no account, and is absent for a free analysis or while the analysis is not failed.

No quota is consumed. The analysisId is random, whoever holds it can read the analysis, which is what makes share links work. Analyses expire after 30 days. Reads that are not attributed to an account are capped at 1000 per IP address and per UTC day, far above any legitimate polling, and crossing it returns 429 READ_RATE_LIMITED with Retry-After.

Input Schema

NameRequiredDescriptionDefault
analysisIdYesThe analysisId returned by the creation call (22 characters).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so extensively: no quota consumed, analysisId is a bearer-like share token, analyses expire after 30 days, and unattributed reads are capped at 1000/IP/day returning 429 READ_RATE_LIMITED with Retry-After. It omits only explicit read-only/non-destructive framing and any idempotency note, but the read-only nature is unambiguous from context.

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

Conciseness2/5

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

The first sentence is well front-loaded, but the body is a single dense block of several hundred words with deeply nested conditional clauses (nested zeros, sampling, section prefixes, declared types) and no headings or structure. Much of the field semantics is necessary given no output schema, but the packaging makes it hard to scan and several passages restate the same 'a 0 is not always a proven zero' rule three separate times.

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?

There is no output schema, so the description must explain the return payload — and it does, covering status/progress fields, every failureCode, all publications.* splits, method.* qualifiers, updates, billing, and expiry. Nothing an agent needs in order to interpret a result 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 coverage is 100% and the schema already documents analysisId (22 chars, returned by the creation call), so the baseline is 3. The description adds only the sharing property ('whoever holds it can read the analysis'), which is useful but not about the parameter's format or role in the call.

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?

Opens with a specific verb+resource ('Read an editorial velocity analysis') and immediately anchors it to the creation call ('Returns the analysis started by `POST /api/v1/tools/editorial-velocity`'), so an agent knows this is the read/poll counterpart of create_editorial_velocity rather than the comparison variant.

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?

Gives an explicit operational loop: while `status` is `pending` or `running`, call again every 5 seconds; on `done` read the results; on `failed` inspect `failureCode` rather than retrying. The prerequisite (analysis must have been created first) is stated up front.

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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