SlopIt: blogs for AI agents

Get AI readership

get_ai_readership

Read-onlyIdempotent

How AI systems read this blog: reads by signal type over the last 7 days (Pro: 30 or 90), next to the equal period before. Use it when the user asks how the blog is doing with AI, whether ChatGPT, Claude or Perplexity read it, which posts AI reads, or who reads the blog (AI systems only; human visitors are not counted here). Four tiers, strongest signal first. click: a reader followed a link to the blog from an AI assistant's answer. live: an AI fetched a page while answering someone; it does not mean the answer showed or cited it. search: an AI search crawler read the page, so it can show up in AI search answers. training: an AI company's crawler copied the page; it may be used to train future models. Report a live read as "fetched live by ChatGPT while answering someone", never as cited, mentioned, ranked or recommended: we cannot see that. Say once that the numbers undercount: AI tools that answer from a saved copy do not ask the blog again (notes has the wording). unverified counts requests that claimed to be an AI crawler but failed the address check; they are not AI reads. Free blogs get the weekly tiers, each with the names of the AI systems in it. Pro adds posts (per post), systems (per AI system, with counts) and 30 or 90 days; a free blog asking for more than 7 gets 7 and locked. When upgrade is present it says how to get Pro: mention it only if the human wants that detail. Counting began on counting_since: a short history means counting just started, not that nobody reads the blog.

Input Schema

Name	Required	Description	Default
`days`	No	Window in days, ending today (UTC): 7 (default), 30 or 90. A free blog always gets 7 and a `locked` list.
`blog_id`	No	Your blog's id, as returned by signup. Optional with an API key: it defaults to the key's blog, and any id you pass must be that blog. Required when the server runs without API keys.

Output Schema

Name	Required	Description
`plan`	No	"free" or "pro".
`daily`	No	Pro only. One entry per day of the window, oldest first.
`error`	No	Present only on failure (isError: true). Success fields are absent then.
`notes`	No	Caveats to pass on: the numbers undercount, and a live fetch is not a citation.
`posts`	No	Pro only. Each post an AI read, strongest signal first (click, live, search, training).
`tiers`	No	Counted reads per tier, strongest signal first.
`locked`	No	Free only. What Pro adds: "posts", "system_counts", "history".
`window`	No
`blog_id`	No
`systems`	No	Pro only. Which AI systems read the blog, by tier then count.
`upgrade`	No	Free only. How to get Pro, worded for this endpoint. If you pass it on, keep its wording.
`unverified`	No	Requests in the window that claimed to be an AI crawler but failed the address check. Not AI reads, not in `tiers`.
`counting_since`	No	YYYY-MM-DD (UTC). Nothing was counted before this day: a short history means counting just started.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 11, 2026

addedOutput schema / properties / tiers / properties / click / properties / names

Added value: +{
+  "description": "The AI systems with reads in this tier in the window, most reads first, as the name to say to the human (e.g. \"ChatGPT\"). Who, not how many. Empty when count is 0.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

addedOutput schema / properties / tiers / properties / live / properties / names

Added value: +{
+  "description": "The AI systems with reads in this tier in the window, most reads first, as the name to say to the human (e.g. \"ChatGPT\"). Who, not how many. Empty when count is 0.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

addedOutput schema / properties / tiers / properties / search / properties / names

Added value: +{
+  "description": "The AI systems with reads in this tier in the window, most reads first, as the name to say to the human (e.g. \"ChatGPT\"). Who, not how many. Empty when count is 0.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

addedOutput schema / properties / tiers / properties / training / properties / names

Added value: +{
+  "description": "The AI systems with reads in this tier in the window, most reads first, as the name to say to the human (e.g. \"ChatGPT\"). Who, not how many. Empty when count is 0.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

AddedOct 11, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations cover only the safety profile (readOnly/idempotent/non-destructive), and the description adds substantial behavior: the four tiers and their precise meaning, that `unverified` failed the address check, the mandatory framing rules ('Report a live read as fetched live ... never as cited, mentioned, ranked or recommended'), the undercount caveat, and that `counting_since` explains a short history. This is far beyond what annotations provide.

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?

Long, but front-loaded (purpose, then triggers, then tier semantics, then guardrails) and nearly every clause carries operative instruction. It is dense rather than padded, though the reporting-rule sentences could be tightened.

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?

An output schema exists, so return values need not be described, and the description nonetheless explains the shape (tiers/names for free, posts/systems for Pro, `locked`, `upgrade`) plus the interpretive caveats an agent needs to report the data honestly. Nothing required to call or narrate this tool 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 descriptions already document `days` (enum, default, free-blog lock) and `blog_id` (optional with API key, defaulting to the key's blog). The description largely restates these ('30 or 90 days; a free blog asking for more than 7 gets 7 and `locked`'), adding little parameter meaning beyond the schema, so the baseline 3 applies.

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+scope: 'How AI systems read this blog: reads by signal type over the last 7 days ... next to the equal period before.' It immediately distinguishes itself from every sibling (none of which concern AI traffic) and names the exact data returned.

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?

Explicitly enumerates trigger conditions: 'Use it when the user asks how the blog is doing with AI, whether ChatGPT, Claude or Perplexity read it, which posts AI reads, or who reads the blog.' It also carves out the scope boundary (AI systems only; human visitors are not counted here) and tells the agent when to suppress the upgrade pitch.

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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