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OperStack

Read your own AI visit counter

ai_visits
Read-onlyIdempotent

Reports how many visits each AI assistant sent to a site that runs the free OperStack counter. Needs the private token from the counter link, which only the site owner has. Returns visit counts per assistant, not individual visitors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoHow many days back to report. Default 90.
tokenYesThe private token from your counter link (the part after t=)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent and non-destructive behavior, so the description's job is narrower. It still adds real context beyond them: the access constraint (a private token only the site owner holds) and the aggregation granularity (per-assistant counts, not individual visitors), which tells the agent what the data can and cannot answer.

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

Conciseness5/5

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

Three short sentences, front-loaded with what is reported, then the prerequisite, then the data granularity. No filler and nothing buried.

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

Completeness4/5

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

For a read-only two-parameter tool with no output schema, the description covers purpose, prerequisite and return semantics (aggregate counts per assistant). It does not describe the default 90-day window or response shape, but the schema covers the window and the omissions are minor at this complexity.

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 documents both parameters, including that token is the part after 't='. The description reinforces who can supply the token but adds no syntax or format detail for the days window, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (reports/counts) and resource (AI assistant visits to a site using the OperStack counter), which is plain and concrete. It does not explicitly differentiate itself from siblings like my_visibility or who_instead, but the resource is distinct enough that an agent can separate them.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the tool only works for a site running the OperStack counter and requires the private owner token. There is no explicit when-to-use versus when-not, and no alternative tool is named for adjacent questions such as overall visibility.

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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