Use this when the user asks about access, subscription, remaining limits, or usage («что мне доступно», «сколько осталось», «моя подписка»). Показывает доступ: подписка, доступные советники, потрачено за месяц, лимиты.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| limits | Yes | ||
| this_month | Yes | ||
| subscription | Yes | ||
| advisors_available | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": false,
+ "properties": {
+ "advisors_available": {
+ "minimum": 0,
+ "type": "integer"
+ },
+ "limits": {
+ "additionalProperties": false,
+ "properties": {
+ "calls_per_min": {
+ "minimum": 1,
+ "type": "integer"
+ },
+ "consultations_per_day": {
+ "minimum": 1,
+ "type": "integer"
+ }
+ },
+ "required": [
+ "calls_per_min",
+ "consultations_per_day"
+ ],
+ "type": "object"
+ },
+ "subscription": {
+ "additionalProperties": false,
+ "properties": {
+ "active": {
+ "type": "boolean"
+ },
+ "expires_at": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "plan": {
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "active",
+ "plan",
+ "expires_at"
+ ],
+ "type": "object"
+ },
+ "this_month": {
+ "additionalProperties": false,
+ "properties": {
+ "calls": {
+ "minimum": 0,
+ "type": "integer"
+ },
+ "tokens": {
+ "minimum": 0,
+ "type": [
+ "integer",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "calls",
+ "tokens"
+ ],
+ "type": "object"
+ }
+ },
+ "required": [
+ "subscription",
+ "advisors_available",
+ "this_month",
+ "limits"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds value by specifying exactly what content is shown (subscription, advisors, spent details, limits), which goes beyond the annotations' abstract hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the usage trigger, followed by a clear list of displayed information. Every sentence serves a purpose, and the bilingual examples efficiently convey intent without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with an output schema present, the description provides sufficient context: it explains when to invoke the tool and what result the user will see. The sibling tools are all advisor-related, and this description clearly positions the tool as the account-access counterpart, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so per the rubric the baseline is 4. The description does not need to explain parameter semantics since there are none; it instead clarifies what the tool reports, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to show access, subscription, available advisors, monthly usage, and limits. It provides a specific verb ('shows') and resource (access/subscription), and it distinguishes itself from sibling tools (ask_advisor, find_advisor, list_advisors) by focusing on the user's account status rather than advisor interactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage triggers: 'Use this when the user asks about access, subscription, remaining limits, or usage' with concrete example phrases. However, it does not mention when NOT to use it or explicitly compare with alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: listing the catalog, finding an advisor for a task, asking a specific advisor a question, and checking access. The overlap between find_advisor and list_advisors is minimal and well-explained, so no confusion arises.
Three tools follow the verb_noun pattern (ask_advisor, find_advisor, list_advisors), but my_access deviates by being a possessive phrase rather than a verb-based name. This is a minor inconsistency in an otherwise predictable scheme.
With only 4 tools, the server is tightly scoped to the core advisory workflow: discover, match, consult, and manage access. Every tool earns its place, and the count feels appropriate for the domain.
The tool set covers the full user journey: listing available advisors, finding the best match for a task, asking an advisor with session continuity, and checking access/limits. There are no obvious gaps for the stated purpose of providing business methodology advice.