QuotaTick

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-source traits are covered. The description adds that a probability estimate and an official-source live link are produced, which is useful output context, but it says nothing about data freshness, caching, or how the probability is derived.

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?

One sentence, front-loaded with the question it answers and then listing the returned facts. The trailing enumeration is somewhat list-like but every item earns its place since no output schema exists.

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?

With no output schema, the description usefully enumerates the return fields (reset flag, last reset time UTC, hours since, 24h probability, source link), which is exactly the burden it must carry. Minor gaps remain around edge cases such as unknown tools or missing data.

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?

Schema description coverage is 100% with a fully enumerated enum, so the schema already documents the single parameter completely. The description's 'for one AI coding tool' adds no meaning beyond the schema, making the baseline 3 correct.

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 states a precise verb+resource: answering whether a single AI coding tool reset its usage limits in the last 24 hours, and enumerates the exact fields returned. It is unmistakably a single-tool status lookup, though it never names or contrasts with its siblings list_events/list_tools.

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?

Usage is implied by the framing question ('did <tool> reset its usage limits today?'), which tells the agent the scenario this answers. However, there is no explicit when-to-use, when-not-to-use, or alternative-routing guidance relative to list_tools or list_events.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-source behavior are covered. The description adds genuinely new behavioral detail beyond that: results are ordered newest first and each entry carries an official source link. However, it says nothing about pagination, truncation by the limit parameter, or result volume.

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?

Two tight sentences, front-loaded with the core action and the result shape before the optional filtering note. The event-type enumeration is slightly listy but earns its place by defining scope.

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 simple read-only listing tool with full schema coverage and no output schema, the description covers scope, ordering, item contents, and filters adequately. Missing pieces (pagination behavior, what happens when no filter is supplied, result size vs default limit) are minor for this complexity level.

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?

Schema description coverage is 100%, so tool, group, and limit are already fully documented including enums and defaults. The description only restates the tool/group filters at a high level and omits the limit parameter entirely, adding little semantic value over the schema.

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?

States a specific verb (List) and resource (recent events for AI coding tools) and enumerates the event categories covered: limit resets, promotions/free credits, limit changes, discontinued plans. That enumeration makes it easy to tell apart from get_reset_status (singular status) and list_tools, though neither sibling is named explicitly.

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 only usage guidance is 'Optionally filter by tool and by group,' which implies this is the browse-all endpoint. It never says when to prefer it over get_reset_status or when a filter is required, so the agent must infer routing from the scope alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations declare readOnlyHint and openWorldHint, and the description adds meaningful return-value semantics (last reset time in UTC, hours since, 30-day reset count, 24-hour reset probability) plus 'Takes no arguments.' It does not mention ordering, result size, or pagination, but for a small fixed enumeration that is minor.

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?

Front-loaded with the verb and scope, then the returned fields, then the usage hint. No filler sentences; every clause carries either identifying or routing information.

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?

No output schema exists, so the description carries the return-value burden and does so thoroughly, and a zero-arg read-only list tool needs nothing more (no auth, mutation, or pagination concerns).

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?

Zero parameters, so the baseline is 4; the description explicitly confirms 'Takes no arguments,' matching the empty schema with no ambiguity.

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?

Specific verb ('List') plus named resource ('every AI coding tool QuotaTick tracks') with concrete examples (Codex, Claude Code, Cursor, Copilot) and the exact fields returned. This is clearly distinguishable from get_reset_status (single-tool detail) and list_events.

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?

Explicitly states the use cases: 'find a tool's slug or to compare tools,' which tells the agent when to reach for this versus a per-tool lookup. It stops short of naming get_reset_status as the alternative for a specific tool's status, so no explicit exclusion is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.