AgentCut

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description earns credit by disclosing the return payload (setup steps, supported versions, safety notes, license, stars, check date), which matters because no output schema exists.

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 front-loaded sentence that leads with what is fetched and follows with the payload contents. No filler or redundant restatement of the title.

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 one-parameter read tool with no output schema, listing the returned fields is the key missing piece and the description supplies it. Only the slug's provenance/format and the relationship to search_tools are left implicit.

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 0% and the single 'slug' parameter is undocumented. The description adds only 'by slug', which hints at the identifier's role but gives no format, source, or example; the baseline for a non-empty undocumented parameter set is a 3.

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 gives a specific verb ('get') plus resource ('one tool') and the key that selects it ('by slug'), then enumerates the record's contents. It is clear what the tool returns, though it never explicitly contrasts itself with the sibling search_tools/list_apps beyond implying a single-record fetch.

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 only implied: an agent infers this is the follow-up call once a slug is known from search_tools, but the description names no alternative or condition. There is no statement of when not to use it or how to obtain a valid slug.

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=false, so the safety profile is covered. The description adds useful return-content context (keys, page URLs, tool counts) but says nothing about ordering, pagination, or whether the list is exhaustive.

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?

A single compact sentence with no filler, front-loading the scope ('App categories on AgentCut') before the returned fields. It is efficient, though it lacks an explicit verb to anchor the action.

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, no-output-schema listing tool, the description does the essential work of naming the returned fields. It leaves the categories-vs-apps ambiguity and any ordering/pagination behavior unaddressed, which is a minor gap at 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?

The tool takes zero parameters, so the baseline of 4 applies. The schema has nothing to document and the description correctly adds no parameter claims.

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 identifies the resource ('App categories on AgentCut') and enumerates the returned fields, but supplies no verb and does not match the tool name list_apps cleanly — it is unclear whether it lists apps, categories, or categories-as-apps. It makes no attempt to distinguish itself from get_tool or search_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?

There is no guidance on when to call this versus the sibling tools search_tools or get_tool. An agent is left to infer that this is the enumeration/discovery entry point rather than a search or single-lookup call.

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?

The readOnlyHint=true and openWorldHint=false annotations already establish this as a safe, closed-world lookup, so the bar is lower. The description adds useful framing (it searches MCP servers, CLIs and workflows) but says nothing about result size, pagination, or what happens when no filter matches.

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?

Three sentences, front-loaded with the core purpose, filters, and the sibling pointer. Every sentence earns its place with no redundancy.

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 should convey enough for correct invocation, and it does cover purpose, filters, and how to obtain valid app keys for a read-only search. It stops short of describing the return shape or how results are ordered, a minor omission given the tool's simplicity.

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 only 50%, so the description must compensate, and it largely does: it names app key, setup difficulty, price, DaVinci Resolve edition, and free-text query, mapping to five of six parameters and clarifying the resolve_edition semantics. The limit parameter is not addressed in either place, leaving one small gap.

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 ('Find') plus resource with concrete examples ('AI agent tools (MCP servers, CLIs, workflows) for video and motion apps'). It also names the sibling list_apps for valid app keys, distinguishing this search tool from the app-listing tool without opening a schema.

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?

Explains the filtering options and explicitly routes the agent to list_apps to obtain valid app keys, which is genuine when-to-use guidance. It does not, however, mention when to use get_tool instead for fetching a specific result, so routing among all siblings is incomplete.

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