GetItDone

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

Annotations already declare destructiveHint=true, openWorldHint=true and idempotentHint=false, so the agent knows this is an unsafe, non-repeatable, world-touching operation. The description adds the useful fact that code runs in a sandbox, but does not disclose that the external_ calls reach real systems with real side effects, nor any timeout, resource, or library constraints.

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 sentences, zero filler, front-loaded with what the tool does and followed immediately by the reason to choose it over making calls individually.

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?

Covers purpose, execution model, and the calling convention for external tools; an output schema exists so return values need not be described. It could say more about sandbox limits (available libraries, timeouts, whether side effects persist), which matters for a destructive, open-world tool.

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?

Only one parameter and schema description coverage is 100%, so the schema already defines the `code` body, the external_<toolName>(args) calling convention, and that the returned value becomes the result. The description reinforces the orchestration intent but adds no syntax or format detail beyond 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 (run/execute) and resource (a TypeScript program in a sandbox), plus the mechanism that makes it distinctive: calling external_<toolName> functions declared by search_tools. An agent can distinguish this from its only sibling, search_tools, without opening the 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?

Gives a clear positive trigger ('orchestrate multiple tool calls ... looping, branching, combining results, in one round trip') and points to search_tools as the prerequisite for discovering the external_ functions. It stops short of an explicit exclusion, e.g. that a single simple call should be made directly rather than through code execution.

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 readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond them — the return artifact is TypeScript function stubs, and broad queries degrade to a one-line index — but says nothing about size limits, cost, or what the index lines contain.

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 sentences, front-loaded with purpose, then the two modes in a single parallel clause. Tight and waste-free; slightly dense packing of examples and mode logic in one sentence costs it a point.

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-only discovery tool with an output schema, this covers purpose, both modes, and the shape of both responses. An agent has everything needed to call it correctly on the first try.

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 the single query parameter is already fully documented, including the exact-name vs. word-match fallback. The description restates the same semantics with an example rather than adding format or edge-case detail beyond the schema, which puts it at the baseline.

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 and resource ("Find the GetItDone tools this credential can reach") and immediately names the two operating modes. It also ties itself to its only sibling by saying results are TypeScript stubs for use inside execute_typescript, so an agent can tell the two apart 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?

Explicitly distinguishes the two invocation modes: pass tool names to get signatures, omit the query for a full index. What is missing is an explicit exclusion/alternative rule against execute_typescript (e.g. when to stop searching and start executing), so it is clear context rather than full when/when-not guidance.

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