comfy-colab-kit

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

With no annotations, the description carries the full burden, and it does disclose key traits: this is a blocking call that waits for execution and returns image URLs plus metadata. It omits failure behavior — what happens if the graph is invalid, if the queue is busy, or what a timeout produces — which matters for a long-running submit-and-wait tool with a configurable 180s default timeout.

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, front-loaded sentence with no filler: submit, wait, return. It could only be improved by spending one clause on when to prefer a sibling wrapper instead.

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?

There is no output schema, so the description usefully states the return values (image URLs and metadata) and covers both params at full schema coverage. However, with zero annotations and a nested object parameter, the definition should say more about error/timeout outcomes and side effects (enqueueing work on a shared instance) to be 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?

Schema coverage is 100%, so both parameters are already documented in the schema and the baseline is 3. The description adds modest value by framing 'prompt' as a raw workflow graph submitted to a running instance and by tying the wait behavior to the timeout, but it adds no format or validation 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?

The description names a specific verb and resource — 'Submit a raw ComfyUI prompt workflow graph to the running instance' — plus the two follow-on actions (wait, return images). The word 'raw' implicitly separates it from the higher-level gate_txt2img/gate_img2img siblings, but it never names them, so the differentiation is inferred rather than stated.

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 explicit when-to-use or when-not-to-use guidance, and nothing points the agent to gate_txt2img or gate_img2img for simpler cases. The term 'raw ... workflow graph' implies this is the low-level escape hatch when a full graph is needed, which is meaningful but left for the agent to infer.

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?

No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about whether generation is synchronous or long-running, what happens on timeout, whether GPU resources are consumed, or where the resulting image ends up. For a potentially slow generation tool with a configurable timeout_seconds parameter, these omissions matter.

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 well-formed sentence with the action front-loaded and no filler. The parenthetical enumerating image sources duplicates the schema and could be trimmed, but overall it is tight.

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 annotations, no output schema, and seven parameters, the description should explain execution behavior and the nature of the returned artifact. It covers only the input contract, leaving the agent without enough information to set expectations about latency, failure modes, or results.

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 parameters such as seed, preset, denoise, negative_prompt and timeout_seconds are already fully documented in the schema. The description's parenthetical listing image source types (local path, HTTP/HTTPS URL, uploaded ComfyUI filename) restates the schema's image description rather than adding new meaning.

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 uses a specific verb ('Generate') and resource ('a new image variation') and states the two required inputs (reference image + text prompt). It implicitly distinguishes itself from gate_txt2img by requiring a reference image, but never names that sibling 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?

Usage is only implied: an agent can infer this is the right tool when it has an existing image to transform. There is no explicit when-to-use/when-not guidance and no mention of gate_txt2img or gate_generate as alternatives for prompt-only generation.

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?

No annotations are provided, so the description carries the full burden. "Inspect" signals a read-only, side-effect-free operation and the enumerated fields effectively describe what the caller gets back, which is valuable given there is no output schema. It does not state whether polling is cheap, whether it consumes Compute Units, or how fresh the reported progress is, which leaves real behavioral gaps.

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 front-loaded sentence with the action first and the returned data listed after. No filler, no redundancy, and every clause names a distinct piece of state an agent would want.

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 status tool with no output schema, the description supplies exactly the missing piece: what data comes back. Completeness would be higher if it noted the absence of side effects or how often it is reasonable to poll during a long generation.

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 there is nothing for the description to disambiguate. Baseline of 4 applies; no parameter meaning is missing or contradicted.

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?

"Inspect" is a specific verb and the description enumerates the exact resources returned: session state, active profile, progress, remaining time, and Compute Unit balance. This clearly separates it from siblings gate_wake, gate_generate, and gate_stop, though it never names those siblings 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 read-only inspection framing implies the natural use case (checking session state before spending time or Compute Units via gate_generate), but the description never states when to call it versus the alternatives or any preconditions. Guidance is implied rather than spelled out.

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?

With no annotations, the description still discloses the key effects: termination is immediate, hardware is released, and billing stops accruing. It omits whether in-flight work is lost, whether the call is idempotent if the session is already stopped, and that gate_wake is required to resume.

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 with the action first and the motivation second; every clause earns its place with no filler.

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-required-parameter action tool with no output schema, the description covers what happens and why. The remaining gap is recoverability — that the session must be woken again via a sibling — which an agent could infer but is not stated.

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 coverage is 100% for the single optional 'reason' parameter, so the schema already documents it fully. The description adds nothing about the parameter, making the baseline of 3 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?

Names a specific verb and resource: stop the Colab GPU session and release its hardware. The intent is unmistakable against gate_status and gate_wake, 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 clause 'to avoid unnecessary Compute Unit charges' implies the condition for calling it (GPU idle or no longer needed), but there is no explicit when-not-to-use guidance and no instruction to use gate_wake for restarting.

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?

With no annotations, the description carries the full burden; it does disclose the two possible backends (MOSS-Image DeBand or SD 3.5 Large fp8) and that output is returned as full image URLs. It omits important behavior such as whether generation is blocking or queued, whether images persist, and what happens if the wait exceeds timeout_seconds, so the safety/cost profile remains unclear.

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 short sentences, front-loaded with purpose and ending with the return format. Nothing is wasted and no filler or restatement of the name appears.

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 7-parameter generation tool with no annotations and no output schema, the definition is thin: it never explains the response object beyond "full image URLs" and never situates the tool relative to gate_status or gate_img2img. The rich input schema compensates for the parameter side, but the operational context is incomplete.

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%, and every parameter (seed, width, height, preset, prompt, negative_prompt, timeout_seconds) is documented with defaults and semantics in the schema. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the work.

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 ("Generate an image from a text prompt") and identifies the underlying pipeline, so the agent knows exactly what the call produces. It does not explicitly distinguish itself from the close sibling gate_img2img, which is the only thing keeping this from a 5.

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 when/when-not guidance, no mention of prerequisites such as an active profile or server state (gate_status), and no pointer to gate_img2img for image-input work. Usage is only implied by the words "text prompt".

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?

No annotations exist, so the description carries the full behavioral burden, and it discloses very little: no mention of startup latency, GPU quota/cost implications, authentication or Colab account requirements, or what state the instance is left in. 'Join' weakly implies idempotency, but the blocking semantics of the wait parameter are only covered in the schema, not the prose.

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 sentence with no filler, front-loading the action and the target resource before the optional qualifier. Nothing is redundant or buried.

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?

This is a resource-provisioning operation on a cloud GPU with no annotations and no output schema, and the description says nothing about cost, latency, failure modes, or what the caller receives on return. For a tool of this operational weight, one sentence leaves the agent under-informed.

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 coverage is 100%, so the baseline is 3; the description earns an extra point by supplying concrete example profile IDs ('moss-image', 'sd-latest', 'qwen-image') that the schema does not enumerate, giving the agent a usable vocabulary for the profile parameter. It adds nothing for wait, which is already well documented in 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?

The description gives a specific verb pair ('wake or join') and a concrete resource ('shared Google Colab L4 GPU instance'), plus the notion of a model profile. This lets an agent distinguish it from siblings like gate_status and gate_stop, though it never explicitly names those siblings or states the boundary.

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?

'Wake or join' hints that the call is safe whether or not the instance is already up, but there is no guidance on when to call this versus gate_status (to check state) or gate_stop, and no preconditions or exclusions are given. The agent must infer the workflow ordering entirely.

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