nanoodle

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

With no annotations, the description carries the full burden and actually delivers: it discloses the payment model ($0.63 deposit per call in Nano/XNO, settles at actual model cost +20% with change returned, no account needed), cost and latency evidence (last run $0.2601, ~47s, ~$0.27 sampled), the output destination (video saved to disk, file path in result), and non-determinism tied to the seed. The payment-phase mechanics are the main gap, though the schema's _payment_id description partly covers that.

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 pipeline is front-loaded, which is good, but the text then repeats the same flow in a second notation and cuts off mid-word ('Hold both f…'), leaving genuine clutter. Cost and latency figures are useful, but the duplication and truncation cost the definition readability.

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 multi-stage, paid, no-annotation tool with no output schema, the description covers the pipeline, output artifact and its location, cost, latency, and payment settlement — enough for an agent to invoke it knowingly. Remaining gaps are the exact result shape and failure behavior, which are minor given the schema's _payment_id documentation.

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 schema already documents all four parameters including defaults and the _payment_id protocol; baseline 3 applies. The description only gestures at the seed and the two LLM-written prompt parameters, adding 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?

The description lays out a concrete pipeline (seed → LLM still prompt → text-to-image → LLM motion prompt → MiniMax H3 Max i2v at 480p/5s) and the output is stated as a fight/clash video saved to disk. That is specific, but it is presented as a duplicated, partially truncated flow chart ('Hold both f…', then the same steps again in 'text:Fight seed -> llm:...' notation), so the agent must assemble the actual purpose from fragments. No sibling tool is named or contrasted.

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 cue is 'Change the seed; both LLMs rewrite prompts,' which describes a side effect, not when to choose this tool over siblings like photo-to-video, storyboard-relay, or talking-avatar. There is no when-not-to-use, no prerequisite statement, and no alternative named.

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 and does well: it discloses the output shape (image + image + image + text), that media is saved to disk with file paths in the result, the pricing model ($0.19 deposit in Nano/XNO, settled at cost + 20% with change returned), that no account is needed, and measured latency/cost (~2m 4s, last run $0.0652). It omits the payment/watch lifecycle, but that gap is covered by the _payment_id schema description.

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 purpose and the closing cost/latency sentences are front-loaded and earn their place, but the middle pipeline chain is a long, dense arrow/semicolon run that is hard to parse, and the prose summary of it trails off with an ellipsis ('Muse Edit uses the draft…'). It is information-rich but structurally uneven.

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 high-complexity 6-parameter, multi-model, pay-per-call tool with no output schema and no annotations, the description covers output composition, storage, cost, latency, and the internal pipeline. The remaining gaps are selection guidance relative to siblings and the asynchronous payment/watch flow, the latter partially covered by the schema.

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 baseline would be 3, but the description's pipeline notation maps each parameter name to its position and role in the chain (First scene → Muse opens the story, Next beat → stages the next beat, Continuity rules → join, Continuity notes and Draft continuity check → llm checks), adding ordering and dependency semantics the schema doesn't convey.

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 opening sentence gives a specific verb+resource ('Make a two-frame story through a handoff between models') and names every participating model and its role, so the agent understands this is a multi-model two-frame pipeline rather than a single-image generator. It does not, however, explicitly contrast itself with siblings like tiny-world-film or photo-to-video, which would be needed for 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-to-use or when-not-to-use guidance and no mention of the sibling tools that also produce narrative imagery (tiny-world-film, character-sprites). The description explains how the pipeline works internally but never tells the agent which situation should select this tool over its alternatives.

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 provided, the description carries the full behavioral burden and does so well: it discloses the payment model ($0.65 deposit in Nano/XNO, settles at actual model cost + 20%, change returned, no account needed), an observed runtime (~2m 11s, last run $0.27), and that outputs are image + video saved to disk with file paths in the result. It stops short of describing failure modes or what happens if payment is abandoned.

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 pipeline and output information is front-loaded and dense, with each clause carrying real content (stages, outputs, pricing, runtime). It is slightly disorganized and contains a visibly truncated fragment ('Defaul…'), which costs 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 zero-required-param, three-stage generative pipeline with no output schema and no annotations, the description supplies the essential return shape (image + video with file paths) plus pricing and runtime expectations. The two-phase _payment_id handshake is covered by the schema rather than the description, leaving only minor gaps.

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 World, Motion, and _payment_id are already fully documented, including the two-phase payment flow for _payment_id. The description's flow diagram ('text:World -> text:Motion') adds marginal pipeline-mapping meaning but no syntax or format detail beyond the schema, so the baseline 3 applies.

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 conveys that this tool generates a short film by chaining three models (Muse builds a miniature, Wan animates it, Mirelo adds foley), and the pipeline notation clarifies the stages. However, it is narrated through model names rather than stated as a crisp verb+resource, and it never distinguishes itself from siblings like photo-to-video or storyboard-relay.

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 guidance and no named alternatives among the sibling tools. The line 'Compare the silent and sounded takes' hints at a comparison use case but does not tell the agent when to pick this over photo-to-video or storyboard-relay.

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