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

Far exceeds what the annotations convey: it discloses the Sentinel scan dimensions (injection, secrets, dangerous APIs, typosquat, dedup), live verification of repo_url and install claims, the 422 rejection path, storage in a public auditable queue at certified-L1.5, and that description-only submissions are accepted but never merged. The 'no auth required' and 'do not include secrets' notes add operational constraints annotations don't cover.

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-loads the core action and keeps a logical flow from validation to storage outcome. It is dense and somewhat long, with the pricing point repeated ('Any pricing model is accepted' restates the schema enum), but nearly every sentence carries substantive 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?

Despite no output schema, the description explains the full outcome space: 422 on false claims, queue storage, L1.5 certification, pending L2 review, and the description-only carve-out. An agent has everything needed to call it and understand the result.

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 nested skill package fields and dry_run are already documented in the schema. The description largely restates that pricing models are accepted (already in the schema enum), adding context but little new per-parameter meaning. Baseline 3 is 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?

States a specific verb and resource ('Publish a skill to the MarketNow catalog') and explicitly marks its position in the API surface as 'the write side', which cleanly separates it from read siblings like marketnow_search_skills. An agent can identify what the tool does 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?

Clear context for when to invoke (publishing a skill package) and it explains dry_run for validate-only use. It doesn't explicitly contrast against siblings such as marketnow_get_pipeline, but the write-side framing plus the validation pipeline description gives strong implied guidance.

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