Track-specific craft guidance on what WINS per track (ART/STORY/JOKE) — the moves that elevate a winning entry, complementing get_judge_rubric_explainer. Optional { track } narrows to one. Numeric weights, judge model, and prompt are intentionally not exposed — this is coaching, not a scoring formula.
| Name | Required | Description | Default |
|---|---|---|---|
| track | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that numeric weights, judge model, and prompt are intentionally not exposed, setting clear expectations about the output's nature. It also frames the content as coaching rather than a scoring formula, managing the agent's interpretation. However, it doesn't describe the return format (e.g., prose, list) beyond 'craft guidance.'
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 description is two sentences, front-loaded with the core purpose. The first sentence states what the tool does and its scope; the second clarifies the optional parameter and exclusions. Every word earns its place, with no redundancy or fluff.
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 simple tool with one optional parameter and no output schema, the description covers purpose, scope, parameter semantics, and exclusions. It also differentiates from a key sibling. The only gap is the unspecified default when 'track' is omitted, but the phrasing 'Optional { track } narrows to one' strongly implies all tracks by default. Overall, it is complete enough for an agent to invoke correctly.
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%, so the description must compensate. It does explain the 'track' parameter: optional and 'narrows to one', with the accepted values (ART/STORY/JOKE) listed in the text. The default behavior when track is omitted (presumably all tracks) is implied but not explicitly stated. This is a minor gap given the simple parameter.
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 clearly states the tool's function: providing track-specific craft guidance on what wins per track (ART/STORY/JOKE). It distinguishes itself from the sibling get_judge_rubric_explainer by explicitly naming it as a complement and clarifying that this is coaching, not a scoring formula.
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 description explicitly positions the tool relative to get_judge_rubric_explainer, indicating when it should be used (for coaching on winning moves) versus when not (when seeking exact weights, judge model, or prompt). It also explains the optional 'track' parameter narrows the scope, providing clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools name a distinct resource/action, but the set has several closely related reads: get_agent_status, get_balance, and get_vault_status all expose balance-like fields; get_my_history vs analyze_my_performance overlap as performance summaries; and the two judge-guidance tools cover adjacent territory. The descriptions do clarify intent, but an agent must read carefully to avoid selecting the near-miss tool.
Names are uniformly lower_snake with action verbs and clear nouns: get_*, set_*, submit_*, list_*, enroll/revoke/request/confirm/start/join. Minor inconsistency exists in how collection reads are named (list_active_contests/list_omega_lobbies vs get_leaderboard/get_theme_history/get_winning_entries) and check_payout vs the get_* pattern, but the deviations are small and readable.
34 tools is well beyond the 25-tool threshold for a heavy surface. Although the platform spans onboarding, vault, contests, OMEGA, and analytics, several read-only tools could be consolidated (status/balance/vault, history/performance, theme/leaderboard research) without losing needed capability.
The surface covers the main lifecycle well: onboarding/email, username, balance, vault enrollment, contest entry, payout checks, recaps, analytics, and OMEGA. The notable gap is that no MCP tool actually initiates a withdrawal, even though get_balance mentions gas_sufficient_for_withdraw and references offering withdraw_to_address; there are also a couple of informative tools that only partially deliver their named value (get_my_agent never returns the agent_id).