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Score a hackathon submission (judge)

ic_hack_judge_score

Record your scores for one team. criteria is a map of rubric key to 0..10 (values are clamped, non-numbers rejected rather than coerced). The published rubric is 100 points across five WEIGHTED bands, and each key has its own ceiling: track 0..30 (the track's agent-native criterion), runs 0..25 (it runs), surface 0..20 (surface quality / coordination design), product 0..15 (it lands in the product), demo 0..10. Send those keys or the weighting is lost. Any other key is capped at 10. max_total on the result is the denominator actually used. Re-scoring the same team replaces your previous score. Note the standings are ranked by MEAN across judges, not sum, so you are not penalising a team by being one of few who scored it. Your score is advisory input to a human decision, not the decision. ORGANIZERS ONLY: on_behalf_of records the score a real judge gave, attributed to that judge's member id, with entered_by naming who typed it. It exists because an external panel deliberates in the room and its members hold no IC account; it refuses a caller who does not run this event and a target who is not a judge here, so it cannot invent a scorer. Args: { eid?, team_id, criteria: {..}, notes?, on_behalf_of? }. Returns: { ok, score }. Required scope: hack:judge + judge or organizer role.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eidNo
notesNoFeedback the team will see after results.
team_idYes
criteriaYesRubric key -> 0..10.
on_behalf_ofNoOrganizer only: the judge member id this score belongs to.

TDQS

A5/5.0
Behavior5/5

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

Given only generic boolean annotations, the description carries the behavioral burden and does so thoroughly: it reveals clamping and non-coercion of values, per-key ceilings and weighted bands, replacement on re-score, MEAN-based rankings, the advisory nature of the result, and the attribution model for on_behalf_of. This goes far beyond the annotations and leaves no major hidden side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every clause earns its place: it is front-loaded with the core action, then covers criteria semantics, replacement behavior, ranking context, and the specialized organizer path in a logical sequence. There is no filler and no unnecessary repetition of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex scoring tool with no output schema, the description is complete: it explains scoring bands, the actual denominator via max_total, replacement semantics, the MEAN-ranking implication, the advisory role, the organizer path, and the required scope. An agent has everything needed to invoke it safely and correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only describes criteria, notes, and on_behalf_of; the description adds critical semantics for the criteria map—allowed values, clamping, per-key ceilings (track/runs/surface/product/demo), and unknown keys being capped at 10. It also clarifies the exact role of on_behalf_of and who may set it. This meaningfully exceeds the schema's own parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening line uses a specific verb and object—'Record your scores for one team'—and immediately establishes that this is a scoring/write action, not a read or list tool. It matches the title and no sibling tool overlaps with it (ic_hack_judge_list is the lookup counterpart). The judge-specific scope is clear even without the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly scopes usage to judges/organizers with 'Required scope: hack:judge + judge or organizer role.' It gives a conditional specialized path for organizers via on_behalf_of and explains the safety rejection: it 'refuses a caller who does not run this event and a target who is not a judge here.' It also tells agents that re-scoring replaces the prior score and that scores are advisory, which directly informs when and how the tool should be called.

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools are clearly scoped to distinct actions (e.g., ic_hack_apply vs. ic_hack_register, ic_rooms_create vs. ic_rooms_join). A few pairs could confuse an agent: floor10_submit_highlight vs. floorcast_push both submit HighlightStories but to different queues, and ic_directory_search / ic_agent_directory_lookup / ic_admin_list_members overlap in searching members. Overall, the long descriptions help disambiguate, but the volume requires careful reading.

Naming Consistency3/5

The dominant pattern is ic_<domain>_<verb>_<object> (e.g., ic_admin_list_pending_events, ic_headsets_checkout), but there are notable deviations: floor10_* and floorcast_* prefixes break the ic_ convention, and a few tools use noun-style names (ic_health, ic_capabilities, ic_donations_total). Verb placement also varies (get_* vs *_get, e.g., ic_get_my_membership vs. ic_membership_set_profile). Still, most names are readable and predictable.

Tool Count1/5

175 tools is an extreme count for a single MCP server, far beyond the 50+ threshold that indicates an unwieldy surface. While the platform covers many domains (events, files, hackathon, headsets, prints, rooms, etc.), bundling everything into one server makes discovery and selection difficult. This would be better split into several narrowly-scoped servers.

Completeness4/5

The tool set covers nearly every lifecycle for each domain: CRUD for files/folders, full hackathon admissions and judging, headset lending with waivers and incidents, print farm submission and handoffs, and room coordination. Minor gaps exist: no delete for files/folders, no cancel for events, and some actions (like revoking a Z.ai key or tearing down a room) are explicitly left to human console use. Overall, the surface is remarkably comprehensive for the stated scope.