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Immersive Commons

by com.immersivecommons

Approve a pending member-event-request draft (operator)

ic_admin_approve_event
Idempotent

Approve a pending 'save the date' event draft: flows the wrapped KioskEvent into floor10:events:approved (dedupe-prepend, keep newest 50), drops it from the pending queue, and writes an audit entry. The kiosk events page merges approved drafts with the live Luma list (live wins on the shared slug); once the real Luma event goes live, ic.kv_push.push_events prunes the draft automatically. This NEVER creates a public Luma event — it posts a no-RSVP save-the-date card; IC staff create the live Luma event from the request detail afterward. Two-step: omit confirm (or pass false) for a dry-run preview that returns what the call would do without mutating; pass confirm: true to actually apply. Idempotent: a missing / already-handled / TTL-expired id returns ok:false (and cleans the stale list pointer). Rate-limited to 20 approve+reject mutations per token per UTC day; dry-run calls do NOT count. Args: { id, confirm? }. Returns: dry-run shape on confirm=false; { ok, id } on confirm=true. Required scope: admin:events_review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe pending event id to approve — the draft slug (e.g. 'demo-night-a1b2c3'), as returned by ic_admin_list_pending_events / ic_events_request.
confirmNoSet to true to actually mutate. When false / omitted, returns a dry-run preview that does NOT change state and does NOT count against the daily rate limit.

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (idempotentHint, destructiveHint), the description adds rate limiting, dry-run behavior, side effects (cleaning stale pointers), and scope requirements. No contradictions with annotations.

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

Conciseness4/5

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

Somewhat verbose but every sentence adds value. Front-loaded with core purpose and logically organized. Could be slightly more terse, but clarity is not sacrificed.

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?

With no output schema, the description covers return shapes for both modes, prerequisites, side effects, rate limits, and idempotency. Comprehensive for a complex mutation tool.

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?

Despite 100% schema coverage, the description adds crucial context: explains id as draft slug from list_pending_events, and confirm as dry-run toggle with rate limit exemption. This significantly aids agent understanding.

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 description clearly states it approves a pending 'save the date' event draft, specifies the action (flows into approved, drops from pending, writes audit), and distinguishes from creating a Luma event. It contrasts with sibling tools like ic_admin_reject_event by focusing on approval.

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?

Explicitly explains when to use (approve pending drafts), when not to (does not create Luma events), and the two-step dry-run vs confirm process. Idempotency and rate limits are clearly stated, providing full guidance for correct invocation.

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.

Resources