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Immersive Commons

by com.immersivecommons

Deny a pending Z.ai key request (operator)

ic_admin_deny_key_request
DestructiveIdempotent

Deny a pending Z.ai key request. Marks it denied + removes it from the queue; no key is minted. Two-step: omit confirm (or pass false) for a dry-run preview, confirm: true to apply. Refuses to deny an already-approved request (revoke the minted key at /floor10/agent-console instead). Rate-limited to 20 approve+deny mutations per token per UTC day; dry-run does NOT count. Args: { request_id, reason?, confirm? }. Returns dry-run shape on confirm=false; { ok, request_id, was_pending } on confirm=true. Required scope: admin:llm_keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional note recorded in the audit trail.
confirmNoSet to true to actually deny. When false / omitted, returns a dry-run preview that does NOT mutate and does NOT count against the daily rate limit.
request_idYesThe id of the pending request to deny.

TDQS

A4.9/5.0
Behavior5/5

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

Discloses destructive nature (mutates on confirm), idempotency (refuses to deny already-approved), dry-run behavior, rate limit, scope requirement, and return shapes. 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.

Conciseness5/5

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

Five well-structured sentences, front-loaded purpose, each sentence adds unique value (purpose, effect, flow, constraints, args/returns). No redundancy.

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?

Covers all critical aspects: mutation, preview mode, error handling, rate limits, scope, return shapes. No output schema needed given the return description.

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

Parameters4/5

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

Schema coverage is 100% with good descriptions; description adds context on the two-step workflow and rate limit impact but does not significantly enhance parameter understanding beyond the schema.

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 denies a pending key request, specifies the effect (marked denied, removed from queue, no key minted), and distinguishes from related tools like approve and revoke.

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 describes the two-step process (dry-run vs. confirm), warns against denying already-approved requests with an alternative action, and details rate limits (20 per token per UTC day, dry-run not counted).

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