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alexalexalex222

super-loop-mcp

human_review_request

Queue changes for operator approval or list pending review items. Human decisions are handled on the dashboard only, keeping automation loops running without blocking.

Instructions

Queue a change for the operator’s Approve/Sludge dashboard or list pending items. This tool CANNOT resolve human review; approval/sludge is dashboard-only. Never blocks deterministic lanes — the loop keeps running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemNo
notesNoignored/refused; human decisions are dashboard-only
runIdYes
actionNoadd | list (resolve is refused: dashboard-only)
decisionNoignored/refused; human decisions are dashboard-only
reviewIdNoaccepted only for rejected legacy resolve attempts
Behavior3/5

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

With no annotations, the description carries full burden. It discloses that the tool cannot resolve and is dashboard-only, and that it never blocks lanes. However, it lacks details on side effects, auth requirements, or return behavior.

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 three sentences long, front-loading the main purpose and key constraints. Every sentence adds value with no redundancy or fluff.

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

Completeness3/5

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

For a tool with 6 parameters and no output schema, the description covers core constraints but omits return format, pagination for list, and behavior when queuing. Given sibling tools, more context would help, but the essentials are present.

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

Parameters3/5

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

The schema already covers 67% of parameters with descriptions (notes, action, decision, reviewId). The description reiterates the 'list' vs 'add' actions but adds little beyond the schema. It does not explain nested 'item' object fields.

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

Purpose4/5

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

The description clearly states the tool queues changes for the operator's Approve/Sludge dashboard or lists pending items. It distinguishes from resolve actions, but does not explicitly differentiate from sibling tools like update_dashboard or cycle_decision_request.

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

Usage Guidelines3/5

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

The description provides guidance on when to use (add to dashboard or list) and when not to (cannot resolve). It also notes that it never blocks deterministic lanes. However, it does not mention alternatives or specific sibling tools for comparison.

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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