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super-loop-mcp

initialize_loop_run

Confirms the task before initiating a self-improving agent loop. Asks clarifying questions once, then accepts answers to start the run without repeating.

Instructions

Ask-once gate. Confirms the task before any loop runs. If the task is underspecified, returns one brief explanation plus a few short questions once (goal; PATH — improve an existing loop / discover-or-find a loop, optionally scouting a public loop library / mine your whole history; the loop or domain to start from; corpus scope — whole history or a set number of loops, and best-first vs in-order; what "better" means; any task-specific hard limit; and a deeper-explanation offer); call again with { answers } to begin. It never asks the operator to choose the model, promotion mode, benchmark policy, deterministic-vs-subjective routing, or the standing guarantees — the supervisor decides those from the task. Stores every user message locally with a sha256 hash. After initialization it does not ask again or mark the campaign complete; the operator remains the stop condition and the dashboard stays available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNowhat to improve/build
modelNofrontier route; defaults to claude-opus-4-8
runIdNoreuse to continue a run; omit to create one
configNo{ failurePatience(10-15), comparisonRule, promotion:{...}, mode }
answersNoanswers to the ask-once questions
userMessagesNoverbatim operator messages — stored + hashed for the hook
acceptanceCriteriaNo
Behavior4/5

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

With no annotations, the description carries full burden. It discloses key behaviors: stores messages with sha256 hash, asks once, never asks again after initialization, operator remains stop condition, dashboard stays available. This is comprehensive but could mention idempotency or side effects more explicitly.

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?

The description starts with a concise summary ('Ask-once gate') but then expands into a dense paragraph. While it is informative, the length could be slightly reduced by separating key points. Still, it remains focused and structured.

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

Completeness4/5

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

Given 7 parameters, nested objects, no output schema, and many siblings, the description provides enough context for usage. It explains the initialization flow, constraints, and operator involvement. Lacks details on return values or state persistence, but overall adequate.

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?

Schema coverage is 86%, so baseline is 3. The description adds context (e.g., 'answers' are responses to ask-once questions, 'userMessages' stored and hashed), but the schema already covers most parameters. Additional value is moderate.

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 the tool's purpose: 'Ask-once gate. Confirms the task before any loop runs.' It explains the interaction flow (returns questions, then call again with answers), which distinguishes it from sibling tools like loop_start or continue_run that handle later stages.

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

Usage Guidelines4/5

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

The description implies when to use (before a loop runs) and clarifies what the tool will not ask (model, promotion mode, etc.), guiding the agent on what inputs are relevant. While it does not explicitly name alternatives, the context of the workflow is clear.

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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