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alexalexalex222

super-loop-mcp

execute_full_test

Launches 3-5 frontier workers to run a full test, captures outputs, and validates against allowlisted binaries. Requires opt-in environment variable to enable execution.

Instructions

SUPERVISOR-EXECUTED full test (off by default; opt in with env SUPER_LOOP_ALLOW_EXEC=1). Sling itself LAUNCHES 3-5 allowlisted frontier workers (claude/codex/glm/gemini binaries on PATH) via execFile (never a shell), captures each output, and feeds the tool-captured bytes through the same gate as test_hypothesis — so there is no model-supplied run-log to fabricate. A failed/timed-out/non-allowlisted launch is an invalid batch and does not count toward retirement. Without the opt-in this returns BLOCKED (EXEC_DISABLED) and you record run-logs via artifact_record + test_hypothesis instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYes
promptYesthe loop + task the launched worker should actually run
routesYes3-5 frontier worker routes to launch (each must map to an allowlisted binary)
timeoutMsNoper-worker hard timeout (default 600000)
hypothesisIdYes
Behavior4/5

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

No annotations exist, so the description carries full burden. It discloses critical behavioral traits: execFile (no shell), allowlisted binaries, captura output and gate processing, blocking behavior without opt-in, and failure handling. However, it does not describe the return format for successful executions, leaving some ambiguity.

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 is informative but somewhat lengthy. It is well-structured: front-loaded with the core purpose and opt-in requirement, followed by operational details and alternatives. Every sentence adds value, though some could be more succinct.

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?

Given no output schema, the description does not fully specify the return value for successful execution. It mentions blocking behavior but not the structure of success results. The reference to 'same gate as test_hypothesis' provides some context but is ambiguous. Overall, sufficient but could be more complete.

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 description coverage is 60% (3 of 5 parameters have descriptions). The tool description adds minimal new information beyond the schema: it mentions 'routes' must be allowlisted and 'prompt' is the task, but these are already in the schema. It does not explain 'runId' or 'hypothesisId'.

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 function: it executes a full test by launching 3-5 allowlisted frontier workers via execFile, captures outputs, and processes them. It distinguishes itself from test_hypothesis by noting that it launches real workers and that without opt-in it blocks, directing to alternative tools.

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 states the tool is off by default and requires an environment variable opt-in. Provides clear guidance on when to use (with opt-in) and when to use alternatives (without opt-in, use artifact_record + test_hypothesis). Also clarifies that failed launches do not count toward retirement.

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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