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get_trial_status

Check whether a GnosisLab trial is running, completed, or failed and retrieve its persisted executor output for auditing or next-step decisions.

Instructions

Check the status of a running or completed trial.

Returns: {"trial_id": ..., "status": "running"|"completed"|"failed", "executor_output": ...} # raw output once finalized

executor_output is persisted on the trial row at finalize time — it survives server restarts (the executor's async cache does not).

artifact_path is a transient staging directory — its contents are captured content-addressed into SQLite at finalize and the files deleted. An empty artifact_path is by design, not lost data: recover contents via get_blob / the code:// resource.

Enforcement: commitment 1 — the loop is the unit (orphan check).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trial_idYesID of the target trial.
programme_idYesID of the target research programme.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNo
reasonNo
statusNo
progressNo
trial_idNo
cancelledNo
started_atNo
eta_secondsNo
finished_atNo
artifact_pathNo
elapsed_secondsNo
executor_outputNo
duration_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.28

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and largely meets it: it discloses that executor_output is persisted on the trial row and survives restarts, that artifact_path is a transient staging directory whose contents are captured content-addressed into SQLite, and that an empty artifact_path is by design rather than data loss. It does not cover permission requirements, error behavior for a missing/invalid trial_id, or whether the call blocks — minor gaps against an otherwise rich disclosure.

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?

Purpose is front-loaded in a single sentence, and the subsequent paragraphs each carry distinct payload (return shape, persistence semantics, artifact lifecycle, enforcement note) with no filler. The Returns block partially overlaps the output schema, but the surrounding lifecycle notes are not derivable from it.

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?

An output schema exists, so the return-value explanation is partly redundant, yet the description adds persistence and artifact-recovery context that the schema cannot express. Combined with the enforcement note about the orphan check, it is close to complete; the missing pieces are error/permission behavior rather than core call semantics.

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 100%, so both parameters (trial_id, programme_id) are already documented in the schema. The description adds no syntax, format, or relational detail beyond what the schema provides, so the baseline 3 applies.

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 opens with a specific verb+resource: 'Check the status of a running or completed trial.' An agent can tell it inspects a specific trial rather than enumerating (list_trials) or blocking (wait_trial). It never names those siblings explicitly, so differentiation is inferred rather than stated.

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?

Scope is implied by 'a running or completed trial', and the note routes artifact recovery to 'get_blob / the code:// resource', which is a genuine alternative-pointer. But there is no explicit when-to-use guidance relative to wait_trial, list_trials, or correct_trial_status, so the agent must infer the boundary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.