Skip to main content
Glama

run_log

Retrieves a run's status and last log lines, live while it executes; monitor progress and diagnose failures in ML/QSAR/GNN pipeline runs.

Instructions

Return the status and the last lines of a run's log (live while it runs).

Input Schema

NameRequiredDescriptionDefault
tailNoLast N lines
run_idYesRun id

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It does disclose that output is live during execution and includes status alongside log tail, but it omits details like permissions, truncation behavior, or handling of finished/failed runs. Given the presence of an output schema, the return format gap is mitigated, making a 3 appropriate.

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?

A single, efficient sentence that front-loads the action and resource. The parenthetical adds a useful nuance without bloat, though there is minimal structure beyond that one sentence.

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?

For a simple two-parameter read tool with a fully described schema and an output schema, the description covers the essentials: what it returns and when it is live. Missing details (e.g., behavior on completed runs) are minor given the structured coverage.

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 (run_id and tail) are already documented in the schema. The description adds no extra meaning about the tail parameter's behavior or run_id format, 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 states a specific verb ('Return') and resource ('status and the last lines of a run's log'), making the tool's function immediately clear. It does not explicitly differentiate itself from siblings like log_run or list_runs, which keeps it just short of a 5.

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 parenthetical '(live while it runs)' hints that the tool can be polled during an active run, which is useful implied guidance. However, there is no explicit when-to-use vs. when-not-to-use guidance or reference to alternatives such as log_run, leaving usage to inference.

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