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ateam_get_metrics

Get execution metrics — timing, tool stats, bottlenecks, signals, and recommendations. (Advanced.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idNoOptional: deep analysis for a specific job
actor_idNoOptional. WHO is asking. A job belongs to an actor and Core enforces that on per-job reads, so a tenant key alone is refused. Usually unnecessary — the session remembers the actor from ateam_conversation/ateam_test_skill. Pass it to inspect a job run by a DIFFERENT actor (e.g. a real user's).
chain_idNoOptional: deep analysis for the job behind a CHAIN id — what ateam_conversation returns and what you actually hold. Resolved to the job for you.
skill_idNoOptional: recent metrics for a specific skill
solution_idYesThe solution ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden, and 'Get' reasonably implies a read-only operation. However, it does not mention auth enforcement, side effects, or how the optional job_id/chain_id 'deep analysis' paths change behavior; those details are left to the schema.

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 a single sentence that front-loads the action and resource, then uses a scannable comma-separated list of result categories. There is no filler or redundant restatement of the tool name.

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?

The description gives useful output categories but, with no output schema and no annotations, it does not fully explain return format, filtering behavior, or access constraints. The rich parameter schema compensates for some of this, but the overall context is only partially self-contained.

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 the baseline is 3. The tool description does not add parameter-level meaning, but the schema already documents solution_id, job_id, actor_id, chain_id, and skill_id in detail.

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 uses a specific verb and resource ('Get execution metrics') and enumerates concrete content categories: timing, tool stats, bottlenecks, signals, and recommendations. It is clear but does not explicitly differentiate itself from sibling tools like ateam_get_execution_logs or ateam_get_progress.

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

Usage Guidelines2/5

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

The description provides no when-to-use or when-not-to-use guidance and names no alternatives. The only hint is '(Advanced.)', which signals caution but does not tell an agent when to choose this over sibling analytics or logging tools.

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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