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Glama

record_interaction

Log success, latency, and failure data after using an agent, tool, or service to build a shared reputation dataset other agents can query before choosing tools.

Instructions

Record an interaction with an agent, tool, or service after using it. Helps build the shared reputation dataset for the community.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorYesYour agent/system identifier
sourceNo
targetYesIdentifier of what you used
outcomeYes
task_typeYesWhat kind of task was performed. e.g. 'web_search', 'code_gen'
latency_msNoHow long it took in milliseconds
target_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.11

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It usefully reveals that submitted data feeds a shared, persistent 'reputation dataset for the community' – which implies public visibility of the write. However, it says nothing about required permissions, whether records are immutable, deduplication, or rate limits.

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?

Two short sentences, zero filler, purpose front-loaded in the first clause. Nothing to trim.

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

Completeness2/5

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

This is a 7-parameter mutation tool with no annotations and no output schema, so the description must carry more weight. It omits what happens after submission, whether the call can fail on validation, and what the response contains – important for an agent deciding whether to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

7 parameters with only 57% schema description coverage, and the description adds no parameter-level meaning at all. Enum-constrained fields (source, outcome, target_type) are self-documenting in the schema, but 'source' in particular has no description anywhere and the description does nothing to compensate for the undocumented fields.

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 and resource ('Record an interaction with an agent, tool, or service'), which is unambiguous. It does not differentiate from the sibling tools (get_lowdown, compare_tools, get_node_stats), but those serve clearly different functions, so confusion risk is low.

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?

'after using it' gives implied timing guidance – call this once you have finished consuming a target. There is no explicit statement of when not to use it, no mention of prerequisites, and no comparison to alternatives.

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