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Glama

Teamtailor Ops Control Plane

by app.vercel.ats-ops-control-plane-gateway

get_audit_event

Get one audit_event. Audit events for governance and change history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesaudit_event ID.
includeNo
query_jsonNoAdditional documented query parameters, including bracketed filter keys.
path_paramsNoValues for path placeholders such as {id} in a write operation.
detail_profileNooperational (default) returns a compact recruiting-ops projection with names, prose, and other personal fields omitted; pass full to include the raw API payload with those fields.operational

Schema Changelog

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

  1. Changed4 schema fields changed
    • changedInput schema / properties / detail_profile / default
      Previous value: -"full"New value: +"operational"
    • changedInput schema / properties / detail_profile / description
      Previous value: -"full returns raw API payload; operational returns a compact recruiting-ops projection."New value: +"operational (default) returns a compact recruiting-ops projection with names, prose, and other personal fields omitted; pass full to include the raw API payload with those fields."
    • addedInput schema / properties / path_params
      Added value: +{
+  "additionalProperties": {
+    "type": "string"
+  },
+  "description": "Values for path placeholders such as {id} in a write operation.",
+  "type": "object"
+}
    • removedInput schema / properties / reason
      Removed value: -{
-  "description": "Required when detail_profile=full.",
-  "maxLength": 500,
-  "minLength": 12,
-  "type": "string"
-}
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only defines audit events ('governance and change history') but does not mention return format, pagination, auth requirements, error behavior, or the effect of the detail_profile parameter that could alter response shape.

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 concise with two short sentences and no fluff. The second sentence adds context about audit events, but the overall brevity could be seen as under-specification rather than efficient conciseness, though it is appropriately front-loaded.

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?

Given the tool has 5 parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, provide usage context, or clarify the optional parameters like include and query_json. The description is too sparse to fully support an agent in invoking the tool correctly.

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 coverage is high (80%), with descriptions for id, query_json, path_params, and detail_profile, so the baseline is 3. The description itself adds no parameter information, and the 'include' parameter remains undocumented in both schema and description, leaving a gap.

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 clearly states 'Get one audit_event', specifying the verb and resource, which is a straightforward retrieval operation by ID. It distinguishes from list_audit_events by using 'one', but does not explicitly name the alternative or elaborate on the scope.

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?

No guidance is provided on when to use this tool versus alternatives like list_audit_events. The description implies usage by saying 'Get one' but omits any context about prerequisites, typical scenarios, or situations where another tool would be more appropriate.

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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TDQS

C2.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes due to specific resource names and detailed descriptions. However, the large number of similar get/list pairs (e.g., get_activity, get_answer) could cause an agent to misselect without careful reading, slightly reducing clarity.

Naming Consistency5/5

The naming follows a strict and predictable verb_noun pattern (list_/get_/create_/update_) using snake_case throughout. The only outlier is 'api_request', but it is a generic tool and does not break the overall pattern.

Tool Count3/5

With 62 tools, the set is large but arguably justified by the breadth of the Teamtailor domain (candidates, jobs, applications, interviews, notes, etc.). Still, it exceeds the typical 3-15 range for high coherence, making navigation heavy for agents.

Completeness3/5

The tool set provides comprehensive read access (get/list) for most entities, but lacks delete operations entirely and has limited update coverage (only candidate, job, job_application). The 'api_request' tool can compensate, but the surface has notable gaps in mutation capabilities.

Resources