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by io.github.saloprj
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agents_traces_list

Read-onlyIdempotent

List recent execution traces for an agent — the same data as /admin/requests, scoped to one agent and readable by an LLM.

Use this when an agent call timed out, drafted the wrong response, or you want to know which tool/LLM call burned the latency. Pair with agents.trace_get for full detail on a specific trace.

Filters: status, success, source (single value or comma-separated: agent,voice), date_from/date_to (ISO-8601), pagination via limit/offset.

Returns returned_count, dropped_on_page (should be 0 — positive means the backend agent_id predicate let something through), and has_more. Edge case: a raw page of all-dedup-dropped rows yields returned_count=0, has_more=true; re-call with offset += limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows per page (1–100).
offsetNoRows to skip for pagination. OMIT to start at row 0 (default).
sourceNoFilter by trace source. Single value or comma-separated, e.g. 'agent,voice'. Values: agent / auto_reply / agentic / outreach / voice. Note: source='agent' also matches voice traces today (known upstream bug).
statusNoFilter by status. OMIT to include all statuses.
date_toNoISO-8601 upper bound on created_at.
successNoFilter to succeeded (true) or failed (false) runs only. OMIT to include both.
agent_idYesAgent ID to pull traces for (must belong to your workspace).
date_fromNoISO-8601 lower bound on created_at, e.g. '2026-04-10T00:00:00Z'.
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / in_workspace
      Added value: +{
+  "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
+  "type": "integer"
+}
  2. Added
  3. Removed
  4. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description still adds real behavioral context: the response fields (returned_count, dropped_on_page, has_more), what a non-zero dropped_on_page implies, and the tricky edge case where a fully deduped page returns returned_count=0 with has_more=true and requires re-calling with offset += limit. That is exactly the kind of operational nuance annotations cannot express.

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?

Front-loaded with purpose, then usage, then filters, then return-shape caveats — a logical progression with no filler sentences. It is on the longer side, but nearly every clause carries actionable information, so the size is defensible.

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

Completeness5/5

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

With no output schema, the description takes on the burden of explaining the return shape and does so (returned_count, dropped_on_page, has_more) plus the pagination edge case and recovery step. Combined with the filter inventory and the pointer to agents.trace_get, an agent has everything needed to call and interpret this 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 description coverage is 100%, so every parameter is already documented in the schema, and the description's filter paragraph largely restates it (status, success, source, date range, limit/offset). It adds modest consolidation value by grouping the filters in one place, but no new semantics such as default behavior or interaction rules. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List recent execution traces for an agent') and immediately scopes it ('scoped to one agent'), plus maps it to a known surface (/admin/requests). It also names the sibling that provides the complementary capability (agents.trace_get), so an agent can distinguish it from agents_traces_stats and agents_activity without opening a schema.

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

Usage Guidelines5/5

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

Gives explicit triggering scenarios — an agent call timed out, a wrong draft, or latency investigation — and explicitly routes to agents.trace_get for per-trace detail. That is a clear when-to-use plus a named alternative, leaving little to inference.

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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