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list_time_entries

Read-only

Read declared time for a week or custom period, including task and project names, daily and project totals, and entry IDs needed to edit records. Use it before making changes.

Instructions

Read declared time over a week or a period, with task and project names filled in, per-day and per-project totals, and the identifiers needed to change an entry. Read before you write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoLast day of an explicit period. Defaults to `from`.
fromNoFirst day of an explicit period. Ignored when `week` is set.
taskNoKeep only this task, by name or id.
userNoWhose time to read. Defaults to the user this server acts as.
weekNoA week: `this week`, `last week`, `2026-W38`, or a date inside it.
limitNoHow many objects to return. Upstream maximum is 1000.
offsetNoHow many objects to skip, for the next page.
projectNoKeep only this project, by name, code or id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesLast day of the period.
daysYesOne line per day that carries time.
fromYesFirst day of the period.
userYesWhose time this is.
weekNoThe ISO week, when the period is exactly one.
totalYesThe same, human readable.
entriesNoThe declarations themselves, when the caller asked for them.
projectsYesOne line per project, largest first.
total_hoursYesThe same, in decimal hours.
total_secondsYesDeclared time over the period, in seconds.
missing_workdaysYesWorking days of the period with nothing declared.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuine behavioral context beyond that: names/totals are filled in, per-day and per-project aggregates are produced, and it returns the identifiers needed to mutate entries, which is useful for planning a read-then-write flow.

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?

One dense sentence front-loaded with the verb and resource, plus a short four-word directive. Little waste, though the run-on clause list is slightly heavy for the amount of information conveyed.

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?

With an output schema present, the description need not document return values, and the readOnly annotations cover the safety profile. It conveys scope (week/period), enrichment (names, totals), and the write-workflow hook, leaving little an agent would need before calling it.

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 (week, from/to, task, project, user, limit, offset) is already documented in the schema. The description adds no parameter-level syntax or default details beyond that baseline.

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?

States a specific verb (read) and resource (declared time entries), with the added scope detail of week/period reads. It is clearly distinct from the write siblings (log_time, update_time_entry, delete_time_entry), but it never explicitly contrasts itself with the closest read alternative, `timesheet`.

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?

"Read before you write" gives an implicit workflow cue for pairing with update/delete tools, but no explicit when-to-use-vs-alternatives guidance is given (e.g., when to prefer this over `timesheet` or `export_times_and_leaves`). Usage must be inferred.

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