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Resume a stopped timer

keeping_resume_timer
Destructive

Resume a previously-stopped time entry as an ongoing timer. Uses dry-run preview before confirming the update.

Instructions

Resume a previously-stopped time entry as an ongoing timer. Implemented as POST /{orgId}/time-entries/{entry_id}/resume. Returns the resumed entry plus server_time_ms — the millisecond-precision server timestamp captured from the X-Server-Time-Ms response header (TIMER-02). When the header is missing or unparseable, server_time_ms falls back to the local clock and a warning is logged to stderr. NOTE: Keeping may return a different time_entry.id than the input entry_id — when the original entry's date is no longer 'today', Keeping creates a NEW ongoing entry rather than modifying the old one. Always read time_entry.id from the response; do not assume it matches your input. Cannot resume locked entries (returns a 403 error). DRY-RUN BY DEFAULT — call without confirm first to receive a would_post preview; call again with confirm: true ONLY after a human reviewed the preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNoSet to true ONLY after a human has reviewed the would_post preview returned by a prior dry-run call. The MCP client (LLM) MUST NOT set this autonomously — wait for the human to type 'yes' / 'confirm'.
entry_idYesNumeric Keeping time-entry id of the previously-stopped entry to resume.
organisation_idNoOverride KEEPING_ORG_ID; required for multi-org tokens.
Behavior5/5

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

The description adds significant behavioral context beyond annotations: dry-run behavior, ID change on non-today entries, fallback for server_time_ms, and error handling (403 for locked). Annotations only indicate readOnlyHint=false and destructiveHint=true; the description elaborates fully.

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 lengthy but every sentence adds value. It is front-loaded with the main purpose. Could be slightly more concise, but no unnecessary words.

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?

Given no output schema, the description explains the return value (resumed entry plus server_time_ms) and covers key scenarios (locked entries, ID change). Complete for a tool of this complexity.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds critical context for the 'confirm' parameter (must not be set autonomously) and explains the dry-run flow, which goes beyond schema descriptions.

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?

The description starts with a clear verb+resource: 'Resume a previously-stopped time entry as an ongoing timer.' This distinguishes it from sibling tools like keeping_start_timer and keeping_stop_timer.

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?

Explicit step-by-step guidance: dry-run first, then confirm only after human review. Also notes limitations (locked entries, ID change). Provides a complete usage pattern.

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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