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Stop a running timer

keeping_stop_timer
Destructive

Stop a running time entry in Keeping. Use dry-run to preview changes, then confirm after human review to apply.

Instructions

Stop an ongoing time entry (running timer) by setting its end. Implemented as PATCH /{orgId}/time-entries/{entry_id}/stop. Returns the updated 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. 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 ongoing entry to stop.
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?

Beyond the destructiveHint annotation, the description discloses the PATCH endpoint, return value including server_time_ms with fallback behavior, and dry-run preview mechanism. This adds significant behavioral context.

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 well-structured and front-loaded with the core action, but includes some repetitive details (e.g., endpoint path) that could be condensed. Still, most sentences earn their place.

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 fully explains the return object and error handling for missing headers. It covers the complete workflow from dry-run to confirmed execution, leaving no gaps.

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

Parameters5/5

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

Despite 100% schema coverage, the description adds critical semantics: clarifies the confirm parameter's dry-run workflow and restrictions, entry_id as numeric ID, and organisation_id as override for multi-org tokens.

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 clearly states the tool stops an ongoing timer by setting its end, with a specific verb and resource. It distinguishes itself from siblings like keeping_start_timer and keeping_resume_timer by focusing on stopping.

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?

The description provides explicit usage guidance: dry-run by default, then confirm only after human review. It warns the LLM not to set confirm autonomously, which is crucial for safe invocation.

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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