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Delimit Daemon Run

delimit_daemon_run

Manually advance the daemon loop by N iterations for testing or scheduled cron-style runs, with dry-run logging or live execution.

Instructions

Advance the autonomous daemon by N iterations (Pro).

When to use: to manually advance the daemon loop one or more iterations, e.g. for testing or scheduled cron-style execution. When NOT to use: for inspection only (use delimit_daemon_status) or to classify an item (delimit_daemon_classify).

Sibling contrast: delimit_daemon_status reads; delimit_daemon_classify decides; this drives the loop.

Side effects: in dry_run mode, logs actions without executing them. In live mode, executes the daemon's automatable actions. Calls ai.daemon.run_loop with a 5-second interval between iterations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf True (default), log actions but do not execute.
iterationsNoNumber of iterations. 0 = infinite. Default 1.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed2 schema fields changedv4.7.9
    • changedInput schema / properties / dry_run / description
      Previous value: -"If true, log actions but don't execute (default true)"New value: +"If True (default), log actions but do not execute."
    • changedInput schema / properties / iterations / description
      Previous value: -"Number of loop iterations (0 = infinite, default 1)"New value: +"Number of iterations. 0 = infinite. Default 1."
  2. Addedv4.5.5

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations, the description discloses the dry_run vs live mode side effects, that it calls ai.daemon.run_loop, and the 5-second interval between iterations. This gives the agent a clear picture of what executing the tool actually does.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with labeled sections, front-loads the core behavior, and avoids filler. Every sentence contributes either usage guidance, sibling differentiation, or behavioral transparency.

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?

The tool carries a safety-relevant readOnlyHint=false and destructiveHint=false, and the description explains the side-effectful behavior in both modes. An output schema exists so return-value documentation is not required here. The description is sufficient for correct selection and invocation.

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 both parameters are already fully documented in the schema. The description adds narrative context around dry_run and iterations but does not meaningfully extend the parameter semantics beyond what the schema provides; baseline 3 applies.

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 opens with a specific verb and resource: 'Advance the autonomous daemon by N iterations.' It also explicitly contrasts itself with delimit_daemon_status and delimit_daemon_classify, so an agent can distinguish it from closely related siblings.

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?

It has a dedicated 'When to use' section with concrete examples like testing and cron-style execution, plus a 'When NOT to use' section naming delimit_daemon_status and delimit_daemon_classify as alternatives. The sibling contrast further clarifies the decision boundary.

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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