Skip to main content
Glama

delimit_loop_config

Configure autonomous build loop safeguards by setting max iterations, cost cap, error threshold, and approval policy before starting a session.

Instructions

Configure autonomous build loop safeguards.

When to use: BEFORE starting a loop session — to set max iterations, cost cap, error threshold, approval policy. When NOT to use: to read loop metrics (use delimit_loop_status) or drive the loop (delimit_build_loop).

Sibling contrast: delimit_loop_status reads metrics; delimit_build_loop runs; this configures the policy.

Side effects: writes the loop session config via ai.loop_engine.loop_config. Only non-zero/non-empty values are applied — pass just the fields you want to change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idNoSession to configure. Empty = create new.
max_iterationsNoMax tasks before stopping. Default 50.
cost_capNoMax session cost in dollars. Default 5.0.
auto_consensusNoIf True, suggest consensus when ledger empty.
error_thresholdNoConsecutive errors before circuit-breaker trips. Default 3.
statusNoSet loop status — "running", "paused", "stopped".
require_approval_forNoComma-separated action types requiring human approval.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses side effects (writes config via ai.loop_engine.loop_config) and behavior (only applies non-zero/non-empty values). Lacks details on error handling or auth, but overall adequate.

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?

Concise with structured sections (When to use, When NOT, sibling contrast, side effects). Front-loaded with purpose. Every sentence adds value.

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 7 parameters, no required fields, and presence of output schema, the description provides sufficient context for correct usage. Covers usage context, alternatives, side effects, and key parameter behavior.

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 coverage is 100%, so baseline is 3. The description summarizes key parameters (max iterations, cost cap, etc.) but does not add meaning beyond what schema descriptions already provide.

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 states a specific verb ('Configure') and resource ('autonomous build loop safeguards'). It explicitly distinguishes from siblings by naming delimit_loop_status and delimit_build_loop.

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?

Provides clear when-to-use ('BEFORE starting a loop session') and when-not-to-use (for metrics or driving the loop), with explicit alternative tool names.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/delimit-ai/delimit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server