Skip to main content
Glama

Repair network (bounded)

repair_network
Destructive

Scan and repair cook errors in a TouchDesigner subtree by classifying and planning safe fixes, bounded by a step limit. Optionally apply known-safe repairs when dry_run is disabled.

Instructions

Bounded, autonomous repair: scan cook errors under a subtree, classify each, and plan a safe fix, capped at max_steps so it can never run away. Defaults to dry_run (PLAN only, no changes). Set dry_run:false to apply the known-safe fixes — resetting a broken parameter expression to constant mode, and re-enabling a bypassed/display-off op — within the same bound; risky cases (DAT syntax errors, missing inputs, unclassified errors) are always PLAN-only. Re-checks errors after applying and stops at the bound or when errors clear. Returns {parent_path, dry_run, max_steps, errors_before, errors_after, steps[], remaining[], warnings, rolled_back}. Use it as the diagnostic 'try the obvious safe fixes' loop after a build; for raw triage use summarize_td_errors / get_td_node_errors instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parent_pathNoRoot of the subtree to scan + repair./project1
max_stepsNoHard cap on repair attempts — the bound that prevents runaway repair.
dry_runNoWhen true (default), only PLAN fixes (no changes applied). Set false to apply within the bound.
Behavior5/5

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

Annotations indicate readOnlyHint=false, destructiveHint=true, openWorldHint=true. The description expands on these by detailing the bounded autonomous repair mechanism, dry_run default, known-safe fixes, and risky case handling. No contradiction with annotations.

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 concise yet comprehensive, front-loading key information (bounded, autonomous, dry_run). Every sentence contributes value, no fluff.

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?

Despite no output schema, the description fully explains return fields and behavior. Given the tool's moderate complexity and rich annotations, the description is complete and covers all necessary context.

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% with descriptions for all 3 parameters, so baseline is 3. The description adds context like 'Root of the subtree' and 'Hard cap on repair attempts', enhancing understanding beyond the schema alone.

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 provides a specific verb ('repair') and resource ('network') with clear scope: scanning cook errors under a subtree, classifying, and planning safe fixes. It distinguishes itself from sibling tools like summarize_td_errors and get_td_node_errors by noting its use as a diagnostic 'try the obvious safe fixes' 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?

Explicit guidance on when to use: 'Use it as the diagnostic "try the obvious safe fixes" loop after a build; for raw triage use summarize_td_errors / get_td_node_errors instead.' This directly tells the agent when to prefer this tool over alternatives.

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/Pantani/tdmcp'

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