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delegate_task

Offload tasks to a cheaper model or summarize vault files. Returns small files directly; delegates large files for summarization.

Instructions

Offload work to a cheaper model or summarize vault files.

When project is provided, reads a vault file. Small files (≤50 lines) are returned directly. Large files are auto-delegated to a worker for summarization — falls back to raw content if workers are unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptNoThe task description or code to process.
contextNoOptional system context for the model.
modelNo'auto', 'ollama', 'openrouter-free', 'openrouter' (paid), or model ID.auto
max_tokensNoMaximum tokens in the response.
max_cost_per_requestNoMax USD. 0 = free models only.
projectNoProject slug for vault summarization mode.
sectionNoShortcut name for summarization. Ignored if path is set.context
pathNoRelative path to a .md file. Overrides section.
max_summary_linesNoTarget summary length for summarization.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the sparse annotations (readOnlyHint, destructiveHint, idempotentHint), the description reveals key behaviors: auto-delegation to workers for large files, fallback to raw content if workers unavailable, and file size thresholds. This adds significant transparency not captured by 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 two sentences, front-loaded with the core purpose, and every sentence adds necessary context without redundancy. It is extremely efficient and well-structured.

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 the tool's complexity (9 parameters, two modes, output schema exists), the description covers the major behavioral aspects: the two modes, file size handling, and fallback. An output schema exists, so return values need not be explained. The description is sufficiently complete for an agent to understand when and how to invoke the tool.

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 description coverage is 100%, so the baseline is 3. The description adds value by explaining how parameters like project, path, and max_summary_lines relate to the two modes (offload vs summarization) and file size behavior, though it does not detail each parameter individually.

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 two distinct purposes: offloading work to a cheaper model and summarizing vault files. It provides a specific verb+resource for each mode, and distinguishes itself from sibling tools that deal with vault operations but not combined cheap model routing or summarization.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes conditional guidance ('When project is provided, reads a vault file') and describes behavior for file sizes, indicating when to expect summarization vs direct return. However, it does not explicitly state when to use this tool over alternatives or provide exclusions, leaving some implicit context.

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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