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strategy_plan

Returns a strategic approach protocol for planning multi-step work. Provides phased instructions scaled to task size: small, medium, or large.

Instructions

Functional alias for jambavan_yukti. Return a strategic approach protocol for planning multi-step work. Call BEFORE starting implementation of any non-trivial task. Returns phased instructions scaled to task size: small (just do it), medium (2-3 approaches + sequence), large (decompose + checkpoint). Auto-infers scale from task description if not provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesWhat you need to accomplish.
scaleNoTask scale. If omitted, auto-inferred from task description.
constraintsNoKnown constraints: time, compatibility, dependencies, scope limits.
Behavior4/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It transparently explains the scaling behavior (small/medium/large outputs) and auto-inference of scale. However, it does not mention side effects, idempotency, or output format details, which would improve transparency.

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 extremely concise with no redundant words. All sentences serve a purpose: identifying the function, stating when to use, describing outputs, and clarifying parameter behavior. It is well-structured and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite covering purpose, usage, and scaling behavior, the description lacks a detailed explanation of the output format (e.g., what 'phased instructions' look like). With no output schema, the agent may need more specific structure to parse the result correctly. The examples for scales are helpful but not fully complete.

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 each parameter described. The description adds value beyond the schema by explaining that the 'scale' parameter is optional and auto-inferred, and by detailing the meaning of each scale value (just do it, approaches+sequence, decompose+checkpoint).

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 it returns a 'strategic approach protocol for planning multi-step work' and distinguishes itself as a functional alias for jambavan_yukti. It specifies the output is 'phased instructions scaled to task size' with examples for small, medium, and large tasks, making the tool's purpose unmistakable.

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?

Explicitly states 'Call BEFORE starting implementation of any non-trivial task', providing clear when-to-use guidance. It does not explicitly list when-not-to-use or alternative tools, but the alias mention and context imply its role. The auto-inference of scale is also noted.

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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