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propose_plan

Analyze a codebase and generate a ranked list of unapproved work proposals for human review before any code changes.

Instructions

Analyze the project and return ranked, UNAPPROVED work proposals.

Use when: you want misterdev to recommend what to work on and let a human
approve a subset BEFORE any code is edited — the review gate. The proposals
are persisted, so ``get_plan`` re-reads them, ``approve_plan`` marks a
subset, and ``execute_plan`` builds the approved ones. The codebase is
analyzed in this process, so it never enters the client's context. Do NOT
use to execute immediately without review — that is ``build``. Related:
``get_plan``, ``approve_plan``, ``execute_plan``.

Side effects: spends LLM budget analyzing the project and writes the plan to
``.orchestrator/proposed_plan.json``; it edits NO source code.

Returns ``{items: [...]}`` — each item has an id, title, work_type,
rationale, and ``approved: false`` — or ``{error}`` on failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to the project to analyze. Example: '/Users/me/code/my-api'.
budgetNoMaximum US dollars to spend on analysis; > 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations, describes side effects: spends LLM budget, writes to .orchestrator/proposed_plan.json, edits no source code. Complements readOnlyHint=false and destructiveHint=false with concrete behavior.

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?

Well-structured with clear sections: purpose, usage, side effects, return value. Every sentence serves a function. Front-loaded with main action and outcome. 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?

Covers all essential aspects: what it does, when to use, not to use, side effects, return format. Includes output schema info and references sibling tools. No gaps identified.

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 description adds limited value. Mentions budget's purpose in side effects but doesn't detail parameter constraints beyond schema. Baseline 3 is appropriate.

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?

Clearly states it analyzes the project and returns ranked, unapproved work proposals. Distinguishes from siblings like build, get_plan, approve_plan, execute_plan by naming them and contrasting use cases.

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 'Use when' section explains the review gate purpose. Directly states 'Do NOT use to execute immediately without review — that is `build`.' Lists related tools for workflow 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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