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wm_explain

Get the nutrition label for any workspace path: its policy grade (G1-G4), why it was assigned, and what cleanup would do. Use it to understand why a file or directory is or isn't cleanup-worthy.

Instructions

Return the 'nutrition label' for one path: the grade the policy assigns (G1-G4), why it is graded that way, and what cleanup would do to it. Use this when you or the user ask why a specific file or directory is (or is not) cleanup-worthy. Read-only; fails with a clear message if the path is outside the workspace or the policy is missing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesPath to explain, relative to the workspace root (e.g. 'logs' or 'src/util.py').
Behavior5/5

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

With no annotations present, the description carries the full behavioral burden, and it does so thoroughly. It explicitly labels the operation 'Read-only' and discloses the two error cases: paths outside the workspace and missing policy. It also describes the shape of the output (grade, reasoning, cleanup effect), giving the agent a solid expectation of what will come back.

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?

Three sentences with no filler. The core function is front-loaded in the first sentence, the usage condition is second, and the read-only plus failure messages are third. Every sentence adds essential information and the description remains compact.

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?

For a one-parameter, read-only explain tool with no output schema and no annotations, this description is fully sufficient. It covers what the tool does, what it returns, when to use it, that it is safe (read-only), and the failure modes. An agent has everything needed to decide when to call it and what to expect.

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?

The schema already provides a complete description of the single 'path' parameter, including its relative-to-workspace-root format and examples ('logs' or 'src/util.py'). The description adds no further parameter-level detail, but none is needed; per the calibration rule, baseline 3 is appropriate when schema coverage is 100%.

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 opens with a specific verb and resource: 'Return the nutrition label for one path', and goes on to enumerate exactly what the output contains (G1-G4 grade, rationale, cleanup effect). This clearly distinguishes it from the sibling tools: wm_clean acts on paths, wm_audit and wm_health operate at a broader level, whereas wm_explain is specifically about interrogating a single path. There is no ambiguity about what the tool does.

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 second sentence explicitly states when to use it: 'Use this when you or the user ask why a specific file or directory is (or is not) cleanup-worthy.' This gives clear context for invoking it. It does not explicitly name a sibling as an alternative, but the provided sibling list and this conditional are enough to route an agent correctly without excluding anything.

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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