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

With no annotations, the description carries the full burden, and it does meaningful work: it discloses the return artifacts (letter grade, findings, a safer config, README badge Markdown) and a privacy behavior ('Inputs are not stored or logged'). It does not explicitly state there are no side effects on the caller's config or describe failure behavior on malformed JSON, but overall it exceeds the minimum for an unannotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with purpose, followed by return values and the privacy note. No filler; every sentence adds information.

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

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

There is no output schema, so the description appropriately explains the return values and adds a privacy guarantee. It is nearly complete for a two-parameter analysis tool; only edge-case behavior (invalid JSON, grading criteria) is unaddressed, which is acceptable here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters are already documented, making 3 the baseline. The description adds some value by naming the config file formats, but it lists only three of the four enum values and omits cursor_mcp, so it does not fully clarify the 'tool' parameter's option set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Grade'), a precise resource ('AI coding agent permissions config'), and lists concrete example files (Claude Code settings.json, Gemini CLI settings.json, mcp.json). An agent can immediately tell this is an analysis tool for agent configs, which is clearly distinct from the sibling tools get_index_stats and get_leaderboard.

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

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

The description gives clear context on what inputs are accepted and what the tool produces, so an agent knows when to reach for it. It stops short of explicit when-not conditions or naming alternatives, but the sibling tools are unrelated in domain, so this is a minor gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.